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X-ORIGINAL-URL:https://www.ibs.re.kr/bimag
X-WR-CALDESC:Events for Biomedical Mathematics Group
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BEGIN:VTIMEZONE
TZID:Asia/Seoul
BEGIN:STANDARD
TZOFFSETFROM:+0900
TZOFFSETTO:+0900
TZNAME:KST
DTSTART:20210101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20221226T100000
DTEND;TZID=Asia/Seoul:20221226T120000
DTSTAMP:20260424T062821
CREATED:20221226T004917Z
LAST-MODIFIED:20260404T011224Z
UID:7164-1672048800-1672056000@www.ibs.re.kr
SUMMARY:IBS BIMAG 2022 Winter Internship Workshop
DESCRIPTION:IBS BIMAG will host a kick-off workshop for the winter internships on Monday\, 26 December 2022. The internship participants from Pusan National University and Postech will give 8 minutes presentations on their research topics. \nPresentation List:\n\n김미지 (Miji Kim) – A Comparison Study of Dropout to Prevent Overfitting Problem in CNN Image Data Classification\n김지현 (Jihyeon Kim)- Study of Ensemble Kalman Filter\n이시은 (Sieun Lee) – Early Detection using Epidemic Data\n이유진 (Youjin Lee) – On Parameter Estimation Approaches for Biomathematical Models through Physics-Informed Neural Networks\n장근수 (Geunsoo Jang) – Development of mathematical model for impact evaluation of Radioactive Water Discharge in Fukushima\n김진영 (Jinyoung Kim) – Stochastic aggregation models in 2D and 3D spaces to describe Liquid-Liquid Phase Separation (LLPS)\n김민준 (Minjoon Kim) –  Stability of Chemical reaction networks
URL:https://www.ibs.re.kr/bimag/event/ibs-bimag-winter-internship-workshop/
LOCATION:IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Lunch Lab Meeting Seminar
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20221223T150000
DTEND;TZID=Asia/Seoul:20221223T170000
DTSTAMP:20260424T062821
CREATED:20221222T082248Z
LAST-MODIFIED:20221222T082248Z
UID:7075-1671807600-1671814800@www.ibs.re.kr
SUMMARY:Olive Cawiding\, Optimal control of aging in complex networks
DESCRIPTION:We will discuss about “Optimal control of aging in complex networks”\,\nSun\, Eric D.\, Thomas CT Michaels\, and L. Mahadevan\, Proceedings of the National Academy of Sciences 117.34 (2020): 20404-20410. \nAbstract \n\n\n\nMany complex systems experience damage accumulation\, which leads to aging\, manifest as an increasing probability of system collapse with time. This naturally raises the question of how to maximize health and longevity in an aging system at minimal cost of maintenance and intervention. Here\, we pose this question in the context of a simple interdependent network model of aging in complex systems and show that it exhibits cascading failures. We then use both optimal control theory and reinforcement learning alongside a combination of analysis and simulation to determine optimal maintenance protocols. These protocols may motivate the rational design of strategies for promoting longevity in aging complex systems with potential applications in therapeutic schedules and engineered system maintenance.
URL:https://www.ibs.re.kr/bimag/event/2022-12-23-jc/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20221216T130000
DTEND;TZID=Asia/Seoul:20221216T150000
DTSTAMP:20260424T062821
CREATED:20221214T122407Z
LAST-MODIFIED:20221214T122407Z
UID:7022-1671195600-1671202800@www.ibs.re.kr
SUMMARY:Role of DNA binding sites and slow unbinding kinetics in titration-based oscillators
DESCRIPTION:We will discuss about “Role of DNA binding sites and slow unbinding kinetics in titration-based oscillators”\, Karapetyan\, Sargis\, and Nicolas E. Buchler\,Physical Review E 92.6 (2015): 062712. \nAbstract \n\n\n\nGenetic oscillators\, such as circadian clocks\, are constantly perturbed by molecular noise arising from the small number of molecules involved in gene regulation. One of the strongest sources of stochasticity is the binary noise that arises from the binding of a regulatory protein to a promoter in the chromosomal DNA. In this study\, we focus on two minimal oscillators based on activator titration and repressor titration to understand the key parameters that are important for oscillations and for overcoming binary noise. We show that the rate of unbinding from the DNA\, despite traditionally being considered a fast parameter\, needs to be slow to broaden the space of oscillatory solutions. The addition of multiple\, independent DNA binding sites further expands the oscillatory parameter space for the repressor-titration oscillator and lengthens the period of both oscillators. This effect is a combination of increased effective delay of the unbinding kinetics due to multiple binding sites and increased promoter ultrasensitivity that is specific for repression. We then use stochastic simulation to show that multiple binding sites increase the coherence of oscillations by mitigating the binary noise. Slow values of DNA unbinding rate are also effective in alleviating molecular noise due to the increased distance from the bifurcation point. Our work demonstrates how the number of DNA binding sites and slow unbinding kinetics\, which are often omitted in biophysical models of gene circuits\, can have a significant impact on the temporal and stochastic dynamics of genetic oscillators.
URL:https://www.ibs.re.kr/bimag/event/2022-12-16-jc/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20221213T160000
DTEND;TZID=Asia/Seoul:20221213T170000
DTSTAMP:20260424T062821
CREATED:20221209T045119Z
LAST-MODIFIED:20221211T121541Z
UID:6984-1670947200-1670950800@www.ibs.re.kr
SUMMARY:Static and Dynamic Absolute Concentration Robustness
DESCRIPTION:Absolute Concentration Robustness (ACR) was introduced by Shinar and Feinberg (Science 327:1389-1391\, 2010) as robustness of equilibrium species concentration in a mass action dynamical system. Their aim was to devise a mathematical condition that will ensure robustness in the function of the biological system being modeled. The robustness of function rests on what we refer to as empirical robustness — the concentration of a species remains unvarying\, when measured in the long run\, across arbitrary initial conditions. Even simple examples show that the ACR notion introduced in Shinar and Feinberg (here referred to as static ACR) is neither necessary nor sufficient for empirical robustness. To make a stronger connection with empirical robustness\, we define dynamic ACR\, a property related to long-term\, global dynamics\, rather than only to equilibrium behavior. We discuss general dynamical systems with dynamic ACR properties as well as parametrized families of dynamical systems related to reaction networks. In particular\, we find necessary and sufficient conditions for dynamic ACR in complex balanced reaction networks\, a class of networks that is central to the theory of reaction networks.This is joint work with Badal Joshi (CSUSM)
URL:https://www.ibs.re.kr/bimag/event/static-and-dynamic-absolute-concentration-robustness/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Biomedical Mathematics Seminar
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:20260424T062821
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:20221202T150000
DTEND;TZID=Asia/Seoul:20221202T170000
DTSTAMP:20260424T062821
CREATED:20221128T010402Z
LAST-MODIFIED:20221128T010402Z
UID:6906-1669993200-1670000400@www.ibs.re.kr
SUMMARY:Multiparameter persistent homology landscapes identify immune cell spatial patterns in tumors
DESCRIPTION:We will discuss about “Multiparameter persistent homology landscapes identify immune cell spatial patterns in tumors”\, Vipond\, Oliver\, et al\, Proceedings of the National Academy of Sciences 118.41 (2021): e2102166118. \nAbstract\nHighly resolved spatial data of complex systems encode rich and nonlinear information. Quantification of heterogeneous and noisy data—often with outliers\, artifacts\, and mislabeled points—such as those from tissues\, remains a challenge. The mathematical field that extracts information from the shape of data\, topological data analysis (TDA)\, has expanded its capability for analyzing real-world datasets in recent years by extending theory\, statistics\, and computation. An extension to the standard theory to handle heterogeneous data is multiparameter persistent homology (MPH). Here we provide an application of MPH landscapes\, a statistical tool with theoretical underpinnings. MPH landscapes\, computed for (noisy) data from agent-basedMultiparameter persistent homology landscapes identify immune cell spatial patterns in tumors model simulations of immune cells infiltrating into a spheroid\, are shown to surpass existing spatial statistics and one-parameter persistent homology. We then apply MPH landscapes to study immune cell location in digital histology images from head and neck cancer. We quantify intratumoral immune cells and find that infiltrating regulatory T cells have more prominent voids in their spatial patterns than macrophages. Finally\, we consider how TDA can integrate and interrogate data of different types and scales\, e.g.\, immune cell locations and regions with differing levels of oxygenation. This work highlights the power of MPH landscapes for quantifying\, characterizing\, and comparing features within the tumor microenvironment in synthetic and real datasets.
URL:https://www.ibs.re.kr/bimag/event/2022-12-02-jc/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
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:20260424T062821
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:20260424T062821
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:20260424T062821
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:20221118T150000
DTEND;TZID=Asia/Seoul:20221118T170000
DTSTAMP:20260424T062821
CREATED:20221117T034958Z
LAST-MODIFIED:20221117T034958Z
UID:6871-1668783600-1668790800@www.ibs.re.kr
SUMMARY:Detecting critical state before phase transition of complex biological systems by hidden Markov model
DESCRIPTION:We will discuss about “Detecting critical state before phase transition of complex biological systems by hidden Markov model”\, Chen\, Pei\, et al. Bioinformatics 32.14 (2016): 2143-2150. \n  \nAbstract \nMotivation: Identifying the critical state or pre-transition state just before the occurrence of a phase transition is a challenging task\, because the state of the system may show little apparent change before this critical transition during the gradual parameter variations. Such dynamics of phase transition is generally composed of three stages\, i.e. before-transition state\, pre-transition state and after-transition state\, which can be considered as three different Markov processes. \nResults: By exploring the rich dynamical information provided by high-throughput data\, we present a novel computational method\, i.e. hidden Markov model (HMM) based approach\, to detect the switching point of the two Markov processes from the before-transition state (a stationary Markov process) to the pre-transition state (a time-varying Markov process)\, thereby identifying the pre-transition state or early-warning signals of the phase transition. To validate the effectiveness\, we apply this method to detect the signals of the imminent phase transitions of complex systems based on the simulated datasets\, and further identify the pre-transition states as well as their critical modules for three real datasets\, i.e. the acute lung injury triggered by phosgene inhalation\, MCF-7 human breast cancer caused by heregulin and HCV-induced dysplasia and hepatocellular carcinoma. Both functional and pathway enrichment analyses validate the computational results.
URL:https://www.ibs.re.kr/bimag/event/2022-11-18-jc-2/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
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:20260424T062821
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:20221111T150000
DTEND;TZID=Asia/Seoul:20221111T170000
DTSTAMP:20260424T062821
CREATED:20221028T015855Z
LAST-MODIFIED:20221107T064232Z
UID:6740-1668178800-1668186000@www.ibs.re.kr
SUMMARY:PI-VAE: Physics-Informed Variational Auto-Encoder for stochastic differential equations
DESCRIPTION:We will discuss about “PI-VAE: Physics-Informed Variational Auto-Encoder for stochastic differential equations”\,\nZhong\, Weiheng\, and Hadi Meidani\, Computer Methods in Applied Mechanics and Engineering 403 (2023): 115664. \nAbstract\nWe propose a new class of physics-informed neural networks\, called the Physics-Informed Variational Auto-Encoder (PI-VAE)\, to solve stochastic differential equations (SDEs) or inverse problems involving SDEs. In these problems the governing equations are known but only a limited number of measurements of system parameters are available. PI-VAE consists of a variational autoencoder (VAE)\, which generates samples of system variables and parameters. This generative model is integrated with the governing equations. In this integration\, the derivatives of VAE outputs are readily calculated using automatic differentiation\, and used in the physics-based loss term. In this work\, the loss function is chosen to be the Maximum Mean Discrepancy (MMD) for improved performance\, and neural network parameters are updated iteratively using the stochastic gradient descent algorithm. We first test the proposed method on approximating stochastic processes. Then we study three types of problems related to SDEs: forward and inverse problems together with mixed problems where system parameters and solutions are simultaneously calculated. The satisfactory accuracy and efficiency of the proposed method are numerically demonstrated in comparison with physics-informed Wasserstein generative adversarial network (PI-WGAN).
URL:https://www.ibs.re.kr/bimag/event/2022-11-11-jc/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
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:20260424T062821
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:20221109T140000
DTEND;TZID=Asia/Seoul:20221109T150000
DTSTAMP:20260424T062821
CREATED:20221028T010418Z
LAST-MODIFIED:20221031T003941Z
UID:6747-1668002400-1668006000@www.ibs.re.kr
SUMMARY:Developing and designing dynamic mobile applications that transform wearable data with machine learning and mathematical models.
DESCRIPTION:Wearable analytics hold far more potential than sleep tracking or step counting. In recent years\, a number of applications have emerged which leverage the massive quantities of data being amassed by wearables around the world\, such as real-time mood detection\, advanced COVID screening\, and heart rate variability analysis. Yet packaging insights from research for success in the consumer market means prioritizing design and understandability\, while also seamlessly managing the sometimes-unreliable stream of data from the device. In this presentation\, I will discuss my own experiences building apps which interface with wearable data and process the data using mathematical modeling\, as well as recent work extending to other wearable streams and environmental controls.
URL:https://www.ibs.re.kr/bimag/event/2022-11-09/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Biomedical Mathematics Seminar
ATTACH;FMTTYPE=image/png:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2022/10/KakaoTalk_Photo_2022-10-28-10-19-48.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20221108T160000
DTEND;TZID=Asia/Seoul:20221108T170000
DTSTAMP:20260424T062821
CREATED:20221028T010543Z
LAST-MODIFIED:20221028T012054Z
UID:6748-1667923200-1667926800@www.ibs.re.kr
SUMMARY:Shift: A mobile application for shift workers leveraging wearable data\, mathematical models\, and connected devices
DESCRIPTION:Shift workers experience profound circadian disruption due to the nature of their work\, which often has them working at times when their internal clock is sending a strong signal for sleep. Mathematical models can be used to generate recommendations for shift workers that shift their body’s clock to better align with their work schedules\, to help them sleep\, feel\, and perform better. In this talk\, I will discuss our recent mobile app\, Shift\, which pulls wearable data from user’s devices and generates personalized recommendations to help them manage shift work schedules. I will also discuss how this product was designed\, how it can interface with Internet of Things devices\, and how its insights can be useful for other groups beyond shift workers.
URL:https://www.ibs.re.kr/bimag/event/developing-and-designing-dynamic-mobile-applications-that-transform-wearable-data-with-machine-learning-and-mathematical-models-2/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Biomedical Mathematics Seminar
ATTACH;FMTTYPE=image/png:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2022/10/KakaoTalk_Photo_2022-10-28-10-19-48.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20221104T150000
DTEND;TZID=Asia/Seoul:20221104T170000
DTSTAMP:20260424T062821
CREATED:20220930T035218Z
LAST-MODIFIED:20221030T231656Z
UID:6648-1667574000-1667581200@www.ibs.re.kr
SUMMARY:Model Reduction for the Chemical Master Equation: an Information-Theoretic Approach
DESCRIPTION:We will discuss about “Model Reduction for the Chemical Master Equation: an Information-Theoretic Approach”\, Öcal\, Kaan\, Guido Sanguinetti\, and Ramon Grima.\, arXiv preprint arXiv:2210.05329 (2022). \nAbstract: \nThe complexity of mathematical models in biology has rendered model reduction an essential tool in the quantitative biologist’s toolkit. For stochastic reaction networks described using the Chemical Master Equation\, commonly used methods include time-scale separation\, the Linear Mapping Approximation and state-space lumping. Despite the success of these techniques\, they appear to be rather disparate and at present no general-purpose approach to model reduction for stochastic reaction networks is known. In this paper we show that most common model reduction approaches for the Chemical Master Equation can be seen as minimising a well-known information-theoretic quantity between the full model and its reduction\, the Kullback-Leibler divergence defined on the space of trajectories. This allows us to recast the task of model reduction as a variational problem that can be tackled using standard numerical optimisation approaches. In addition we derive general expressions for the propensities of a reduced system that generalise those found using classical methods. We show that the Kullback-Leibler divergence is a useful metric to assess model discrepancy and to compare different model reduction techniques using three examples from the literature: an autoregulatory feedback loop\, the Michaelis-Menten enzyme system and a genetic oscillator.
URL:https://www.ibs.re.kr/bimag/event/2022-11-04-jc/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20221028T140000
DTEND;TZID=Asia/Seoul:20221028T160000
DTSTAMP:20260424T062821
CREATED:20220930T035148Z
LAST-MODIFIED:20221027T083230Z
UID:6646-1666965600-1666972800@www.ibs.re.kr
SUMMARY:Inferring microenvironmental regulation of gene expression from single-cell RNA sequencing data using scMLnet with an application to COVID-19
DESCRIPTION:We will discuss about “Inferring microenvironmental regulation of gene expression from single-cell RNA sequencing data using scMLnet with an application to COVID-19”\, Cheng\, Jinyu\, et al.\, Briefings in bioinformatics 22.2 (2021): 988-1005. \nAbstract: \nInferring how gene expression in a cell is influenced by cellular microenvironment is of great importance yet challenging. In this study\, we present a single-cell RNA-sequencing data based multilayer network method (scMLnet) that models not only functional intercellular communications but also intracellular gene regulatory networks (https://github.com/SunXQlab/scMLnet). scMLnet was applied to a scRNA-seq dataset of COVID-19 patients to decipher the microenvironmental regulation of expression of SARS-CoV-2 receptor ACE2 that has been reported to be correlated with inflammatory cytokines and COVID-19 severity. The predicted elevation of ACE2 by extracellular cytokines EGF\, IFN-γ or TNF-α were experimentally validated in human lung cells and the related signaling pathway were verified to be significantly activated during SARS-COV-2 infection. Our study provided a new approach to uncover inter-/intra-cellular signaling mechanisms of gene expression and revealed microenvironmental regulators of ACE2 expression\, which may facilitate designing anti-cytokine therapies or targeted therapies for controlling COVID-19 infection. In addition\, we summarized and compared different methods of scRNA-seq based inter-/intra-cellular signaling network inference for facilitating new methodology development and applications.
URL:https://www.ibs.re.kr/bimag/event/2022-10-28-jc/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
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:20260424T062821
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:20221021T150000
DTEND;TZID=Asia/Seoul:20221021T170000
DTSTAMP:20260424T062821
CREATED:20220930T035045Z
LAST-MODIFIED:20221019T070546Z
UID:6641-1666364400-1666371600@www.ibs.re.kr
SUMMARY:Rhythmicity is linked to expression cost at the protein level but to expression precision at the mRNA level
DESCRIPTION:We will discuss about “Rhythmicity is linked to expression cost at the protein level but to expression precision at the mRNA level”\, David Laloum\, and Marc Robinson-Rechavi\, PLoS computational biology 18.9 (2022): e1010399. \nAbstract: \nMany genes have nycthemeral rhythms of expression\, i.e. a 24-hours periodic variation\, at either mRNA or protein level or both\, and most rhythmic genes are tissue-specific. Here\, we investigate and discuss the evolutionary origins of rhythms in gene expression. Our results suggest that rhythmicity of protein expression could have been favored by selection to minimize costs. Trends are consistent in bacteria\, plants and animals\, and are also supported by tissue-specific patterns in mouse. Unlike for protein level\, cost cannot explain rhythm at the RNA level. We suggest that instead it allows to periodically reduce expression noise. Noise control had the strongest support in mouse\, with limited evidence in other species. We have also found that genes under stronger purifying selection are rhythmically expressed at the mRNA level\, and we propose that this is because they are noise sensitive genes. Finally\, the adaptive role of rhythmic expression is supported by rhythmic genes being highly expressed yet tissue-specific. This provides a good evolutionary explanation for the observation that nycthemeral rhythms are often tissue-specific.
URL:https://www.ibs.re.kr/bimag/event/2022-10-21-jc/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
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:20260424T062821
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:20260424T062821
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:20260424T062821
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:20260424T062821
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
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220930T150000
DTEND;TZID=Asia/Seoul:20220930T160000
DTSTAMP:20260424T062821
CREATED:20220830T012122Z
LAST-MODIFIED:20220830T012141Z
UID:6531-1664550000-1664553600@www.ibs.re.kr
SUMMARY:Absolute concentration robustness in networks with low-dimensional stoichiometric subspace
DESCRIPTION:We will discuss about “Absolute concentration robustness in networks with low-dimensional stoichiometric subspace”\, Meshkat\, Nicolette\, Anne Shiu\, and Angelica Torres.\, Vietnam Journal of Mathematics 50.3 (2022): 623-651. \nAbstract: \nA reaction system exhibits “absolute concentration robustness” (ACR) in some species if the positive steady-state value of that species does not depend on initial conditions. Mathematically\, this means that the positive part of the variety of the steady-state ideal lies entirely in a hyperplane of the form xi = c\, for some c > 0. Deciding whether a given reaction system – or those arising from some reaction network – exhibits ACR is difficult in general\, but here we show that for many simple networks\, assessing ACR is straightforward. Indeed\, our criteria for ACR can be performed by simply inspecting a network or its standard embedding into Euclidean space. Our main results pertain to networks with many conservation laws\, so that all reactions are parallel to one other. Such “one-dimensional” networks include those networks having only one species. We also consider networks with only two reactions\, and show that ACR is characterized by a well-known criterion of Shinar and Feinberg. Finally\, up to some natural ACR-preserving operations – relabeling species\, lengthening a reaction\, and so on – only three families of networks with two reactions and two species have ACR. Our results are proven using algebraic and combinatorial techniques. \n 
URL:https://www.ibs.re.kr/bimag/event/2022-09-30-jc/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220927T160000
DTEND;TZID=Asia/Seoul:20220927T170000
DTSTAMP:20260424T062821
CREATED:20220920T065117Z
LAST-MODIFIED:20220920T080942Z
UID:6633-1664294400-1664298000@www.ibs.re.kr
SUMMARY:Causal Inference – basics and examples
DESCRIPTION:Abstract: \nIn real world\, people are interested in causality rather than association. For example\, pharmaceutical companies want to know effectiveness of their new drugs against diseases. South Korea Government officials are concerned about the effects of recent regulation with respect to an electric car subsidy from United States. Due to this reason\, causal inference has been received much attention in decades and it is now a big research field in statistics. In this seminar\, I will talk about basic idea and theory in the causal inference. Real data examples will be discussed.
URL:https://www.ibs.re.kr/bimag/event/2022-09-27-seminar/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Biomedical Mathematics Seminar
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220923T150000
DTEND;TZID=Asia/Seoul:20220923T160000
DTSTAMP:20260424T062821
CREATED:20220830T011634Z
LAST-MODIFIED:20220922T011820Z
UID:6529-1663945200-1663948800@www.ibs.re.kr
SUMMARY:Cell clustering for spatial transcriptomics data with graph neural networks
DESCRIPTION:We will discuss about “Cell clustering for spatial transcriptomics data with graph neural networks”\, Li\, J.\, Chen\, S.\, Pan\, X. et al.\, Nat Comput Sci 2\, 399–408 (2022) \nAbstract: \nSpatial transcriptomics data can provide high-throughput gene expression profiling and the spatial structure of tissues simultaneously. Most studies have relied on only the gene expression information but cannot utilize the spatial information efficiently. Taking advantage of spatial transcriptomics and graph neural networks\, we introduce cell clustering for spatial transcriptomics data with graph neural networks\, an unsupervised cell clustering method based on graph convolutional networks to improve ab initio cell clustering and discovery of cell subtypes based on curated cell category annotation. On the basis of its application to five in vitro and in vivo spatial datasets\, we show that cell clustering for spatial transcriptomics outperforms other spatial clustering approaches on spatial transcriptomics datasets and can clearly identify all four cell cycle phases from multiplexed error-robust fluorescence in situ hybridization data of cultured cells. From enhanced sequential fluorescence in situ hybridization data of brain\, cell clustering for spatial transcriptomics finds functional cell subtypes with different micro-environments\, which are all validated experimentally\, inspiring biological hypotheses about the underlying interactions among the cell state\, cell type and micro-environment. \n  \n 
URL:https://www.ibs.re.kr/bimag/event/2022-09-23/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220919T133000
DTEND;TZID=Asia/Seoul:20220919T140000
DTSTAMP:20260424T062821
CREATED:20220904T124842Z
LAST-MODIFIED:20220904T124842Z
UID:6555-1663594200-1663596000@www.ibs.re.kr
SUMMARY:Design frameworks for engineering efficient cell factory performance within host and industrial constraints
DESCRIPTION:This talk will be given online. \nAbstract: \nSynthetic biology and microbial biotechnology offer sustainable routes to the manufacture of commodity and high value chemicals from agricultural by-products instead of petrochemical feedstocks. However\, engineered gene circuits and metabolic pathways both co-opt the cell’s gene expression machinery for protein/enzyme production and divert metabolic flux away from key host biosynthetic building blocks to a desired product. These interactions impair host growth and complicate the engineering of synthetic functions. To overcome these difficulties\, we propose a host-aware engineering approach which accounts for these constraints during the circuit/pathway design process. Here we present a dynamic whole cell modelling framework of microbial growth\, metabolism\, and gene expression which captures key host-circuit/pathway interactions. By coupling our modelling framework with systems engineering approaches and multi-objective optimization tools\, we identify key design trade-offs\, make recommendations for optimal host resource usage\, and develop feedback control strategies which improve pathway productivity and yields.
URL:https://www.ibs.re.kr/bimag/event/2022-09-19-seminar-2/
LOCATION:Daejeon
CATEGORIES:Biomedical Mathematics Seminar
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220919T130000
DTEND;TZID=Asia/Seoul:20220919T133000
DTSTAMP:20260424T062821
CREATED:20220904T124617Z
LAST-MODIFIED:20220904T125510Z
UID:6552-1663592400-1663594200@www.ibs.re.kr
SUMMARY:STEM Initiatives for Agricultural 4.0 and Beyond
DESCRIPTION:This talk will be given online. \nAbstract: \nThe establishment of UN Sustainable Development Goals (SDG) has led to widespread initiative in STEM learning and research in realising these goals. Here\, we will look at some of the works that use control engineering approaches for smart farming (also known as Agriculture 4.0) applications that addresses UN SDG Goal No. 2 – ZERO HUNGER. The tools developed have tremendous potential in optimising conditions required for enhanced crop efficiency and productivity for Agriculture 4.0.
URL:https://www.ibs.re.kr/bimag/event/2022-09-19-seminar-1/
LOCATION:Daejeon
CATEGORIES:Biomedical Mathematics Seminar
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220916T110000
DTEND;TZID=Asia/Seoul:20220916T120000
DTSTAMP:20260424T062821
CREATED:20220825T190000Z
LAST-MODIFIED:20220905T053032Z
UID:6351-1663326000-1663329600@www.ibs.re.kr
SUMMARY:Physics-informed neural networks for PDE-constrained optimization and control
DESCRIPTION:We will discuss about “Physics-informed neural networks for PDE-constrained optimization and control”\, Barry-Straume\, Jostein\, et al.\, arXiv preprint arXiv:2205.03377 (2022). \nAbstract: A fundamental problem of science is designing optimal control policies that manipulate a given environment into producing a desired outcome. Control PhysicsInformed Neural Networks simultaneously solve a given system state\, and its respective optimal control\, in a one-stage framework that conforms to physical laws of the system. Prior approaches use a two-stage framework that models and controls a system sequentially\, whereas Control PINNs incorporates the required optimality conditions in its architecture and loss function. The success of Control PINNs is demonstrated by solving the following open-loop optimal control problems: (i) an analytical problem (ii) a one-dimensional heat equation\, and (iii) a two-dimensional predator-prey problem.
URL:https://www.ibs.re.kr/bimag/event/2022-09-16-jc/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220902T150000
DTEND;TZID=Asia/Seoul:20220902T160000
DTSTAMP:20260424T062821
CREATED:20220817T042800Z
LAST-MODIFIED:20220828T171528Z
UID:6398-1662130800-1662134400@www.ibs.re.kr
SUMMARY:Hidden Markov models for monitoring circadian rhythmicity in telemetric activity data
DESCRIPTION:We will discuss about “Hidden Markov models for monitoring circadian rhythmicity in telemetric activity data”\, Huang\, Qi\, Journal of The Royal Society Interface 15.139 (2018): 20170885. \nAbstract: Wearable computing devices allow collection of densely sampled real-time information on movement enabling researchers and medical experts to obtain objective and non-obtrusive records of actual activity of a subject in the real world over many days. Our interest here is motivated by the use of activity data for evaluating and monitoring the circadian rhythmicity of subjects for research in chronobiology and chronotherapeutic healthcare. In order to translate the information from such high-volume data arising we propose the use of a Markov modelling approach which (i) naturally captures the notable square wave form observed in activity data along with heterogeneous ultradian variances over the circadian cycle of human activity\, (ii) thresholds activity into different states in a probabilistic way while respecting time dependence and (iii) gives rise to circadian rhythm parameter estimates\, based on probabilities of transitions between rest and activity\, that are interpretable and of interest to circadian research.
URL:https://www.ibs.re.kr/bimag/event/2022-09-02-jc/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
END:VCALENDAR