BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Biomedical Mathematics Group - ECPv6.15.18//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://www.ibs.re.kr/bimag
X-WR-CALDESC:Events for Biomedical Mathematics Group
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Asia/Seoul
BEGIN:STANDARD
TZOFFSETFROM:+0900
TZOFFSETTO:+0900
TZNAME:KST
DTSTART:20210101T000000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20240412T110000
DTEND;TZID=Asia/Seoul:20240412T120000
DTSTAMP:20260405T231246
CREATED:20240219T043247Z
LAST-MODIFIED:20240728T142452Z
UID:9233-1712919600-1712923200@www.ibs.re.kr
SUMMARY:Michael Chee\, How Data from Sleep Trackers Can Transform Our Understanding of Sleep
DESCRIPTION:Abstract: Wearable health trackers have shifted from gadgets for sports enthusiasts to valuable health sentinels over the last few years and that transformation is gathering pace. What do these devices really measure about sleep? What types of devices are there\, and which can we trust? Which of the many sleep measures reported\, contribute to a better understanding of sleep\, sleep habits and sleep health? How can sleep data improve personal and public health? What new uses of sensor data can we look forward to in coming years? I seek to shed light on these issues in a presentation that will focus on distinguishing scientific and health-oriented perspectives from consumer-facing ones.
URL:https://www.ibs.re.kr/bimag/event/michael-chee-how-data-from-sleep-trackers-can-transform-our-understanding-of-sleep-2/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2024/02/Michael-Chee-e1722176681984.jpeg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20240405T110000
DTEND;TZID=Asia/Seoul:20240405T120000
DTSTAMP:20260405T231246
CREATED:20240219T043532Z
LAST-MODIFIED:20240728T142635Z
UID:9236-1712314800-1712318400@www.ibs.re.kr
SUMMARY:Brian P. Delisle\, Circadian Regulation of Cardiac Electrophysiology
DESCRIPTION:Abstract: Circadian rhythms in physiology and behavior are regulated by circadian clocks\, ubiquitous molecular transcriptional-translational feedback loops that cycle with a periodicity of ~24 hours. Circadian clocks serve as cellular timekeepers regulating important cell-type specific functions. The phase of circadian rhythms and circadian clocks throughout the body are entrained to the light cycle by signals originating in the suprachiasmatic nucleus of the hypothalamus. The functional importance of circadian clocks in cardiomyocytes is underscored by the observation that genetic disruption of the circadian clock mechanism in mouse hearts alters the electrocardiogram (ECG)\, cardiac action potential\, and size of individual ionic currents. This presentation discusses recent basic science studies showing how daily environmental\, behavioral\, and circadian rhythms impact cardiac electrophysiology and cardiac arrhythmogenesis at the systems\, tissue\, and molecular levels. These studies provide new insights into how daily environmental\, behavioral\, and circadian rhythms affect the timing of cardiovascular events\, and they are starting to identify chronotherapeutic strategies that may mitigate the risk for cardiac arrhythmias.
URL:https://www.ibs.re.kr/bimag/event/brian-p-delisle-circadian-regulation-of-cardiac-electrophysiology/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2024/02/Brian-Delisle-e1722176786315.jpeg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20240308T110000
DTEND;TZID=Asia/Seoul:20240308T120000
DTSTAMP:20260405T231246
CREATED:20240219T042938Z
LAST-MODIFIED:20240728T142756Z
UID:9230-1709895600-1709899200@www.ibs.re.kr
SUMMARY:Mark Alber\, Combined multiscale mathematical modeling and experimental study of regulation mechanisms of shape formation during tissue development
DESCRIPTION:Abstract: The regulation and maintenance of an organ’s shape and structure is a major outstanding question in developmental biology. The Drosophila wing imaginal disc serves as a powerful system for elucidating design principles of the shape formation in epithelial morphogenesis.
URL:https://www.ibs.re.kr/bimag/event/mark-alber-combined-multiscale-mathematical-modeling-and-experimental-study-of-regulation-mechanisms-of-shape-formation-during-tissue-development/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2024/02/Mark-Alber-e1722176863895.jpeg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20231208T110000
DTEND;TZID=Asia/Seoul:20231208T120000
DTSTAMP:20260405T231246
CREATED:20230831T142407Z
LAST-MODIFIED:20240728T143005Z
UID:8394-1702033200-1702036800@www.ibs.re.kr
SUMMARY:Robyn P. Araujo\, Cellular cognition and the simple complexity of the networks of life
DESCRIPTION:Abstract: TBD
URL:https://www.ibs.re.kr/bimag/event/robyn-p-araujo-cellular-cognition-and-the-simple-complexity-of-the-networks-of-life/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2023/08/Robyn-Araujo-e1722176950408.jpeg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20231122T160000
DTEND;TZID=Asia/Seoul:20231122T170000
DTSTAMP:20260405T231246
CREATED:20230831T143538Z
LAST-MODIFIED:20240728T143214Z
UID:8405-1700668800-1700672400@www.ibs.re.kr
SUMMARY:Alfio Quarteroni\, Physics-based and data-driven numerical models for computational medicine
DESCRIPTION:Abstract: I will report on some recent results on modelling the heart\, the external circulation\, and their application to problems of clinical relevance. I will show that a proper integration between PDE-based and machine-learning algorithms can improve the computational efficiency and enhance the generality of our iHEART simulator.
URL:https://www.ibs.re.kr/bimag/event/alfio-quarteroni-physics-based-and-data-driven-numerical-models-for-computational-medicine/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2023/08/Alfio-Quarteroni-e1722177125537.jpeg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20231117T110000
DTEND;TZID=Asia/Seoul:20231117T120000
DTSTAMP:20260405T231246
CREATED:20230831T143713Z
LAST-MODIFIED:20240728T143844Z
UID:8408-1700218800-1700222400@www.ibs.re.kr
SUMMARY:Samuel Isaacson\, Spatial Particle Modeling of Immune Processes
DESCRIPTION:Abstract: \nSurface Plasmon Resonance (SPR) assays are a standard approach for quantifying kinetic parameters in antibody-antigen binding reactions. Classical SPR approaches ignore the bivalent structure of antibodies\, and use simplified ODE models to estimate effective reaction rates for such interactions. In this work we develop a new SPR protocol\, coupling a model that explicitly accounts for the bivalent nature of such interactions and the limited spatial distance over which such interactions can occur\, to a SPR assay that provides more features in the generated data. Our approach allows the estimation of bivalent binding kinetics and the spatial extent over which antibodies and antigens can interact\, while also providing substantially more robust fits to experimental data compared to classical ODE models. I will present our new modeling and parameter estimation approach\, and demonstrate how it is being used to study interactions between antibodies and spike protein. I will also explain how we make the overall parameter estimation problem computationally feasible via the construction of a surrogate approximation to the (computationally-expensive) particle model. The latter enables fitting of model parameters via standard optimization approaches. \nTime-permitting\, I will also give an introduction to our Catalyst.jl symbolic chemical reaction modeling library\, which we have recently demonstrated outperforms a number of popular systems biology simulation packages in solving ODE and stochastic reaction models. A distinguishing feature of Catalyst is the ease with which it integrates with other Julia libraries to enable sensitivity analysis\, parameter estimation studies\, structural identifiability analysis\, bifurcation analysis\, solution of the chemical master equation\, and a variety of higher-level functionality.
URL:https://www.ibs.re.kr/bimag/event/samuel-isaacson-spatial-particle-modeling-of-immune-processes/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2023/08/Samuel-Isaacson-scaled-e1722177501809.jpeg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20231110T110000
DTEND;TZID=Asia/Seoul:20231110T120000
DTSTAMP:20260405T231246
CREATED:20230831T142922Z
LAST-MODIFIED:20240728T144105Z
UID:8399-1699614000-1699617600@www.ibs.re.kr
SUMMARY:Matthew Simpson\, Efficient prediction\, estimation and identifiability analysis with mechanistic mathematical models
DESCRIPTION:Abstract: Interpreting data using mechanistic mathematical models provides a foundation for discovery and decision-making in all areas of science and engineering. Key steps in using mechanistic mathematical models to interpret data include: (i) identifiability analysis; (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 methods for constructing profile-wise prediction intervals enable this workflow and provide the central linkage between different workflow components. These methods propagate profile-likelihood-based confidence sets for model parameters to predictions in a way that isolates how different parameter combinations affect model predictions. We show how to extend these profile-wise prediction intervals to two-dimensional interest parameters\, and then combine profile-wise prediction confidence sets to give an overall prediction confidence set that approximates the full likelihood-based prediction confidence set well. We apply our methods to a range of synthetic data and real-world ecological data describing re-growth of coral reefs on the Great Barrier Reef after some external disturbance\, such as a tropical cyclone or coral bleaching event.
URL:https://www.ibs.re.kr/bimag/event/matthew-simpson-efficient-prediction-estimation-and-identifiability-analysis-with-mechanistic-mathematical-models/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2023/08/Matthew-Simpson-e1722177652995.jpeg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20231101T160000
DTEND;TZID=Asia/Seoul:20231101T170000
DTSTAMP:20260405T231246
CREATED:20230831T143129Z
LAST-MODIFIED:20240728T144218Z
UID:8402-1698854400-1698858000@www.ibs.re.kr
SUMMARY:Eder Zavala\, Quantitative analysis of high-resolution daily profiles of HPA axis hormones
DESCRIPTION:Abstract: The Hypothalamic-Pituitary-Adrenal (HPA) axis is the key regulatory pathway responsible for maintaining homeostasis under conditions of real or perceived stress. Endocrine responses to stressors are mediated by adrenocorticotrophic hormone (ACTH) and corticosteroid (CORT) hormones. In healthy\, non-stressed conditions\, ACTH and CORT exhibit highly correlated ultradian pulsatility with an amplitude modulated by circadian processes. Disruption of these hormonal rhythms can occur as a result of stressors or in the very early stages of disease. Despite the fact that misaligned endocrine rhythms are associated with increased morbidity\, a quantitative understanding of their mechanistic 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 perturbations. Whilst a healthy HPA axis maintains a certain degree of robustness 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 explore how these challenges are being addressed by combining high-resolution biosampling techniques with mathematical and computational analysis methods. This interdisciplinary approach is helping us quantify the inter-individual variability of daily hormone profiles and develop novel “dynamic biomarkers” that serve as a normative reference and to signal endocrine dysfunction. By shifting from a qualitative to a quantitative description of the HPA axis\, these insights bring us a step closer to personalised clinical interventions for which timing is key.
URL:https://www.ibs.re.kr/bimag/event/eder-zavala-quantitative-analysis-of-high-resolution-daily-profiles-of-hpa-axis-hormones/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2023/08/Eder-Zavala-e1722177727704.jpeg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20231020T110000
DTEND;TZID=Asia/Seoul:20231020T120000
DTSTAMP:20260405T231246
CREATED:20230831T143835Z
LAST-MODIFIED:20231124T001740Z
UID:8411-1697799600-1697803200@www.ibs.re.kr
SUMMARY:Tetsuya J. Kobayashi\, Optimality of Biological Information Processing
DESCRIPTION:Abstract: \nAlmost all biological systems possess the ability to gather environmental information and modulate their behaviors to adaptively respond to changing environments. While animals excel at sensing odors\, even simple bacteria can detect faint chemicals using stochastic receptors. They then navigate towards or away from the chemical source by processing this sensed information through intracellular reaction systems. \nIn the first half of our talk\, we demonstrate that the E. coli chemotactic system is optimally structured for sensing noisy signals and controlling taxis. We utilize filtering theory and optimal control theory to theoretically derive this optimal structure and compare it to the quantitatively verified biochemical model of chemotaxis. \nIn the latter half\, we discuss the limitations of traditional information theory\, filtering theory\, and optimal control theory in analyzing biological systems. Notably\, all biological systems\, especially simpler ones\, have constrained computational resources like memory size and energy\, which influence optimal behaviors. Conventional theories don’t directly address these resource constraints\, likely because they emerged during a period when computational resources were continually expanding. To address this gap\, we introduce the “memory-limited partially observable optimal control\,” a new theoretical framework developed by our group\, and explore its relevance to biological problems.
URL:https://www.ibs.re.kr/bimag/event/tetsuya-j-kobayashi-optimality-of-biological-information-processing/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2023/08/Tetsuya-Kobayashi-1.jpeg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20230920T160000
DTEND;TZID=Asia/Seoul:20230920T170000
DTSTAMP:20260405T231246
CREATED:20230831T142706Z
LAST-MODIFIED:20240728T144517Z
UID:8397-1695225600-1695229200@www.ibs.re.kr
SUMMARY:Sebastian Walcher\, Reaction networks: Reduction of dimension and critical parameters
DESCRIPTION:Abstract: Typically\, 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 solutions in various parameter regions. In applications\, identifying the reaction parameters is a fundamental task. Reduction of dimension is desirable from a practical perspective\, and even necessary when different timescales are present. For biochemical reaction networks\, a classical reduction technique assumes quasi-steady state (QSS) of certain species. From a general mathematical perspective\, singular perturbation theory – involving a small 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 parameters for singular perturbations. (“How does one find small parameters?”) Quasi-steady state and singular perturbations. (“What is applicable\, what is correct?”)
URL:https://www.ibs.re.kr/bimag/event/sebastian-walcher-reaction-networks-reduction-of-dimension-and-critical-parameters/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2023/08/Sebastian-Walcher-1-e1722177866528.jpeg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20230609T110000
DTEND;TZID=Asia/Seoul:20230609T120000
DTSTAMP:20260405T231246
CREATED:20230218T033305Z
LAST-MODIFIED:20230529T011204Z
UID:7356-1686308400-1686312000@www.ibs.re.kr
SUMMARY:Sushmita Roy\, Deciphering gene regulatory networks underlying cell-fate specification
DESCRIPTION:Abstract: Cell fate specification is a dynamic process during which gene regulatory networks (GRNs) transition between different states and define cell type-specific patterns of gene expression. Identifying such cell type-specific gene regulatory networks is important for understanding how cells differentiate to diverse lineages from a progenitor state\, how differentiated cells can be reprogrammed\, and how these networks get disrupted in diseases such as cancer and developmental disorders. The advent of single cell omics has enabled us to perform high-throughput molecular phenotyping of individual cells at different omic levels. These technologies have revolutionized our understanding of cell type composition across diverse normal and disease conditions; however inferring cell type-specific networks and their dynamics from single cell omic datasets is an open challenge. I will present some of our recent efforts for inference and analysis of cell type-specific regulatory networks from single cell omic datasets. Application of our approach to hematopoietic differentiation and mouse cellular reprogramming predicted key regulatory nodes likely important for establishing different cell-type specific expression programs.
URL:https://www.ibs.re.kr/bimag/event/tbd-2/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/png:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2023/02/srpic-1.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20230524T160000
DTEND;TZID=Asia/Seoul:20230524T170000
DTSTAMP:20260405T231246
CREATED:20230213T110844Z
LAST-MODIFIED:20230308T101313Z
UID:7342-1684944000-1684947600@www.ibs.re.kr
SUMMARY:Thomas Philipp\, Stochastic gene expression in lineage trees
DESCRIPTION:Abstract: Stochasticity in gene expression is an important source of cell-to-cell variability (or noise) in clonal cell populations. So far\, this phenomenon has been studied using the Gillespie Algorithm\, or the Chemical Master Equation\, which implicitly assumes that cells are independent and do neither grow nor divide. This talk will discuss recent developments in modelling populations of growing and dividing cells through agent-based approaches. I will show how the lineage structure affects gene expression noise over time\, which leads to a straightforward interpretation of cell-to-cell variability in population snapshots. I will also illustrate how cell cycle variability shapes extrinsic noise across lineage trees. Finally\, I outline how to construct effective chemical master equation models based on dilution reactions and extrinsic variability that provide surprisingly accurate approximations of the noise statistics across growing populations. The results highlight that it is crucial to consider cell growth and division when quantifying cellular noise.
URL:https://www.ibs.re.kr/bimag/event/stochastic-gene-expression-in-lineage-trees/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2023/02/PThomastojpeg_1587640386131_x2.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20230510T160000
DTEND;TZID=Asia/Seoul:20230510T170000
DTSTAMP:20260405T231246
CREATED:20230213T110735Z
LAST-MODIFIED:20230308T101512Z
UID:7339-1683734400-1683738000@www.ibs.re.kr
SUMMARY:Mogens Jensen\, Droplet formation\, DNA repair and chaos in CellsBD
DESCRIPTION:Abstract: TBD
URL:https://www.ibs.re.kr/bimag/event/tbd/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2023/02/Mogens_Hogh_Jensen.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20230428T110000
DTEND;TZID=Asia/Seoul:20230428T120000
DTSTAMP:20260405T231246
CREATED:20230213T110626Z
LAST-MODIFIED:20230308T101702Z
UID:7336-1682679600-1682683200@www.ibs.re.kr
SUMMARY:Hans P.A. Van Dongen\, Modeling the temporal dynamics of neurobehavioral performance impairment due to sleep loss and circadian misalignment
DESCRIPTION:Abstract: The well-known two-process model of sleep regulation makes accurate predictions of sleep timing and duration\, as well as neurobehavioral performance\, for a variety of acute sleep deprivation and nap sleep scenarios\, but it fails to predict the effects of chronic sleep restriction on neurobehavioral performance. The two-process model belongs to a broader class of coupled\, non-homogeneous\, 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 impairment due to sleep loss. The equations implicate a biological system analogous to two connected compartments containing interacting compounds with time-varying concentrations\, such as the adenosinergic neuromodulator/receptor system\, as a key mechanism for the regulation of neurobehavioral functioning under conditions of sleep loss. The equations account for dynamic interaction with circadian rhythmicity\, and also provide a new approach to dynamically tracking the magnitude of sleep inertia upon awakening from restricted sleep. This presentation will describe the development of the ODE system and its experimental calibration and validation\, and will discuss some novel predictions.
URL:https://www.ibs.re.kr/bimag/event/modeling-the-temporal-dynamics-of-neurobehavioral-performance-impairment-due-to-sleep-loss-and-circadian-misalignment/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/png:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2023/02/HANS-VAN-DONGEN-396x293-1.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20230407T110000
DTEND;TZID=Asia/Seoul:20230407T120000
DTSTAMP:20260405T231246
CREATED:20230213T110215Z
LAST-MODIFIED:20230308T100617Z
UID:7328-1680865200-1680868800@www.ibs.re.kr
SUMMARY:George Karniadakis\, BINNS: Biophysics-Informed Neural Networks
DESCRIPTION:Abstract: We will present a new approach to develop a data-driven\, learning-based framework for predicting outcomes of biophysical systems and for discovering hidden mechanisms and pathways from noisy data. We will introduce a deep learning approach based on neural networks (NNs) and on generative adversarial networks (GANs). Unlike other approaches that rely on big data\, here we “learn” from small data by exploiting the information provided by the mathematical physics\, e.g..\, conservation laws\, reaction kinetics\, etc\,. which are used to obtain informative priors or regularize the neural networks. We will demonstrate how we can train BINNs from multifidelity/multimodality data\, and we will present several examples of inverse problems\, e.g.\, in systems biology for diabetes and in biomechanics for non-invasive inference of thrombus material properties. We will also discuss how operator regression in the form of DeepOnet can be used to accelerate inference based on historical data and only a few new data\, as well its generalization and transfer learning capacity.
URL:https://www.ibs.re.kr/bimag/event/binns-biophysics-informed-neural-networks/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2023/02/GeorgeKarniadakis.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20230324T160000
DTEND;TZID=Asia/Seoul:20230324T170000
DTSTAMP:20260405T231246
CREATED:20230213T105312Z
LAST-MODIFIED:20230320T010451Z
UID:7318-1679673600-1679677200@www.ibs.re.kr
SUMMARY:(Rescheduled: 3/22 -> 3/24) Stefan Bauer\, Neural Causal Models for Experimental Design
DESCRIPTION:Abstract: Many questions in everyday life as well 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? Inherently\, such questions need to specify the causal variables relevant to the question and their interactions. However\, existing algorithms for learning causal graphs from data are often not scaling well both with the number of variables or the number of observations. This talk will provide a brief introduction to causal structure learning\, recent efforts in using continuous optimization to learn causal graphs at scale and systematic approaches for causal experimental design at scale.
URL:https://www.ibs.re.kr/bimag/event/neural-causal-models-for-experimental-design/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2023/02/jItlmUQr_400x400.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20230315T160000
DTEND;TZID=Asia/Seoul:20230315T170000
DTSTAMP:20260405T231246
CREATED:20230213T105947Z
LAST-MODIFIED:20230312T051759Z
UID:7324-1678896000-1678899600@www.ibs.re.kr
SUMMARY:Julio Saez-Rodriguez\, Dynamic logic models complement machine learning for personalized medicine
DESCRIPTION:Abstract: \nMulti-omics technologies\, and in particular those with single-cell and spatial resolution\, provide unique opportunities to study the deregulation of intra- and inter-cellular signaling processes in disease. I will present recent methods and applications from our group toward this aim\, focusing on computational approaches that combine data with biological knowledge within statistical and machine learning methods. This combination allows us to increase both the statistical power of our analyses and the mechanistic interpretability of the results. These approaches allow us to identify key processes\, that can be in turn studied in detailed with dynamic mechanistic models. I will then present how cell-specific logic models\, trained with measurements upon perturbations\, can provides new biomarkers and treatment opportunities. Finally\, I will show how\, using novel microfluidics-based technologies\, this approach can also be applied directly to biopsies\, allowing to build mechanistic models for individual cancer patients\, and use these models to prose new therapies.
URL:https://www.ibs.re.kr/bimag/event/dynamic-logic-models-complement-machine-learning-for-personalized-medicine/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2023/02/SAEZ_Rodriguez_Julio_March_2014-copy-e1508925747488.jpeg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20230310T100000
DTEND;TZID=Asia/Seoul:20230310T110000
DTSTAMP:20260405T231246
CREATED:20230213T105750Z
LAST-MODIFIED:20230306T000259Z
UID:7321-1678442400-1678446000@www.ibs.re.kr
SUMMARY:Martin Nowak\, Evolution of cooperation
DESCRIPTION:Abstract: Cooperation means that one individual pays a cost for another to receive a benefit. Cooperation can be at variance with natural selection. Why should you help competitors? Yet cooperation is abundant in nature and is important component of evolutionary innovation. Cooperation can be seen as the master architect of evolution and as the third fundamental principle of evolution beside mutation and selection. I will present five mechanisms for the evolution of cooperation: direct reciprocity\, indirect reciprocity\, spatial selection\, group selection and kin selection. Global cooperation and the cooperation with future generations is necessary to ensure the survival of our species. \nFurther reading:\nNowak MA (2006). Evolutionary Dynamics. Harvard University Press\nNowak MA & Highfield R (2011) SuperCooperators. Simon & Schuster.\nHauser OP\, Rand DG\, Peysakhovich A & Nowak MA (2014). Cooperating with the future. Nature 511: 220-223\nHilbe C\, Šimsa Š\, Chatterjee K & Nowak MA (2018). Evolution of cooperation in stochastic games. Nature 559: 246-249\nHauser OP\, Hilbe C\, Chatterjee K & Nowak MA (2019). Social dilemmas among unequals. Nature 572: 524-527
URL:https://www.ibs.re.kr/bimag/event/evolution-of-cooperation/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2023/02/MartinNowak_250.jpeg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20230303T110000
DTEND;TZID=Asia/Seoul:20230303T120000
DTSTAMP:20260405T231246
CREATED:20230213T110430Z
LAST-MODIFIED:20230227T013418Z
UID:7331-1677841200-1677844800@www.ibs.re.kr
SUMMARY:Shinya Kuroda\, Systems Biology of Insulin Action
DESCRIPTION:Abstract: \n1. The “temporal information code” of insulin action: a bottom-up approach One of the essential elements of signaling networks is to encode information from a wide variety of inputs into a limited set of molecules. We have proposed a “temporal information code” that regulates 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 blood insulin is selectively decoded by downstream networks. \n2. Transomics of insulin action: a top-down approach In order to obtain a complete picture 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 talk about approach the principle of homeostasis of living organisms by temporal patterns\, using the analysis of systems biology of insulin action using two different approaches.
URL:https://www.ibs.re.kr/bimag/event/systems-biology-of-insulin-action/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20221209T110000
DTEND;TZID=Asia/Seoul:20221209T120000
DTSTAMP:20260405T231246
CREATED:20220825T013528Z
LAST-MODIFIED:20221207T064542Z
UID:6504-1670583600-1670587200@www.ibs.re.kr
SUMMARY:Taming Complexity in Data-Limited Nonlinear Nonequilibrium Settings
DESCRIPTION:Abstract: \nSince before the time of Aristotle and the natural philosophers\, reductionism has played a foundational role in western scientific thought. The premise of reductionism is that systems can be broken down into constituent pieces and studied independently\, then reassembled to understand the behavior of the system as a whole. It embodies the classical linear perspective. 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 many components acting together and changing in time. \nNonlinearity in living systems means that its parts are interdependent – variables do not act in a mutually independent manner; rather they interact\, and as a consequence associations (correlations) between them will change as the overall system context (state) changes.  This problem is highlighted when extrapolating the results of single-factor experiments to nature\, and surely contributes to the frustrating disconnect between experimental findings and clinical outcomes in drug trials. Indeed\, while everyone knows Berkeley’s 1710 dictum “correlation does not imply causation” few realize that for nonlinear systems the converse “causation does not imply correlation” is also true. This conundrum runs counter to deeply ingrained heuristic thinking that is at the basis of modern science. Biological systems (esp. ecosystems) are particularly perverse on this issue by exhibiting mirage correlations that can continually cause us to rethink relationships we thought we understood. \nHere we examine a minimalist paradigm\, empirical dynamics (EDM)\, for studying non-linear systems and a method (CCM) that can detect causality when there is no correlation among variables. It is a data-driven approach that uses time series to study a system holistically by reconstructing its attractor – a geometric object that embodies the rules of a full set of equations for the system.  The ideas are intuitive and will be illustrated with examples from genetics\, ecology and epidemiology. \nA python version of EDM tools can be found at https://pepy.tech/project/pyEDM
URL:https://www.ibs.re.kr/bimag/event/2022-12-09-colloquium/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2022/08/Sugihara_George_250x250.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20221202T110000
DTEND;TZID=Asia/Seoul:20221202T120000
DTSTAMP:20260405T231246
CREATED:20220825T011607Z
LAST-MODIFIED:20220828T060439Z
UID:6474-1669978800-1669982400@www.ibs.re.kr
SUMMARY:Mammalian synthetic biology by controller design
DESCRIPTION:Abstract: The ability to reliably engineer the mammalian cell will impact a variety of applications in a disruptive way\, including cell fate control and reprogramming\, targeted drug delivery\, and regenerative medicine. However\, our current ability to engineer mammalian genetic circuits that behave as predicted remains limited. These circuits depend on the intra and extra cellular environment in ways that are difficult to anticipate\, and this fact often hampers genetic circuit performance. This lack of robustness to poorly known and often variable cellular environment is the subject of this talk. Specifically\, I will describe control engineering approaches that make the performance of genetic devices robust to context. I will show a feedforward controller that makes gene expression robust to variability in cellular resources and\, more generally\, to changes in intra-cellular context linked to differences in cell type. I will then show a feedback controller that uses bacterial two component signaling systems to create a quasi-integral controller that makes the input/output response of a genetic device robust to a variety of perturbations that affect gene expression. These solutions support rational and modular design of sophisticated genetic circuits and can serve for engineering biological circuits that are more robust and predictable across changing contexts.
URL:https://www.ibs.re.kr/bimag/event/2022-12-02-colloquium/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2022/08/Domitilla-Del-Vecchio-250x250-1.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20221130T160000
DTEND;TZID=Asia/Seoul:20221130T170000
DTSTAMP:20260405T231246
CREATED:20220825T013203Z
LAST-MODIFIED:20221124T211611Z
UID:6498-1669824000-1669827600@www.ibs.re.kr
SUMMARY:Brain dynamics during shiftwork: from maths and codes to real-world applications
DESCRIPTION:Abstract: \nCircadian clocks control the timing and 24-hour periodicity of virtually all physiological rhythms including sleep\, cognition\, and metabolism. There are optimal times for most behaviours; e.g.\, the best sleep is achieved during low circadian activity (night)\, while meals and physical exercise are best placed during high circadian activity (day) when metabolic rates\, stress hormone levels\, and blood pressure are higher. However\, the demands of our 24/7 society often result in misalignment of these environmental\, behavioural and physiological rhythms with the typical examples being shiftwork\, jetlag\, and circadian disorders. This circadian misalignment results in inadequate sleep\, fatigue\, increased risk of accidents\, and in the long-term\, development of disease including cancer and diabetes. Mathematical modelling of circadian misalignment is used to better understand the circadian and sleep regulation and make predictions to reduce risk of fatigue-related accidents. In this talk I will present an overview of our studies of shiftwork modelling and our journey from fundamental modelling research of sleep and circadian rhythms to development of software tools and real-world applications.
URL:https://www.ibs.re.kr/bimag/event/2022-11-30-colloquium/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2022/08/SvetlanaPostnova-250x250-1.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20221123T160000
DTEND;TZID=Asia/Seoul:20221123T170000
DTSTAMP:20260405T231246
CREATED:20220825T012839Z
LAST-MODIFIED:20221119T072455Z
UID:6494-1669219200-1669222800@www.ibs.re.kr
SUMMARY:Assessing the limits of control of Covid-19 outbreaks using agent-based modeling
DESCRIPTION:Transmission of SARS-CoV-2 relies on interactions between humans. Heterogeneity and stochasticity both in human-human interactions and in the transmission of the virus give rise to non-linear infection networks that gain complexity with time. \nWe assessed the limits of control and the effect of pharmaceutical and non-pharmaceutical measures against COVID‐19 outbreaks with a detailed community‐specific agent-based model (GERDA). The demographic and geographic structure of the concrete communities influence the pattern of infection spreading. Stochastic community dynamics and limited vaccination can lead to bimodal outcomes\, rendering predictions about infection spreading and effects of nonpharmaceutical interventions uncertain. \n  \nBy comparing different vaccination strategies\, we found that the herd immunity threshold depends strongly on the applied vaccination strategy.  When vaccine supply is limited\, different vaccination strategies are optimal for the intended goal e.g.\, reducing fatalities or confining an outbreak. Prioritizing highly interactive people diminishes the risk for an infection wave\, while prioritizing the elderly minimizes fatalities. \nThe 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 scenarios the reproduction number R0 is not a suitable predictor for the system behavior or the infectiousness of the virus. \nThe developed simulation platform can process and analyze dynamic COVID‐19 epidemiological situations in diverse communities worldwide to predict pathways to population immunity even with limited vaccination.
URL:https://www.ibs.re.kr/bimag/event/2022-11-23-colloquium/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2022/08/klipp2-250x250-1.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20221118T110000
DTEND;TZID=Asia/Seoul:20221118T120000
DTSTAMP:20260405T231246
CREATED:20220825T012410Z
LAST-MODIFIED:20221114T224951Z
UID:6490-1668769200-1668772800@www.ibs.re.kr
SUMMARY:Quantifying dynamical changes in sparse\, noisy\, high-dimensional data
DESCRIPTION:The circadian clock orchestrates a vast array of behavioral and physiological processes with a 24-hour cycle\, enabling nearly all organisms — from bread mold 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 self-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 evidence suggests that the clock is crucial for mediating the response to changes in an organism’s environment (such as temperature and food availability)\, 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 genes are under circadian control and how their dynamics change under different environmental conditions. Analyzing this transcriptomic time-series data 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 analyze circadian transcriptomic data by exploiting results from dynamical systems theory\, nonlinear dimension reduction\, and topological data analysis.
URL:https://www.ibs.re.kr/bimag/event/2022-11-18-colloquium/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2022/08/braun_rosemary.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20221109T160000
DTEND;TZID=Asia/Seoul:20221109T170000
DTSTAMP:20260405T231246
CREATED:20220825T012221Z
LAST-MODIFIED:20220902T003131Z
UID:6486-1668009600-1668013200@www.ibs.re.kr
SUMMARY:Modeling cell-to-cell heterogeneity from a signaling network
DESCRIPTION:Cells make individual fate decisions through linear and nonlinear regulation of gene network\, generating diverse dynamics from a single reaction pathway. In this colloquium\, I will present two topics of our recent work on signaling dynamics at cellular and patient levels. The first example is about the initial value of the model\, as a mechanism to generate different dynamics from a single pathway in cancer and the use of the dynamics for stratification of the patients [1-3]. Models of ErbB receptor signaling have been widely used in prediction of drug sensitivity for many types of cancers. We trained the ErbB model with the data obtained from cancer cell lines and predicted the common parameters of the model. By simulation of the ErbB model with those parameters and individual patient transcriptome data as initial values\, we were able to classify the prognosis of breast cancer patients and drug sensitivity 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 the 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 regions of the putative transcription factor binding sites and the cooperativity in their interaction significantly influenced the cell-to cell heterogeneity 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 mechanisms are important in our understanding the cell as a system for encoding and decoding signals for fate decisions and its application to human diseases. \n[References] \n[1] Nakakuki et al. Cell 2010\,\n[2] Imoto et al. iScience 2022\,\n[3] Imoto et al. STAR Protocols 2022\,\n[4] Shinohara et al. Science 2014\,\n[5] Michida et al. Cell Reports 2020\,\n[6] Wibisana et al. PLoS Genetics 2022
URL:https://www.ibs.re.kr/bimag/event/2022-11-09-colloquium/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2022/08/okada-250x250-1.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20221026T160000
DTEND;TZID=Asia/Seoul:20221026T170000
DTSTAMP:20260405T231246
CREATED:20220825T012029Z
LAST-MODIFIED:20220925T142427Z
UID:6482-1666800000-1666803600@www.ibs.re.kr
SUMMARY:Mathematical modelling of the sleep-wake cycle: light\, clocks and social rhythms
DESCRIPTION:Abstract: \nWe’re all familiar with sleep\, but how can we mathematically model it? And what determines how long and when we sleep? In this talk I’ll introduce the nonsmooth coupled oscillator systems that form the basis of current models of sleep-wake regulation and discuss their dynamical behaviour. I will describe how we are using models to unravel environmental\, societal and physiological factors that determine sleep timing and outline how we are using models to inform the quantitative design of light interventions for mental health disorders and address contentious societal questions such as whether to move school start time for adolescents.
URL:https://www.ibs.re.kr/bimag/event/2022-10-26-colloquium/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2022/08/anne-skeldon.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20221021T110000
DTEND;TZID=Asia/Seoul:20221021T120000
DTSTAMP:20260405T231246
CREATED:20220825T011824Z
LAST-MODIFIED:20220916T014258Z
UID:6478-1666350000-1666353600@www.ibs.re.kr
SUMMARY:Stationary distributions and positive recurrence of chemical reaction networks
DESCRIPTION:Abstract: \nCellular\, chemical\, and population processes are all often represented via networks that describe the interactions between the different population types (typically called the “species”). If the counts of the species are low\, then these systems are often modeled as continuous-time Markov 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 qualitative properties of the dynamical system relate to the graph properties of the network? For example\, it is of particular interest to know which graph properties imply that the stochastically modeled reaction network is positive recurrent\, and therefore admits a stationary distribution. After a general introduction to the models of interest\, I will discuss this problem\, giving some of the known results. I will also discuss recent progress on the Chemical Recurrence Conjecture\, which has been open for decades\, which is the following: if each connected component of the network is strongly connected\, then the associated stochastic model is positive recurrent.
URL:https://www.ibs.re.kr/bimag/event/2022-10-21-colloquium/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2022/08/DAnderson2018-250x250-1.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20221021T103000
DTEND;TZID=Asia/Seoul:20221021T110000
DTSTAMP:20260405T231246
CREATED:20220916T014503Z
LAST-MODIFIED:20220916T014503Z
UID:6575-1666348200-1666350000@www.ibs.re.kr
SUMMARY:A Brief Introduction to Stochastic Reaction Networks
DESCRIPTION:Abstract: TBA
URL:https://www.ibs.re.kr/bimag/event/2022-10-21-colloquium-2/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2022/08/DAnderson2018-250x250-1.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20221007T110000
DTEND;TZID=Asia/Seoul:20221007T120000
DTSTAMP:20260405T231246
CREATED:20220825T011205Z
LAST-MODIFIED:20220901T005901Z
UID:6471-1665140400-1665144000@www.ibs.re.kr
SUMMARY:Time-keeping and Decision-making in the Cell Cycle
DESCRIPTION:Abstract: Cell 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 ‘copy machine’\, making new daughter cells as warranted. Cells growing under ideal conditions divide with clock-like regularity; however\, if they are challenged with DNA-damaging agents or mitotic spindle disruptors\, they will not progress to the next stage of the cycle until the damage is repaired. These ‘decisions’ (to exit and re-enter the cell cycle) are essential to maintain the integrity of the genome from generation to generation. A crucial challenge for molecular cell biologists in the 1990s was to unravel the genetic and biochemical mechanisms of cell cycle control in eukaryotes. Central to this effort were biochemical studies of the clock-like regulation of ‘mitosis promoting factor’ during synchronous mitotic cycles of fertilized frog eggs and genetic studies of the switch-like regulation of ‘cyclin-dependent kinases’ in yeast cells. The complexity of these control systems demands a dynamical approach\, as described in the first lecture. Using mathematical models of the control systems\, I will uncover some of the secrets of cell cycle ‘clocks’ and ‘switches’.
URL:https://www.ibs.re.kr/bimag/event/2022-10-07-colloquium2/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/png:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2022/08/Tyson_profile-250x250-1.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20221007T103000
DTEND;TZID=Asia/Seoul:20221007T110000
DTSTAMP:20260405T231246
CREATED:20220825T011010Z
LAST-MODIFIED:20220901T010141Z
UID:6468-1665138600-1665140400@www.ibs.re.kr
SUMMARY:A Dynamic Paradigm for Molecular Cell Biology
DESCRIPTION:Abstract: The driving passion of molecular cell biologists is to understand the molecular mechanisms that control important aspects of cell physiology\, but this ambition is – paradoxically – limited by the very wealth of molecular details currently known about these mechanisms. Their complexity overwhelms our intuitive notions of how molecular regulatory networks might respond under normal and stressful conditions. To make progress we need a new paradigm for connecting molecular biology to cell physiology. I will outline an approach that uses precise mathematical methods to associate the qualitative features of dynamical systems\, as conveyed by ‘bifurcation diagrams’\, with ‘signal–response’ curves measured by cell biologists.
URL:https://www.ibs.re.kr/bimag/event/2022-10-01-colloquium1/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/png:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2022/08/Tyson_profile-250x250-1.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
END:VCALENDAR