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BEGIN:VEVENT
SUMMARY:Daniel Forger (University of Michigan)
DTSTART:20210325T020000Z
DTEND:20210325T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/1
DESCRIPTION:Title: The mathematics of the wearables with applications to
circadian rhythms and sleep\nby Daniel Forger (University of Michigan)
as part of IBS Biomedical Mathematics Online Colloquium\n\n\nAbstract\nMi
llions of individuals track their steps\, heart rate\, and other physiolog
ical signals through wearables. This data scale is unprecedented\; I will
describe several of our apps and ongoing studies\, each of which collects
wearable and mobile data from thousands of users\, even in > 100 countries
. This data is so noisy that it often seems unusable and in desperate need
of new mathematical techniques to extract key signals used in the (ode) m
athematical modeling typically done in mathematical biology. I will descri
be several techniques we have developed to analyze this data and simulate
models\, including gap orthogonalized least squares\, a new ansatz for cou
pled oscillators\, which is similar to the popular ansatz by Ott and Anton
sen\, but which gives better fits to biological data and a new level-set K
alman Filter that can be used to simulate population densities. My focus a
pplications will be determining the phase of circadian rhythms\, the scori
ng of sleep and the detection of COVID with wearables.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/1/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Ramon Grima (University of Edinburgh)
DTSTART:20210526T080000Z
DTEND:20210526T090000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/2
DESCRIPTION:Title: Neural network aided approximation and parameter infer
ence of stochastic models of gene expression\nby Ramon Grima (Universi
ty of Edinburgh) as part of IBS Biomedical Mathematics Online Colloquium\n
\n\nAbstract\nNon-Markov models of stochastic biochemical kinetics often i
ncorporate explicit time delays to effectively model large numbers of inte
rmediate biochemical processes. Analysis and simulation of these models\,
as well as the inference of their parameters from data\, are fraught with
difficulties because the dynamics depends on the system’s history. Here
we use an artificial neural network to approximate the time-dependent dist
ributions of non-Markov models by the solutions of much simpler time-inhom
ogeneous Markov models\; the approximation does not increase the dimension
ality of the model and simultaneously leads to inference of the kinetic pa
rameters. The training of the neural network uses a relatively small set o
f noisy measurements generated by experimental data or stochastic simulati
ons of the non-Markov model. We show using a variety of models\, where the
delays stem from transcriptional processes and feedback control\, that th
e Markov models learnt by the neural network accurately reflect the stocha
stic dynamics across parameter space.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/2/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Luonan Chen (Shanghai Institutes for Biological Sciences)
DTSTART:20210415T020000Z
DTEND:20210415T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/3
DESCRIPTION:Title: Dynamics-based data science in biology\nby Luonan
Chen (Shanghai Institutes for Biological Sciences) as part of IBS Biomedic
al Mathematics Online Colloquium\n\n\nAbstract\nLife science has been a pr
osperous subject for a long time\, and is still developing with high speed
now. One of its major aims is to study the mechanisms of various biologic
al processes on the basis of biological big-data. Many statistics-based me
thods have been proposed to catch the essence by mining those data\, inclu
ding the popular category classification\, variables regression\, group cl
ustering\, statistical comparison\, dimensionality reduction\, and compone
nt analysis\, which\, however\, mainly elucidate static features or steady
behavior of living organisms due to lack of temporal data. But\, a biolog
ical system is inherently dynamic\, and with increasingly accumulated time
-series data\, dynamics-based approaches based on physical and biological
laws are demanded to reveal dynamic features or complex behavior of biolog
ical systems.\nIn this talk\, I will present a new concept "dynamics-based
data science" and the approaches for studying dynamical bio-processes\, i
ncluding dynamical network biomarkers (DNB)\, autoreservoir neural network
s (ARNN) and partical cross-mapping. These methods are all data-driven or
model-free approaches but based on the theoretical frameworks of nonlinear
dynamics. We show the principles and advantages of dynamics-based data-dr
iven approaches as explicable\, quantifiable\, and generalizable. In parti
cular\, dynamics-based data science approaches exploit the essential featu
res of dynamical systems in terms of data\, e.g. strong fluctuations near
a bifurcation point\, low-dimensionality of a center manifold or an attrac
tor\, and phase-space reconstruction from a single variable by delay embed
ding theorem\, and thus are able to provide different or additional inform
ation to the traditional approaches\, i.e. statistics-based data science a
pproaches. The dynamical-based data science approaches will further play a
n important role in the systematical research of biology and medicine in f
uture.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/3/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Olaf Wolkenhauer (University of Rostock)
DTSTART:20210421T080000Z
DTEND:20210421T093000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/4
DESCRIPTION:Title: Advice to my younger self\nby Olaf Wolkenhauer (Un
iversity of Rostock) as part of IBS Biomedical Mathematics Online Colloqui
um\n\n\nAbstract\nAge brings the benefit of experience and looking back at
my job as a professor\, there are a couple of things that fall into the c
ategory “I wish someone had told me that earlier”. In this seminar\, I
would like to share some of the things I learned and which\, I hope\, wil
l be useful for younger scientists.\n\nThe questions I will touch upon inc
lude\n\n- What is productivity\, for a scientist?\n\n- What are qualities
of successful people?\n\n- How can one create motivation and success?\n\n-
How to organize myself? (project management\; getting things done)\n\n- H
ow to communicate effectively?\n\n- Seeking fulfillment\n\nThe seminar is
targeted at PhD students\, postdocs\, and junior group leaders.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/4/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Andrew Phillpis (Monash University)
DTSTART:20210610T020000Z
DTEND:20210610T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/5
DESCRIPTION:Title: Towards individualized predictions of human sleep and
circadian timing\nby Andrew Phillpis (Monash University) as part of IB
S Biomedical Mathematics Online Colloquium\n\n\nAbstract\nAccurate assessm
ent of circadian timing is critical to many applications\, including timin
g of drug delivery\, prediction of neurobehavioral performance\, and optim
ized scheduling of sleep. Current methods for measuring circadian timing a
re onerous and do not produce results in real time. Mathematical models ha
ve been developed for predicting circadian timing from an individual’s l
ight exposure patterns\, which can be applied to passively collected data.
These models are now well validated in the field at the group-average lev
el\, but tend to perform poorly at the individual level. One potential sol
ution to this problem is the estimation of model parameters at an individu
al level. We explored whether this approach could be applied to parameters
relating to an individual’s light sensitivity. We found that these para
meters can account for inter-individual and intra-individual variation in
circadian timing. These findings demonstrate that model parametrization ba
sed on physiological measurements of light sensitivity could lead to more
accurate individual-level circadian phase prediction.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/5/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Bärbel Finkenstädt Rand (University of Warwick)
DTSTART:20210714T080000Z
DTEND:20210714T090000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/6
DESCRIPTION:Title: Inference for Circadian Pacemaking\nby Bärbel Fin
kenstädt Rand (University of Warwick) as part of IBS Biomedical Mathemati
cs Online Colloquium\n\n\nAbstract\nOrganisms have evolved an internal bio
logical clock which allows them to temporally regulate and organize their
physiological and behavioral responses to cope in an optimal way with the
fundamentally periodic nature of the environment. It is now well establish
ed that the molecular genetics of such rhythms within the cell consist of
interwoven transcriptional-translational feedback loops involving about 15
clock genes\, which generate circa 24-h oscillations in many cellular fun
ctions at cell population or whole organism levels. We will present statis
tical methods and modelling approaches that address newly emerging large c
ircadian data sets\, namely spatio-temporal gene expression in SCN neurons
and rest-activity actigraph data obtained from non-invasive e-monitoring\
, both of which provide unique opportunities for furthering progress in un
derstanding the synchronicity of circadian pacemaking and address implicat
ions for monitoring patients in chronotherapeutic healthcare.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/6/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Mustafa Khammash (ETH Zürich)
DTSTART:20210728T080000Z
DTEND:20210728T090000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/7
DESCRIPTION:Title: Theory and design of molecular integral feedback contr
ollers\nby Mustafa Khammash (ETH Zürich) as part of IBS Biomedical Ma
thematics Online Colloquium\n\n\nAbstract\nHomeostasis is a recurring them
e in biology that ensures that regulated variables robustly adapt to envir
onmental perturbations. This robust perfect adaptation feature is achieved
in natural circuits by using integral control\, a negative feedback strat
egy that performs mathematical integration to achieve structurally robust
regulation. Despite its benefits\, the synthetic realization of integral f
eedback in living cells has remained elusive owing to the complexity of th
e required biological computations. In this talk I will show that there is
a single fundamental biomolecular controller topology that realizes inte
gral feedback and achieves robust perfect adaptation in arbitrary intracel
lular networks with noisy dynamics. This adaptation property is guaranteed
both for the population-average and for the time-average of single cells.
On the basis of this concept\, I will describe a genetically engineered
synthetic integral feedback controller in living cells and demonstrate it
s tunability and adaptation properties. A growth-rate control application
in Escherichia coli shows the intrinsic capacity of our integral control
ler to deliver robustness and highlights its potential use as a versatile
controller for regulation of biological variables in uncertain networks. T
hese results provide conceptual and practical tools in the area of cyberge
netics\, for engineering synthetic controllers that steer the dynamics of
living systems.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/7/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Aaron A. King (University of Michigan)
DTSTART:20210916T020000Z
DTEND:20210916T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/8
DESCRIPTION:Title: Stochastic processes as scientific instruments: effici
ent inference based on stochastic dynamical systems\nby Aaron A. King
(University of Michigan) as part of IBS Biomedical Mathematics Online Coll
oquium\n\n\nAbstract\nQuestions about the mechanistic operation of biologi
cal systems are naturally formulated as stochastic processes\, but confron
ting such models with data can be challenging. In this talk\, I describe
the essence of the difficulty\, highlighting both the technical issues and
the importance of the “plug-and-play property”. I then illustrate so
me effective approaches to efficient inference based on such models. I co
nclude by sketching promising new developments and describing some open pr
oblems.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/8/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Helen Byrne (University of Oxford)
DTSTART:20210908T080000Z
DTEND:20210908T090000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/9
DESCRIPTION:Title: [CANCELED] Approaches to understanding tumour-immune i
nteractions\nby Helen Byrne (University of Oxford) as part of IBS Biom
edical Mathematics Online Colloquium\n\n\nAbstract\nWhile the presence of
immune cells within solid tumours was initially viewed positively\, as the
host fighting to rid itself of a foreign body\, we now know that the tumo
ur can manipulate immune cells so that they promote\, rather than inhibit\
, tumour growth. Immunotherapy aims to correct for this by boosting and/or
restoring the normal function of the immune system. Immunotherapy has del
ivered some extremely promising results. However\, the complexity of the t
umour-immune interactions means that it can be difficult to understand why
one patient responds well to immunotherapy while another does not. In thi
s talk\, we will show how mathematical\, statistical and topological metho
ds can contribute to resolving this issue and present recent results which
illustrate the complementary insight that different approaches can delive
r.\n\nThis talk has been CANCELED due to unexpected circumstances.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/9/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Chao Tang (Peking University)
DTSTART:20211021T020000Z
DTEND:20211021T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/10
DESCRIPTION:Title: Scaling in development\nby Chao Tang (Peking Univ
ersity) as part of IBS Biomedical Mathematics Online Colloquium\n\n\nAbstr
act\nWithin a given species\, fluctuations in egg or embryo size is unavoi
dable. Despite this\, the gene expression pattern and hence the embryonic
structure often scale in proportion with the body length. This scaling phe
nomenon is very common in development and regeneration\, and has long fasc
inated scientists. I will first discuss a generic theoretical framework to
show how scaling gene expression pattern can emerge from non-scaling morp
hogen gradients. I will then demonstrate that the Drosophila gap gene syst
em achieves scaling in a way that is entirely consistent with our theory.
Remarkably\, a parameter-free model based on the theory quantitatively acc
ounts for the gap gene expression pattern in nearly all morphogen mutants.
Furthermore\, the regulation logic and the coding/decoding strategy of th
e gap gene system can be revealed. Our work provides a general theoretical
framework on a large class of problems where scaling output is induced by
non-scaling input\, as well as a unified understanding of scaling\, mutan
ts’ behavior and regulation in the Drosophila gap gene and related syste
ms.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/10/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Annabelle Ballesta (University of Warwick)
DTSTART:20211027T080000Z
DTEND:20211027T090000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/11
DESCRIPTION:Title: Systems Pharmacology towards Personalized Chronothera
py\nby Annabelle Ballesta (University of Warwick) as part of IBS Biome
dical Mathematics Online Colloquium\n\n\nAbstract\nChronotherapeutics- tha
t is administering drugs following the patient's biological rhythms over t
he 24 h span- may largely impact on both drug toxicities and efficacy in v
arious pathologies including cancer [1]. However\, recent findings highlig
ht the critical need of personalizing circadian delivery according to the
patient sex\, genetic background or chronotype. Chronotherapy personalizat
ion requires to reliably account for the temporal dynamics of molecular pa
thways of patient’s response to drug administration [2]. In a context wh
ere clinical molecular data is usually minimal in individual patients\, mu
lti-scale- from preclinical to clinical- systems pharmacology stands as an
adapted solution to describe gene and protein networks driving circadian
rhythms of treatment efficacy and side effects and allow for the design of
personalized chronotherapies.\n\nSuch a multiscale approach is being unde
rtaken for personalizing the circadian administration of irinotecan\, one
of the cornerstones of chemotherapies against digestive cancers. Irinoteca
n molecular chronopharmacology was studied at the cellular level in an in
vitro/in silico investigation. Large transcription rhythms of period T= 28
h 06 min (SD 1 h 41 min) moderated drug bioactivation\, detoxification\,
transport\, and target in synchronized Caco-2 colorectal cancer cell cultu
res. These molecular rhythms translated into statistically significant cha
nges according to drug timing in irinotecan pharmacokinetics\, pharmacodyn
amics\, and drug-induced apoptosis. Clock silencing through siBMAL1 exposu
re ablated all the chronopharmacology mechanisms. Mathematical modeling hi
ghlighted circadian bioactivation and detoxification as the most critical
determinants of irinotecan chronopharmacology [3]. The cellular model of i
rinotecan chronoPK-PD was further tested on SW480 and SW620 cell lines\, a
nd connected to a new clock model to investigate the feasibility of irinot
ecan timing personalization solely based on clock gene expression monitori
ng (Hesse\, Martinelli et al.\, under review).\n\nTo step towards the clin
ics\, on one side\, mathematical models of irinotecan\, oxaliplatin and 5-
fluorouracil pharmacokinetics were designed to precisely compute the expos
ure concentration of tissue over time after complex chronomodulated drug a
dministration through programmable pumps [4]. On the other side\, we aimed
to design a model learning methodology predicting from non-invasively mea
sured circadian biomarkers (e.g. rest-activity\, body temperature\, cortis
ol\, food intake\, melatonin)\, the patient peripheral circadian clocks an
d associated optimal drug timing [5]. We investigated at the molecular sca
le the influence of systemic regulators on peripheral clocks in four class
es of mice (2 strains\, 2 sexes). Best models involved a modulation of eit
her Bmal1 or Per2 transcription most likely by temperature or nutrient exp
osure cycles. The strengths of systemic regulations were found to be signi
ficantly different according to mouse sex and genetic background.\n\nRefer
ences \n\n1. Ballesta\, A.\, et al.\, Systems Chronotherapeutics. Pharmaco
l Rev\, 2017. 69(2): p. 161-199.\n\n2. Sancar\, A. and R.N. Van Gelder\, C
locks\, cancer\, and chronochemotherapy. Science\, 2021. 371(6524).\n\n3.
Dulong\, S.\, et al.\, Identification of Circadian Determinants of Cancer
Chronotherapy through In Vitro Chronopharmacology and Mathematical Modelin
g. Mol Cancer Ther\, 2015.\n\n4. Hill\, R.J.W.\, et al.\, Optimizing circa
dian drug infusion schedules towards personalized cancer chronotherapy. PL
oS Comput Biol\, 2020. 16(1): p. e1007218.\n\n5. Martinelli\, J.\, et al.\
, Model learning to identify systemic regulators of the peripheral circadi
an clock. 2021\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/11/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Lisa J. Fauci (Tulane University)
DTSTART:20211111T020000Z
DTEND:20211111T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/12
DESCRIPTION:Title: Biofluiddynamics of reproduction\nby Lisa J. Fauc
i (Tulane University) as part of IBS Biomedical Mathematics Online Colloqu
ium\n\n\nAbstract\nFrom fertilization to birth\, successful mammalian repr
oduction relies on interactions of elastic structures with a fluid environ
ment. Sperm flagella must move through cervical mucus to the uterus and i
nto the oviduct\, where fertilization occurs. In fact\, some sperm may ad
here to oviductal epithelia\, and must change their pattern of oscillation
to escape. In addition\, coordinated beating of oviductal cilia also dri
ve the flow. Sperm-egg penetration\, transport of the fertilized ovum fro
m the oviduct to its implantation in the uterus and\, indeed\, birth itsel
f are rich examples of elasto-hydrodynamic coupling. We will discuss suc
cesses and challenges in the mathematical and computational modeling of th
e biofluids of reproduction.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/12/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Jeremy Gunawardena (Harvard University)
DTSTART:20211118T020000Z
DTEND:20211118T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/13
DESCRIPTION:Title: Following the energy in cellular information processi
ng\nby Jeremy Gunawardena (Harvard University) as part of IBS Biomedic
al Mathematics Online Colloquium\n\n\nAbstract\nJohn Hopfield first pointe
d out that there are barriers - we call them Hopfield barriers - to biolog
ical information-processing at thermodynamic equilibrium. I will explain h
ow the widely-used Hill function with coefficient n is the universal Hopfi
eld barrier to the sharpness of binding to n sites. Away from thermodynami
c equilibrium\, I will describe the challenge of path dependent complexi
ty and introduce the entropy-production index as a measure of non-equilibr
ium complexity.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/13/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Ruth Baker (University of Oxford)
DTSTART:20211125T090000Z
DTEND:20211125T100000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/14
DESCRIPTION:Title: Quantitative comparisons between models and data to p
rovide new insights in cell and developmental biology\nby Ruth Baker (
University of Oxford) as part of IBS Biomedical Mathematics Online Colloqu
ium\n\n\nAbstract\nSimple mathematical models have had remarkable successe
s in biology\, framing how we understand a host of mechanisms and processe
s. However\, with the advent of a host of new experimental technologies\,
the last ten years has seen an explosion in the amount and types of quanti
tative data now being generated. This sets a new challenge for the field
– to develop\, calibrate and analyse new models to interpret these data.
In this talk I will use examples relating to intracellular transport and
cell motility to showcase how quantitative comparisons between models and
data can help tease apart subtle details of biological mechanisms.\nRefere
nces:\n• T. P. Prescott\, K. Zhu\, M. Zhao and R. E. Baker (2021). Quant
ifying the impact of electric fields on single-cell motility. Biophys. J.
In press.\n• J. U. Harrison\, R. M. Parton\, I. Davis and R. E. Baker (2
019). Testing models of mRNA localization reveals robustness regulated by
reducing transport between cells. Biophys. J. 117(11):2154-2165.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/14/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Alexander Hoffmann (UCLA)
DTSTART:20211007T020000Z
DTEND:20211007T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/15
DESCRIPTION:Title: A temporal signaling code to specify immune responses
\nby Alexander Hoffmann (UCLA) as part of IBS Biomedical Mathematics O
nline Colloquium\n\n\nAbstract\nImmune sentinel cells must initiate the ap
propriate immune response upon sensing the presence of diverse pathogens o
r immune stimuli. To generate stimulus-specific gene expression responses\
, immune sentinel cells have evolved a temporal code in the dynamics of st
imulus responsive transcription factors. I will present recent works 1) us
ing an information theoretic approach to identify the codewords\, termed
“signaling codons”\, 2) using a machine learning approach to character
ize their reliability and points of confusion\, and 3) dynamical systems m
odeling to characterize the molecular circuits that allow for their encodi
ng. I will present progress on how the temporal code may be decoded to spe
cify immune responses. Further\, I will discuss to what extent such a cod
e may be harnessed to achieve greater pharmacological specificity when the
rapeutically targeting pleiotropic signaling hubs. \n\n\nNFκB Signaling
: information theory\, signaling codons\n\nAdelaja\, A.\, Taylor\, B.\, Sh
eu\, K.M.\, Liu\, Y.\, Luecke\, S.\, Hoffmann\, A. 2021 Six distinct NFκB
signaling codons convey discrete information to distinguish stimuli and e
nable appropriate macrophage responses. Immunity\, 54\, pp.916-930. e7. PM
ID: 33979588\n\nTang\, Y.\, Adelaja\, A.\, Ye\, X\, Deeds\, E.\, Wollman\,
R.\, Hoffmann\, A. 2021. Quantifying information accumulation encoded in
the dynamics of biochemical signaling. Nature Communications 12\, pp.1-10\
n\nDecoding signaling codons to specify immune responses\n\nSen S.\, Cheng
\, Z.\, Sheu\, K.\, Chen\, E.Y.H.\, Hoffmann\, A. 2020 Gene Regulatory Str
ategies that Decode the Duration of NFkB Dynamics Contribute to LPS- versu
s TNF-Specific Gene Expression. Cell Systems\, 10\, pp.1-14. PMID:31972132
\, PMC7047529\n\nCheng\, Q.J.\, Ohta\, S.\, Sheu\, K.M.\, Spreafico\, R.\,
Adelaja\, A.\, Taylor\, B.\, Hoffmann\, A. 2021 NFκB dynamics determine
the stimulus-specificity of epigenomic reprogramming in macrophages. Scie
nce\, 372\, pp.1349-1353\; PMID: 34140389.\n\nPharmacologic manipulation o
f the code\n\nBehar\, M.\, Barken\, D.\, Werner\, S.L.\, Hoffmann\, A. 201
3 The Dynamics of Signaling as a Pharmacological Target. Cell\, 155\, pp
.448-461. PMID: 24120141\, PMC3856316\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/15/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Alexander Anderson (Moffitt Cancer Center)
DTSTART:20210902T010000Z
DTEND:20210902T020000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/16
DESCRIPTION:Title: Exploiting evolution to design better cancer therapie
s\nby Alexander Anderson (Moffitt Cancer Center) as part of IBS Biomed
ical Mathematics Online Colloquium\n\n\nAbstract\nOur current approach to
cancer treatment has been largely driven by finding molecular targets\, th
ose patients fortunate enough to have a targetable mutation will receive a
fixed treatment schedule designed to deliver the maximum tolerated dose (
MTD). These therapies generally achieve impressive short-term responses\,
that unfortunately give way to treatment resistance and tumor relapse. The
importance of evolution during both tumor progression\, metastasis and tr
eatment response is becoming more widely accepted. However\, MTD treatmen
t strategies continue to dominate the precision oncology landscape and ign
ore the fact that treatments drive the evolution of resistance. Here we p
resent an integrated theoretical/experimental/clinical approach to develop
treatment strategies that specifically embrace cancer evolution. We will
consider the importance of using treatment response as a critical driver o
f subsequent treatment decisions\, rather than fixed strategies that ignor
e it. We will also consider using mathematical models to drive treatment d
ecisions based on limited clinical data. Through the integrated applicatio
n of mathematical and experimental models as well as clinical data we will
illustrate that\, evolutionary therapy can drive either tumor control or
extinction using a combination of drug treatments and drug holidays. Our r
esults strongly indicate that the future of precision medicine shouldn’t
be in the development of new drugs but rather in the smarter evolutionary
\, and model informed\, application of preexisting ones.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/16/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Qing Nie (University of California\, Irvine)
DTSTART:20220303T020000Z
DTEND:20220303T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/17
DESCRIPTION:Title: Spatiotemporal reconstruction of static single-cell g
enomics data\nby Qing Nie (University of California\, Irvine) as part
of IBS Biomedical Mathematics Online Colloquium\n\n\nAbstract\nCells make
fate decisions in response to dynamic environments and multicellular struc
ture emerges from interplays among cells in space and time. The recent sin
gle-cell genomics technology provides an unprecedented opportunity to prof
ile cells. However\, those measurements are taken as snapshots for groups
of individual cells with only static information. Can one infer interactio
ns among cells from such datasets? Is it possible to recover spatial infor
mation from non-spatial datasets? How to obtain temporal relationships of
cells from the static measurements? In this talk I will present our newly
developed computational tools that reconstruct interactions and spatiotemp
oral relationships for cells using single-cell RNA-seq\, ATAC-seq\, and sp
atial transcriptomics datasets. Through applications of those methods to s
ystems in development and regeneration\, we show the discovery power of su
ch methods and identify areas for further development in spatiotemporal re
construction.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/17/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Mason Porter (UCLA)
DTSTART:20220324T013000Z
DTEND:20220324T015500Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/18
DESCRIPTION:Title: Introduction to topological data analysis\nby Mas
on Porter (UCLA) as part of IBS Biomedical Mathematics Online Colloquium\n
\n\nAbstract\nI will give an introduction to topological data analysis (TD
A)\, in which one uses ideas from algebraic topology to study the "shape"
of data. I will focus on persistent homology (PH)\, which is the most comm
on approach in TDA.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/18/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Mason Porter (UCLA)
DTSTART:20220324T020000Z
DTEND:20220324T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/19
DESCRIPTION:Title: Topological data analysis of spatial systems\nby
Mason Porter (UCLA) as part of IBS Biomedical Mathematics Online Colloquiu
m\n\n\nAbstract\nFrom the venation patterns of leaves to spider webs\, roa
ds in cities\, social networks\, and the spread of COVID-19 infections and
vaccinations\, the structure of many systems is influenced significantly
by space. In this talk\, I will discuss the application of topological dat
a analysis (specifically\, persistent homology) to spatial systems. I will
present a few examples\, such as voting in presidential elections\, city
street networks\, spatiotemporal dynamics of COVID-19 infections and vacci
nations\, and webs that were spun by spiders under the influence of variou
s drugs.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/19/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Uri Alon (Weizmann Institute of Science)
DTSTART:20220331T020000Z
DTEND:20220331T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/20
DESCRIPTION:Title: Design principles of physiological circuits\nby U
ri Alon (Weizmann Institute of Science) as part of IBS Biomedical Mathemat
ics Online Colloquium\n\n\nAbstract\nWe will discuss hormone circuits and
their dynamics using new models that take into account timescales of weeks
due to growth of the hormone glands. This explains some mysteries in diab
etes and autoimmune disease.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/20/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Kunihiko Kaneko (The University of Tokyo)
DTSTART:20220407T020000Z
DTEND:20220407T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/21
DESCRIPTION:Title: Universal biology in adaptation and evolution: Dimens
ional reduction\, and fluctuation-response relationship\nby Kunihiko K
aneko (The University of Tokyo) as part of IBS Biomedical Mathematics Onli
ne Colloquium\n\n\nAbstract\nA macroscopic theory for cellular states with
steady-growth is presented\, based on consistency between cellular growth
and molecular replication\, together with robustness of phenotypes agains
t perturbations. Adaptive changes in high-dimensional phenotypes are shown
to be restricted within a low-dimensional slow manifold\, from which a ma
croscopic law for cellular states is derived\, as is confirmed by adaptati
on experiments of bacteria under stress. The theory is extended to phenoty
pic evolution\, leading to proportionality between phenotypic responses ag
ainst genetic evolution and by environmental adaptation\, which explains t
he evolutionary fluctuation-response relationship previously uncovered.
\n\nReferences\n\n1)Kaneko K.\, Life: An Introduction to Complex Systems
Biology\, Springer (2006)\n\n2)K. Kaneko\, C.Furusawa\, T. Yomo\, "Macros
copic phenomenology for cells in steady-growth state"\, Phys.Rev.X(2015) 0
11014\n\n3)C. Furusawa\, K. Kaneko "Global Relationships in Fluctuation an
d Response in Adaptive Evolution"\, J of Royal Society Interface 12(2015)\
, 20150482.\n\n4)C. Furusawa\, K. Kaneko " Formation of Dominant Mode by E
volution in Biological Systems” Phys. Rev. E 97(2018)042410\n\n5)K. Kane
ko\, C. Furusawa “Macroscopic Theory for Evolving Biological Systems Aki
n to Thermodynamics”\, Annual Rev. Biophys. (2018) 47\, 273-290\n\n6)A.
Sakata and K. Kaneko\, “Dimensional Reduction in Evolving Spin-Glass Mod
el: Correlation of Phenotypic Responses to Environmental and Mutational Ch
anges”\, Phys. Rev. Lett. (2020) 124\, 218101\n\n7)Q-Y. Tang and K. Kane
ko\, “ Dynamics-evolution correspondence in protein structures”\, Ph
ys. Rev. Lett. (2021) 127\, 098103\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/21/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Denise Kirschner (University of Michigan)
DTSTART:20220414T013000Z
DTEND:20220414T015500Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/22
DESCRIPTION:Title: An overview of methods used for multi-scale modeling
and anlysis\nby Denise Kirschner (University of Michigan) as part of I
BS Biomedical Mathematics Online Colloquium\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/22/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Denise Kirschner (University of Michigan)
DTSTART:20220414T020000Z
DTEND:20220414T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/23
DESCRIPTION:Title: A systems biology approach using multi-scale modeling
to understand the immune response to tuberculosis infection and treatment
\nby Denise Kirschner (University of Michigan) as part of IBS Biomedic
al Mathematics Online Colloquium\n\n\nAbstract\nTuberculosis (TB) is one o
f the world’s deadliest infectious diseases. Caused by the pathogen Myco
bacterium tuberculosis (Mtb)\, the standard regimen for treating TB consis
ts of treatment with multiple antibiotics for at least six months. There a
re a number of complicating factors that contribute to the need for this l
ong treatment duration and increase the risk of treatment failure. The str
ucture of granulomas\, lesions forming in lungs in response to Mtb infecti
on\, create heterogeneous antibiotic distributions that limit antibiotic e
xposure to Mtb. We can use a systems biology approach pairing experimen
tal data from non-human primates with computational modeling to represent
and predict how factors impact antibiotic regimen efficacy and granuloma b
acterial sterilization. We utilize an agent-based\, computational model th
at simulates granuloma formation\, function and treatment\, called GranSim
. A goal in improving antibiotic treatment for TB is to find regimens th
at can shorten the time it takes to sterilize granulomas while minimizing
the amount of antibiotic required. We also created a whole host model\, ca
lled HOSTSIM\, to study Mtb dynamics within a human host. Overall\, we u
se these models to help better understand TB treatment and strengthen our
ability to predict regimens that can improve clinical treatment of TB.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/23/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Kun Hu (Harvard University)
DTSTART:20220428T020000Z
DTEND:20220428T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/24
DESCRIPTION:Title: Scaling behaviors in physiological fluctuations: rele
vance to circadian regulation and insights into the development of Alzheim
er’s disease\nby Kun Hu (Harvard University) as part of IBS Biomedic
al Mathematics Online Colloquium\n\n\nAbstract\nOutputs from health biolog
ical systems display complex fluctuations that are not random but display
robust and often self-similar (fractal) temporal correlations at different
time scales— scaling behaviors. The scaling behaviors in the fluctuatio
ns of biological outputs such as neural activities\, cardiac dynamics\, mo
tor activity are believed to be originated from feedbacks within the compl
ex biological networks\, reflecting the system adaptability to internal an
d external inputs. Supporting this concept\, our studies have demonstrated
a mechanistic link between the scaling regulation of physiological fluctu
ations and the circadian control system— a result of evolutionary adapta
tion to daily environmental light-dark cycles on the earth. In this talk\,
I will discuss certain evidence for this ‘scaling-circadian’ link and
its related implications. Moreover\, I will review some recent studies\,
in which we examined how the scaling patterns of human motor activity fluc
tuations change with aging and in Alzheimer’s disease. Our results showe
d that (1) alterations in scaling activity patterns occur before the clini
cal manifestation of Alzheimer’s disease (i.e.\, cognitive impairment) a
nd predict cognitive decline and the risk for Alzheimer’s dementia\; and
(2) the progression of Alzheimer’s disease accelerates the aging effect
on the scaling activity patterns. Our work provides strong evidence that
altered scaling activity patterns may also be a risk factor for neurodegen
eration\, playing a role in the development and progression of Alzheimer
’s disease.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/24/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Krešimir Josić (University of Houston)
DTSTART:20220512T013000Z
DTEND:20220512T015500Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/25
DESCRIPTION:Title: Introduction to balanced networks\nby Krešimir J
osić (University of Houston) as part of IBS Biomedical Mathematics Online
Colloquium\n\n\nAbstract\nThe idea of balance between excitation and inhi
bition is central in the theory of biological neural networks. I will g
ive a brief introduction to the concept of such balance\, and an overview
of the mathematical ideas that can be used to study it.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/25/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Krešimir Josić (University of Houston)
DTSTART:20220512T020000Z
DTEND:20220512T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/26
DESCRIPTION:Title: Plasticity and balance in neuronal networks\nby K
rešimir Josić (University of Houston) as part of IBS Biomedical Mathemat
ics Online Colloquium\n\n\nAbstract\nI will first describe how to extend t
he theory of balanced networks to account for synaptic plasticity. This th
eory can be used to show when a plastic network will maintain balance\, an
d when it will be driven into an unbalanced state. I will next discuss how
this approach provides evidence for a novel form of rapid compensatory in
hibitory plasticity. Experimental evidence for such plasticity comes from
optogenetic activation of excitatory neurons in primate visual cortex (are
a V1) which induces a population-wide dynamic reduction in the strength of
neuronal interactions over the timescale of minutes during the awake stat
e\, but not during rest. I will shift gears in the final part of the talk\
, and discuss how community detection algorithms can help uncover the larg
e scale organization of neuronal networks from connectome data.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/26/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Radek Erban (University of Oxford)
DTSTART:20220525T073000Z
DTEND:20220525T075500Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/27
DESCRIPTION:Title: Stochastic modelling of reaction-diffusion processes<
/a>\nby Radek Erban (University of Oxford) as part of IBS Biomedical Mathe
matics Online Colloquium\n\n\nAbstract\nI will introduce mathematical and
computational methods for spatio-temporal modelling in molecular and cell
biology\, including all-atom and coarse-grained molecular dynamics (MD)\,
Brownian dynamics (BD)\, stochastic reaction-diffusion models and macrosco
pic mean-field equations. Microscopic (BD\, MD) models are based on the si
mulation of trajectories of individual molecules and their localized inter
actions (for example\, reactions). Mesoscopic (lattice-based) stochastic r
eaction-diffusion approaches divide the computational domain into a finite
number of compartments and simulate the time evolution of the numbers of
molecules in each compartment\, while macroscopic models are often written
in terms of mean-field reaction-diffusion partial differential equations
for spatially varying concentrations.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/27/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Radek Erban (University of Oxford)
DTSTART:20220525T080000Z
DTEND:20220525T090000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/28
DESCRIPTION:Title: Multi-resolution methods for modelling intracellular
processes\nby Radek Erban (University of Oxford) as part of IBS Biomed
ical Mathematics Online Colloquium\n\n\nAbstract\nI will discuss the devel
opment\, analysis and applications of multi-resolution methods for spatio-
temporal modelling of intracellular processes\, which use (detailed) Brown
ian dynamics or molecular dynamics simulations in localized regions of par
ticular interest (in which accuracy and microscopic details are important)
and a (less-detailed) coarser model in other regions in which accuracy ma
y be traded for simulation efficiency. I will discuss the error analysis a
nd convergence properties of the developed multi-resolution methods\, thei
r software implementation and applications of these multiscale methodologi
es to modelling of intracellular calcium dynamics\, actin dynamics and DNA
dynamics. I will also discuss the development of multiscale methods which
couple molecular dynamics and coarser stochastic models in the same dynam
ic simulation.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/28/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Heinz Koeppl (TU Darmstadt)
DTSTART:20220601T080000Z
DTEND:20220601T090000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/29
DESCRIPTION:Title: From live cell imaging to moment-based variational in
ference\nby Heinz Koeppl (TU Darmstadt) as part of IBS Biomedical Math
ematics Online Colloquium\n\n\nAbstract\nQuantitative characterization of
biomolecular networks is important for the analysis and design of network
functionality. Reliable models of such networks need to account for intrin
sic and extrinsic noise present in the cellular environment. Stochastic ki
netic models provide a principled framework for developing quantitatively
predictive tools in this scenario. Calibration of such models requires an
experimental setup capable of monitoring a large number of individual cell
s over time\, automatic extraction of fluorescence levels for each cell an
d a scalable inference approach. In the first part of the talk we will cov
er our microfluidic setup and a deep-learning based approach to cell segme
ntation and data extraction. The second part will introduce moment-based v
ariational inference as a scalable framework for approximate inference of
kinetic models based on single cell data.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/29/
END:VEVENT
BEGIN:VEVENT
SUMMARY:James Ferrell (Standford University)
DTSTART:20220902T020000Z
DTEND:20220902T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/30
DESCRIPTION:Title: Cell signaling in 2D vs. 3D\nby James Ferrell (St
andford University) as part of IBS Biomedical Mathematics Online Colloquiu
m\n\n\nAbstract\nThe activation of Ras depends upon the translocation of i
ts guanine nucleotide exchange factor\, Sos\, to the plasma membrane. More
over\, artificially inducing Sos to translocate to the plasma membrane is
sufficient to bring about Ras activation and activation of Ras’s targets
. There are many other examples of signaling proteins that must translocat
e to the membrane in order to relay a signal.\n\nOne attractive idea is th
at translocation promotes signaling by bringing a protein closer to its ta
rget. However\, proteins that are anchored to the membrane diffuse more sl
owly than cytosolic proteins do\, and it is not clear whether the concentr
ation effect or the diffusion effect would be expected to dominate. Here w
e have used a reconstituted\, controllable system to measure the associati
on rate for the same binding reaction in 3D vs. 2D to see whether associat
ion is promoted\, and\, if so\, how.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/30/
END:VEVENT
BEGIN:VEVENT
SUMMARY:John Tyson (Virginia Tech)
DTSTART:20221007T013000Z
DTEND:20221007T020000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/31
DESCRIPTION:Title: A Dynamic Paradigm for Molecular Cell Biology\nby
John Tyson (Virginia Tech) as part of IBS Biomedical Mathematics Online C
olloquium\n\n\nAbstract\nThe driving passion of molecular cell biologists
is to understand the molecular mechanisms that control important aspects o
f cell physiology\, but this ambition is – paradoxically – limited by
the very wealth of molecular details currently known about these mechanism
s. Their complexity overwhelms our intuitive notions of how molecular regu
latory networks might respond under normal and stressful conditions. To ma
ke progress we need a new paradigm for connecting molecular biology to cel
l physiology. I will outline an approach that uses precise mathematical me
thods to associate the qualitative features of dynamical systems\, as conv
eyed by ‘bifurcation diagrams’\, with ‘signal–response’ curves m
easured by cell biologists.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/31/
END:VEVENT
BEGIN:VEVENT
SUMMARY:John Tyson (Virginia Tech)
DTSTART:20221007T020000Z
DTEND:20221007T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/32
DESCRIPTION:Title: Time-keeping and Decision-making in the Cell Cycle\nby John Tyson (Virginia Tech) as part of IBS Biomedical Mathematics Onl
ine Colloquium\n\n\nAbstract\nCell growth\, DNA replication\, mitosis and
division are the fundamental processes by which life is passed on from one
generation of eukaryotic cells to the next. The eukaryotic cell cycle is
intrinsically a periodic process but not so much a ‘clock’ as a ‘cop
y machine’\, making new daughter cells as warranted. Cells growing under
ideal conditions divide with clock-like regularity\; however\, if they ar
e challenged with DNA-damaging agents or mitotic spindle disruptors\, they
will not progress to the next stage of the cycle until the damage is repa
ired. These ‘decisions’ (to exit and re-enter the cell cycle) are esse
ntial to maintain the integrity of the genome from generation to generatio
n. A crucial challenge for molecular cell biologists in the 1990s was to u
nravel the genetic and biochemical mechanisms of cell cycle control in euk
aryotes. Central to this effort were biochemical studies of the clock-like
regulation of ‘mitosis promoting factor’ during synchronous mitotic c
ycles of fertilized frog eggs and genetic studies of the switch-like regul
ation of ‘cyclin-dependent kinases’ in yeast cells. The complexity of
these control systems demands a dynamical approach\, as described in the f
irst lecture. Using mathematical models of the control systems\, I will un
cover some of the secrets of cell cycle ‘clocks’ and ‘switches’.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/32/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Domitilla Del Vecchio (MIT)
DTSTART:20221202T020000Z
DTEND:20221202T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/33
DESCRIPTION:Title: Mammalian synthetic biology by controller design\
nby Domitilla Del Vecchio (MIT) as part of IBS Biomedical Mathematics Onli
ne Colloquium\n\n\nAbstract\nThe ability to reliably engineer the mammalia
n cell will impact a variety of applications in a disruptive way\, includi
ng cell fate control and reprogramming\, targeted drug delivery\, and rege
nerative medicine. However\, our current ability to engineer mammalian ge
netic circuits that behave as predicted remains limited. These circuits de
pend on the intra and extra cellular environment in ways that are difficul
t to anticipate\, and this fact often hampers genetic circuit performance.
This lack of robustness to poorly known and often variable cellular envir
onment is the subject of this talk. Specifically\, I will describe control
engineering approaches that make the performance of genetic devices robus
t to context. I will show a feedforward controller that makes gene expres
sion robust to variability in cellular resources and\, more generally\, to
changes in intra-cellular context linked to differences in cell type. I w
ill then show a feedback controller that uses bacterial two component sign
aling systems to create a quasi-integral controller that makes the input/o
utput response of a genetic device robust to a variety of perturbations th
at affect gene expression. These solutions support rational and modular de
sign of sophisticated genetic circuits and can serve for engineering biolo
gical circuits that are more robust and predictable across changing contex
ts.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/33/
END:VEVENT
BEGIN:VEVENT
SUMMARY:David Anderson (University of Wisconsin-Madison)
DTSTART:20221021T020000Z
DTEND:20221021T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/34
DESCRIPTION:Title: Stationary distributions and positive recurrence of c
hemical reaction networks\nby David Anderson (University of Wisconsin-
Madison) as part of IBS Biomedical Mathematics Online Colloquium\n\n\nAbst
ract\nCellular\, chemical\, and population processes are all often represe
nted via networks that describe the interactions between the different pop
ulation types (typically called the “species”). If the counts of the s
pecies are low\, then these systems are often modeled as continuous-time M
arkov chains on the d-dimensional integer lattice (with d being the number
of species)\, with transition rates determined by stochastic mass-action
kinetics. A natural (broad) mathematical question is: how do the qualitati
ve properties of the dynamical system relate to the graph properties of th
e network? For example\, it is of particular interest to know which graph
properties imply that the stochastically modeled reaction network is posit
ive recurrent\, and therefore admits a stationary distribution. After a ge
neral introduction to the models of interest\, I will discuss this problem
\, giving some of the known results. I will also discuss recent progress o
n the Chemical Recurrence Conjecture\, which has been open for decades\, w
hich is the following: if each connected component of the network is stron
gly connected\, then the associated stochastic model is positive recurrent
.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/34/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Anne Skeldon (University of Surrey)
DTSTART:20221026T070000Z
DTEND:20221026T080000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/35
DESCRIPTION:Title: Mathematical Modelling of the sleep-wake cycle: light
\, clocks and social rhythms\nby Anne Skeldon (University of Surrey) a
s part of IBS Biomedical Mathematics Online Colloquium\n\n\nAbstract\nWe
’re all familiar with sleep\, but how can we mathematically model it? An
d what determines how long and when we sleep? In this talk I’ll introduc
e the nonsmooth coupled oscillator systems that form the basis of current
models of sleep-wake regulation and discuss their dynamical behaviour. I w
ill describe how we are using models to unravel environmental\, societal a
nd physiological factors that determine sleep timing and outline how we ar
e using models to inform the quantitative design of light interventions fo
r mental health disorders and address contentious societal questions such
as whether to move school start time for adolescents.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/35/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Marko Okada (Osaka University)
DTSTART:20221109T070000Z
DTEND:20221109T080000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/36
DESCRIPTION:Title: Modeling cell-to-cell heterogeneity from a signaling
network\nby Marko Okada (Osaka University) as part of IBS Biomedical M
athematics Online Colloquium\n\n\nAbstract\nCells make individual fate dec
isions through linear and nonlinear regulation of gene network\, generatin
g diverse dynamics from a single reaction pathway. In this colloquium\, I
will present two topics of our recent work on signaling dynamics at cellul
ar and patient levels. The first example is about the initial value of the
model\, as a mechanism to generate different dynamics from a single pathw
ay in cancer and the use of the dynamics for stratification of the patient
s [1-3]. Models of ErbB receptor signaling have been widely used in predic
tion of drug sensitivity for many types of cancers. We trained the ErbB mo
del with the data obtained from cancer cell lines and predicted the common
parameters of the model. By simulation of the ErbB model with those param
eters and individual patient transcriptome data as initial values\, we wer
e able to classify the prognosis of breast cancer patients and drug sensit
ivity based on their in silico signaling dynamics. This result raises the
question whether gene expression levels\, rather than genetic mutations\,
might be better suited to classify the disease. Another example is about t
he regulation of transcription factors\, the recipients of signal dynamics
\, for target gene expression [4-6]. By focusing on the NFkB transcription
factor\, we found that the opening and closing of chromatin at the DNA re
gions of the putative transcription factor binding sites and the cooperati
vity in their interaction significantly influenced the cell-to cell hetero
geneity in gene expression levels. This study indicates that the noise in
gene expression is rather strongly regulated by the DNA side\, even though
the signals are similarly regulated in a cell population. Overall these m
echanisms are important in our understanding the cell as a system for enco
ding and decoding signals for fate decisions and its application to human
diseases.\n\n[References]\n\n[1] Nakakuki et al. Cell 2010\,\n[2] Imoto et
al. iScience 2022\,\n[3] Imoto et al. STAR Protocols 2022\,\n[4] Shinohar
a et al. Science 2014\,\n[5] Michida et al. Cell Reports 2020\,\n[6] Wibis
ana et al. PLoS Genetics 2022\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/36/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Rosemary Braun (Northwestern University)
DTSTART:20221118T020000Z
DTEND:20221118T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/37
DESCRIPTION:Title: Quantifying dynamical changes in sparse\, noisy\, hig
h-dimensional data\nby Rosemary Braun (Northwestern University) as par
t of IBS Biomedical Mathematics Online Colloquium\n\n\nAbstract\nThe circa
dian clock orchestrates a vast array of behavioral and physiological proce
sses with a 24-hour cycle\, enabling nearly all organisms -- from bread mo
ld to fruit-flies to humans -- to anticipate and adapt to the Earth's day.
Entrainable by environmental cue\, the rhythm itself is generated by a s
elf-sustained molecular oscillator present in nearly every cell. This in
turn governs the expression of thousands of genes\, precisely coordinating
biomolecular functions at the microscopic scale. While experimental evid
ence suggests that the clock is crucial for mediating the response to chan
ges in an organism's environment (such as temperature and food availabilit
y)\, the precise mechanisms underlying circadian regulation remain unclear
. Today\, high-throughput omics assays enable us to probe these processes
in molecular detail\, with the goal of making inferences about which gene
s are under circadian control and how their dynamics change under differen
t environmental conditions. Analyzing this transcriptomic time-series dat
a raises new challenges: that of characterizing dynamics when the data are
noisy\, sparsely sampled in time\, and may not be strictly periodic. In
this talk\, I will discuss our recent work on nonparametric methods to ana
lyze circadian transcriptomic data by exploiting results from dynamical sy
stems theory\, nonlinear dimension reduction\, and topological data analys
is.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/37/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Edda Klipp (Humboldt University of Berlin)
DTSTART:20221123T070000Z
DTEND:20221123T080000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/38
DESCRIPTION:Title: Assessing the limits of control of Covid-19 outbreaks
using agent-based modeling\nby Edda Klipp (Humboldt University of Ber
lin) as part of IBS Biomedical Mathematics Online Colloquium\n\n\nAbstract
\nTransmission of SARS-CoV-2 relies on interactions between humans. Hetero
geneity and stochasticity both in human-human interactions and in the tran
smission of the virus give rise to non-linear infection networks that gain
complexity with time.\nWe assessed the limits of control and the effect o
f pharmaceutical and non-pharmaceutical measures against COVID‐19 outbre
aks with a detailed community‐specific agent-based model (GERDA). The de
mographic and geographic structure of the concrete communities influence t
he pattern of infection spreading. Stochastic community dynamics and limit
ed vaccination can lead to bimodal outcomes\, rendering predictions about
infection spreading and effects of nonpharmaceutical interventions uncerta
in.\n\nBy comparing different vaccination strategies\, we found that the h
erd immunity threshold depends strongly on the applied vaccination strateg
y. When vaccine supply is limited\, different vaccination strategies are
optimal for the intended goal e.g.\, reducing fatalities or confining an o
utbreak. Prioritizing highly interactive people diminishes the risk for an
infection wave\, while prioritizing the elderly minimizes fatalities.\nTh
e inherent stochasticity can lead to bimodality in predicting an outbreak
in different low-incidence scenarios and\, thereby\, render the effect of
limited NPI uncertain. Further\, we found that for the low-incidence scen
arios the reproduction number R0 is not a suitable predictor for the syste
m behavior or the infectiousness of the virus.\nThe developed simulation p
latform can process and analyze dynamic COVID‐19 epidemiological situati
ons in diverse communities worldwide to predict pathways to population imm
unity even with limited vaccination.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/38/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Svetlana Postnava (University of Sydney)
DTSTART:20221130T070000Z
DTEND:20221130T080000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/39
DESCRIPTION:Title: Brain dynamics during shiftwork: from maths and codes
to real-world applications\nby Svetlana Postnava (University of Sydne
y) as part of IBS Biomedical Mathematics Online Colloquium\n\nAbstract: TB
A\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/39/
END:VEVENT
BEGIN:VEVENT
SUMMARY:George Sugihara (Scripps Institution for Oceanography)
DTSTART:20221209T020000Z
DTEND:20221209T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/40
DESCRIPTION:Title: Taming Complexity in Data-Limited Nonlinear Nonequili
brium Settings\nby George Sugihara (Scripps Institution for Oceanograp
hy) as part of IBS Biomedical Mathematics Online Colloquium\n\n\nAbstract\
nSince before the time of Aristotle and the natural philosophers\, reducti
onism has played a foundational role in western scientific thought. The pr
emise of reductionism is that systems can be broken down into constituent
pieces and studied independently\, then reassembled to understand the beha
vior of the system as a whole. It embodies the classical linear perspectiv
e. This approach has been successful in developing basic physical laws and
especially in engineering where linear analysis dominates and systems are
purposefully designed that way. However\, reductionism is not universally
applicable for natural complex systems where behavior is driven\, not by
a few factors acting independently\, but by complex interactions between m
any components acting together and changing in time.\n\nNonlinearity in li
ving systems means that its parts are interdependent – variables do not
act in a mutually independent manner\; rather they interact\, and as a con
sequence associations (correlations) between them will change as the overa
ll system context (state) changes. This problem is highlighted when extr
apolating the results of single-factor experiments to nature\, and surely
contributes to the frustrating disconnect between experimental findings an
d clinical outcomes in drug trials. Indeed\, while everyone knows Berkeley
’s 1710 dictum “correlation does not imply causation” few realize th
at for nonlinear systems the converse “causation does not imply correlat
ion” is also true. This conundrum runs counter to deeply ingrained heuri
stic thinking that is at the basis of modern science. Biological systems (
esp. ecosystems) are particularly perverse on this issue by exhibiting mir
age correlations that can continually cause us to rethink relationships we
thought we understood.\n\nHere we examine a minimalist paradigm\, empiric
al dynamics (EDM)\, for studying non-linear systems and a method (CCM) tha
t can detect causality when there is no correlation among variables. It is
a data-driven approach that uses time series to study a system holistical
ly by reconstructing its attractor – a geometric object that embodies th
e rules of a full set of equations for the system. The ideas are intuiti
ve and will be illustrated with examples from genetics\, ecology and epide
miology.\n\nA python version of EDM tools can be found at https://pepy.tec
h/project/pyEDM\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/40/
END:VEVENT
BEGIN:VEVENT
SUMMARY:David Anderson (University of Wisconsin Madison)
DTSTART:20221021T013000Z
DTEND:20221021T020000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/41
DESCRIPTION:Title: A brief introduction to stochastic reaction networks<
/a>\nby David Anderson (University of Wisconsin Madison) as part of IBS Bi
omedical Mathematics Online Colloquium\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/41/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Shinya Kuroda (Tokyo University)
DTSTART:20230303T020000Z
DTEND:20230303T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/42
DESCRIPTION:Title: Systems biology of insulin action\nby Shinya Kuro
da (Tokyo University) as part of IBS Biomedical Mathematics Online Colloqu
ium\n\n\nAbstract\n1. The “temporal information code” of insulin actio
n: a bottom-up approach One of the essential elements of signaling network
s is to encode information from a wide variety of inputs into a limited se
t of molecules. We have proposed a “temporal information code” that re
gulates a variety of physiological functions by encoding input information
in temporal patterns of molecular activity\, and based on this concept\,
we are analyzing biological homeostasis by insulin signaling. Taking blood
insulin as an example\, we will explain how the temporal information of b
lood insulin is selectively decoded by downstream networks.\n\n2. Transomi
cs of insulin action: a top-down approach In order to obtain a complete pi
cture of insulin action\, we performed transomics measurements integrating
metabolomics and transcriptomics\, and found that metabolism is regulated
by allosteric regulation in the liver of normal mice and by compensatory
gene expression in the liver of obese mice. (Top-down approach). I will ta
lk about approach the principle of homeostasis of living organisms by temp
oral patterns\, using the analysis of systems biology of insulin action us
ing two different approaches.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/42/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Martin Nowak (Harvard University)
DTSTART:20230310T010000Z
DTEND:20230310T020000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/43
DESCRIPTION:Title: Evolution of cooperation\nby Martin Nowak (Harvar
d University) as part of IBS Biomedical Mathematics Online Colloquium\n\nA
bstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/43/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Saez-Rodriguez\, Julio (Heidelberg University)
DTSTART:20230315T070000Z
DTEND:20230315T080000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/44
DESCRIPTION:Title: Dynamic logic models complement machine learning for
personalized medicine\nby Saez-Rodriguez\, Julio (Heidelberg Universit
y) as part of IBS Biomedical Mathematics Online Colloquium\n\nAbstract: TB
A\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/44/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Stefan Bauer (Helmholtz and TU Munich)
DTSTART:20230324T070000Z
DTEND:20230324T080000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/45
DESCRIPTION:Title: Neural causal models for experimental design\nby
Stefan Bauer (Helmholtz and TU Munich) as part of IBS Biomedical Mathemati
cs Online Colloquium\n\n\nAbstract\nMany questions in everyday life as wel
l as in research are causal in nature: How would the climate change if we
lower train prices or will my headache go away if I take an aspirin? Inher
ently\, such questions need to specify the causal variables relevant to th
e question and their interactions. However\, existing algorithms for learn
ing causal graphs from data are often not scaling well both with the numbe
r of variables or the number of observations. This talk will provide a bri
ef introduction to causal structure learning\, recent efforts in using con
tinuous optimization to learn causal graphs at scale and systematic approa
ches for causal experimental design at scale.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/45/
END:VEVENT
BEGIN:VEVENT
SUMMARY:George Karniadakis (Brown University)
DTSTART:20230407T020000Z
DTEND:20230407T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/46
DESCRIPTION:Title: BINNS: Biophysics-Informed Neural Networks\nby Ge
orge Karniadakis (Brown University) as part of IBS Biomedical Mathematics
Online Colloquium\n\n\nAbstract\nWe will present a new approach to develop
a data-driven\, learning-based framework for predicting outcomes of bioph
ysical systems and for discovering hidden mechanisms and pathways from noi
sy data. We will introduce a deep learning approach based on neural networ
ks (NNs) and on generative adversarial networks (GANs). Unlike other appro
aches that rely on big data\, here we “learn” from small data by explo
iting the information provided by the mathematical physics\, e.g..\, conse
rvation laws\, reaction kinetics\, etc\,. which are used to obtain informa
tive priors or regularize the neural networks. We will demonstrate how we
can train BINNs from multifidelity/multimodality data\, and we will presen
t several examples of inverse problems\, e.g.\, in systems biology for dia
betes and in biomechanics for non-invasive inference of thrombus material
properties. We will also discuss how operator regression in the form of De
epOnet can be used to accelerate inference based on historical data and on
ly a few new data\, as well its generalization and transfer learning capac
ity.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/46/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Hans P.A. Van Dongen (Washington State Univeristy)
DTSTART:20230428T020000Z
DTEND:20230428T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/47
DESCRIPTION:Title: Modeling the temporal dynamics of neurobehavioral per
formance impairment due to sleep loss and circadian misalignment\nby H
ans P.A. Van Dongen (Washington State Univeristy) as part of IBS Biomedica
l Mathematics Online Colloquium\n\n\nAbstract\nAbstract: The well-known tw
o-process model of sleep regulation makes accurate predictions of sleep ti
ming and duration\, as well as neurobehavioral performance\, for a variety
of acute sleep deprivation and nap sleep scenarios\, but it fails to pred
ict the effects of chronic sleep restriction on neurobehavioral performanc
e. The two-process model belongs to a broader class of coupled\, non-homog
eneous\, first-order\, ordinary differential equations (ODEs)\, which can
capture the effects of chronic sleep restriction. These equations exhibit
a bifurcation\, which appears to be an essential feature of performance im
pairment due to sleep loss. The equations implicate a biological system an
alogous to two connected compartments containing interacting compounds wit
h time-varying concentrations\, such as the adenosinergic neuromodulator/r
eceptor system\, as a key mechanism for the regulation of neurobehavioral
functioning under conditions of sleep loss. The equations account for dyna
mic interaction with circadian rhythmicity\, and also provide a new approa
ch to dynamically tracking the magnitude of sleep inertia upon awakening f
rom restricted sleep. This presentation will describe the development of t
he ODE system and its experimental calibration and validation\, and will d
iscuss some novel predictions.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/47/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Morgen Jensen (Niels Bohr Institute)
DTSTART:20230510T070000Z
DTEND:20230510T080000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/48
DESCRIPTION:Title: DNA repair and chaos in CellsBD\nby Morgen Jensen
(Niels Bohr Institute) as part of IBS Biomedical Mathematics Online Collo
quium\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/48/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Thomas Philipp (Imperial College London)
DTSTART:20230524T070000Z
DTEND:20230524T080000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/49
DESCRIPTION:Title: Stochastic gene expression in lineage trees\nby T
homas Philipp (Imperial College London) as part of IBS Biomedical Mathemat
ics Online Colloquium\n\n\nAbstract\nStochasticity in gene expression is a
n important source of cell-to-cell variability (or noise) in clonal cell p
opulations. So far\, this phenomenon has been studied using the Gillespie
Algorithm\, or the Chemical Master Equation\, which implicitly assumes tha
t cells are independent and do neither grow nor divide. This talk will dis
cuss recent developments in modelling populations of growing and dividing
cells through agent-based approaches. I will show how the lineage structur
e affects gene expression noise over time\, which leads to a straightforwa
rd interpretation of cell-to-cell variability in population snapshots. I w
ill also illustrate how cell cycle variability shapes extrinsic noise acro
ss lineage trees. Finally\, I outline how to construct effective chemical
master equation models based on dilution reactions and extrinsic variabili
ty that provide surprisingly accurate approximations of the noise statisti
cs across growing populations. The results highlight that it is crucial to
consider cell growth and division when quantifying cellular noise.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/49/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Sushmita Roy (University of Wisconsin-Madison)
DTSTART:20230609T020000Z
DTEND:20230609T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/50
DESCRIPTION:Title: Deciphering gene regulatory networks underlying cell-
fate specification\nby Sushmita Roy (University of Wisconsin-Madison)
as part of IBS Biomedical Mathematics Online Colloquium\n\n\nAbstract\nCel
l fate specification is a dynamic process during which gene regulatory net
works (GRNs) transition between different states and define cell type-spec
ific patterns of gene expression. Identifying such cell type-specific gene
regulatory networks is important for understanding how cells differentiat
e to diverse lineages from a progenitor state\, how differentiated cells c
an be reprogrammed\, and how these networks get disrupted in diseases such
as cancer and developmental disorders. The advent of single cell omics ha
s enabled us to perform high-throughput molecular phenotyping of individua
l cells at different omic levels. These technologies have revolutionized o
ur understanding of cell type composition across diverse normal and diseas
e conditions\; however inferring cell type-specific networks and their dyn
amics from single cell omic datasets is an open challenge. I will present
some of our recent efforts for inference and analysis of cell type-specifi
c regulatory networks from single cell omic datasets. Application of our a
pproach to hematopoietic differentiation and mouse cellular reprogramming
predicted key regulatory nodes likely important for establishing different
cell-type specific expression programs.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/50/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Sebastian Walcher (Mathematik A\, RWTH Aachen\, Germany)
DTSTART:20230920T070000Z
DTEND:20230920T080000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/51
DESCRIPTION:Title: Reaction networks: Reduction of dimension and critica
l parameters\nby Sebastian Walcher (Mathematik A\, RWTH Aachen\, Germa
ny) as part of IBS Biomedical Mathematics Online Colloquium\n\n\nAbstract\
nTypically\, the mathematical description of reaction networks involves a
system of parameter-dependent ordinary differential equations. Generally\,
one is interested in the qualitative and quantitative behavior of solutio
ns in various parameter regions. In applications\, identifying the reactio
n parameters is a fundamental task. Reduction of dimension is desirable fr
om a practical perspective\, and even necessary when different timescales
are present. For biochemical reaction networks\, a classical reduction tec
hnique assumes quasi-steady state (QSS) of certain species. From a general
mathematical perspective\, singular perturbation theory – involving a s
mall parameter – is often invoked. The talk is mathematically oriented.
The following points will be discussed: Singular perturbation reduction in
general coordinates. (“How does one compute reductions?”) Critical pa
rameters for singular perturbations. (“How does one find small parameter
s?”) Quasi-steady state and singular perturbations. (“What is applicab
le\, what is correct?”)\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/51/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Tetsuya J. Kobayashi (Institute of Industrial Science\, the Univer
sity of Tokyo)
DTSTART:20231020T020000Z
DTEND:20231020T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/52
DESCRIPTION:Title: Optimality of Biological Information Processing\n
by Tetsuya J. Kobayashi (Institute of Industrial Science\, the University
of Tokyo) as part of IBS Biomedical Mathematics Online Colloquium\n\n\nAbs
tract\nTBD\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/52/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Eder Zavala (Centre for Systems Modelling & Quantitative Biomedici
ne\, University of Birmingham)
DTSTART:20231101T070000Z
DTEND:20231101T080000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/53
DESCRIPTION:Title: Quantitative analysis of high-resolution daily profil
es of HPA axis hormones\nby Eder Zavala (Centre for Systems Modelling
& Quantitative Biomedicine\, University of Birmingham) as part of IBS Biom
edical Mathematics Online Colloquium\n\n\nAbstract\nThe Hypothalamic-Pitui
tary-Adrenal (HPA) axis is the key regulatory pathway responsible for main
taining homeostasis under conditions of real or perceived stress. Endocrin
e responses to stressors are mediated by adrenocorticotrophic hormone (ACT
H) and corticosteroid (CORT) hormones. In healthy\, non-stressed condition
s\, ACTH and CORT exhibit highly correlated ultradian pulsatility with an
amplitude modulated by circadian processes. Disruption of these hormonal r
hythms can occur as a result of stressors or in the very early stages of d
isease. Despite the fact that misaligned endocrine rhythms are associated
with increased morbidity\, a quantitative understanding of their mechanist
ic origin and pathogenicity is missing. Mathematically\, the HPA axis can
be understood as a dynamical system that is optimised to respond and adapt
to perturbations. Normally\, the body copes well with minor disruptions\,
but finds it difficult to withstand severe\, repeated or long-lasting per
turbations. Whilst a healthy HPA axis maintains a certain degree of robust
ness to stressors\, its fragility in diseased states is largely unknown\,
and this understanding constitutes a critical step toward the development
of digital tools to support clinical decision-making. This talk will explo
re how these challenges are being addressed by combining high-resolution b
iosampling techniques with mathematical and computational analysis methods
. This interdisciplinary approach is helping us quantify the inter-individ
ual variability of daily hormone profiles and develop novel “dynamic bio
markers” that serve as a normative reference and to signal endocrine dys
function. By shifting from a qualitative to a quantitative description of
the HPA axis\, these insights bring us a step closer to personalised clini
cal interventions for which timing is key.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/53/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Matthew Simpson (Queensland University of Technology\, Australia)
DTSTART:20231110T020000Z
DTEND:20231110T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/54
DESCRIPTION:Title: Efficient prediction\, estimation and identifiability
analysis with mechanistic mathematical models\nby Matthew Simpson (Qu
eensland University of Technology\, Australia) as part of IBS Biomedical M
athematics Online Colloquium\n\n\nAbstract\nInterpreting data using mechan
istic mathematical models provides a foundation for discovery and decision
-making in all areas of science and engineering. Key steps in using mechan
istic mathematical models to interpret data include: (i) identifiability a
nalysis\; (ii) parameter estimation\; and (iii) model prediction. Here we
present a systematic\, computationally efficient likelihood-based workflow
that addresses all three steps in a unified way. Recently developed metho
ds for constructing profile-wise prediction intervals enable this workflow
and provide the central linkage between different workflow components. Th
ese methods propagate profile-likelihood-based confidence sets for model p
arameters to predictions in a way that isolates how different parameter co
mbinations affect model predictions. We show how to extend these profile-w
ise prediction intervals to two-dimensional interest parameters\, and then
combine profile-wise prediction confidence sets to give an overall predic
tion confidence set that approximates the full likelihood-based prediction
confidence set well. We apply our methods to a range of synthetic data an
d real-world ecological data describing re-growth of coral reefs on the Gr
eat Barrier Reef after some external disturbance\, such as a tropical cycl
one or coral bleaching event.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/54/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Samuel Isaacson (Boston University)
DTSTART:20231117T020000Z
DTEND:20231117T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/55
DESCRIPTION:Title: Spatial Particle Modeling of Immune Processes\nby
Samuel Isaacson (Boston University) as part of IBS Biomedical Mathematics
Online Colloquium\n\n\nAbstract\nTBD\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/55/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Alfio Quarteroni (Politecnico di Milano)
DTSTART:20231122T070000Z
DTEND:20231122T080000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/56
DESCRIPTION:Title: Physics-based and data-driven numerical models for co
mputational medicine\nby Alfio Quarteroni (Politecnico di Milano) as p
art of IBS Biomedical Mathematics Online Colloquium\n\n\nAbstract\nI will
report on some recent results on modelling the heart\, the external circul
ation\, and their application to problems of clinical relevance. I will sh
ow that a proper integration between PDE-based and machine-learning algori
thms can improve the computational efficiency and enhance the generality o
f our iHEART simulator.\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/56/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Robyn P. Araujo (Australian Research Council Future Fellow\, Queen
sland University of Technology)
DTSTART:20231208T020000Z
DTEND:20231208T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/57
DESCRIPTION:Title: Cellular cognition and the simple complexity of the n
etworks of life\nby Robyn P. Araujo (Australian Research Council Futur
e Fellow\, Queensland University of Technology) as part of IBS Biomedical
Mathematics Online Colloquium\n\n\nAbstract\nTBD\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/57/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Aiden Doherty (Big Data Institute\, University of Oxford)
DTSTART:20251015T070000Z
DTEND:20251015T080000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/58
DESCRIPTION:Title: Developing time-series machine learning methods to un
lock new insights from large-scale biomedical resources\nby Aiden Dohe
rty (Big Data Institute\, University of Oxford) as part of IBS Biomedical
Mathematics Online Colloquium\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/58/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Luonan Chen (Shanghai Institutes for Biological Sciences)
DTSTART:20251029T070000Z
DTEND:20251029T080000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/59
DESCRIPTION:Title: Dynamical data science and AI for Biology and Medicin
e\nby Luonan Chen (Shanghai Institutes for Biological Sciences) as par
t of IBS Biomedical Mathematics Online Colloquium\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/59/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Amir Sharafkhaneh (Department of Medicine\, Baylor College of Medi
cine)
DTSTART:20251112T070000Z
DTEND:20251112T080000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/60
DESCRIPTION:Title: [Cancelled]\nby Amir Sharafkhaneh (Department of
Medicine\, Baylor College of Medicine) as part of IBS Biomedical Mathemati
cs Online Colloquium\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/60/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Stephan Munch (Department of Applied Mathematics\, UC Santa Cruz)
DTSTART:20251205T020000Z
DTEND:20251205T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/61
DESCRIPTION:Title: Empirical modeling of bifurcations and chaos from tim
e series\nby Stephan Munch (Department of Applied Mathematics\, UC San
ta Cruz) as part of IBS Biomedical Mathematics Online Colloquium\n\nAbstra
ct: TBA\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/61/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Chen Jia
DTSTART:20260325T070000Z
DTEND:20260325T080000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/62
DESCRIPTION:Title: Stochastic theory of complex biochemical reaction net
works\nby Chen Jia as part of IBS Biomedical Mathematics Online Colloq
uium\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/62/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Sean Lawley
DTSTART:20260403T020000Z
DTEND:20260403T030000Z
DTSTAMP:20260404T100028Z
UID:IBS_BIMAG_Colloquium/63
DESCRIPTION:Title: Stochastics in medicine: Delaying menopause and missi
ng drug doses\nby Sean Lawley as part of IBS Biomedical Mathematics On
line Colloquium\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/IBS_BIMAG_Colloquium/63/
END:VEVENT
END:VCALENDAR