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PRODID:-//Biomedical Mathematics Group - ECPv6.16.2//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Biomedical Mathematics Group
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:20230530T160000
DTEND;TZID=Asia/Seoul:20230530T170000
DTSTAMP:20260522T063019
CREATED:20230524T125426Z
LAST-MODIFIED:20230524T125651Z
UID:7788-1685462400-1685466000@www.ibs.re.kr
SUMMARY:Trivial but not trivial things in data science: From a statistical perspective
DESCRIPTION:TBA
URL:https://www.ibs.re.kr/bimag/event/t/
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:20230525T110000
DTEND;TZID=Asia/Seoul:20230525T120000
DTSTAMP:20260522T063019
CREATED:20230522T134427Z
LAST-MODIFIED:20230522T134449Z
UID:7767-1685012400-1685016000@www.ibs.re.kr
SUMMARY:Nonparametric predictive model for sparse and irregular longitudinal data
DESCRIPTION:We propose a kernel-based estimator to predict the mean response trajectory for sparse and irregularly measured longitudinal data. The kernel estimator is constructed by imposing weights based on the subject-wise similarity on L2 metric space between predictor trajectories\, where we assume that an analogous fashion in predictor trajectories over time would result in a similar trend in the response trajectory among subjects. In order to deal with the curse of dimensionality caused by the multiple predictors\, we propose an appealing multiplicative model with multivariate Gaussian kernels. This model is capable of achieving dimension reduction as well as selecting functional covariates with predictive significance. The asymptotic properties of the proposed nonparametric estimator are investigated under mild regularity conditions. We illustrate the robustness and flexibility of our proposed method via the simulation study and an application to Framingham Heart Study
URL:https://www.ibs.re.kr/bimag/event/2023-05-25-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:20230522T120000
DTEND;TZID=Asia/Seoul:20230522T130000
DTSTAMP:20260522T063019
CREATED:20230509T062709Z
LAST-MODIFIED:20230509T062709Z
UID:7730-1684756800-1684760400@www.ibs.re.kr
SUMMARY:Pan Li\, Modeling the circadian control of cardiac function
DESCRIPTION:Abstract: TBA
URL:https://www.ibs.re.kr/bimag/event/pan-li-modeling-the-circadian-control-of-cardiac-function/
LOCATION: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:20230508T160000
DTEND;TZID=Asia/Seoul:20230508T170000
DTSTAMP:20260522T063019
CREATED:20230425T045600Z
LAST-MODIFIED:20230425T045600Z
UID:7637-1683561600-1683565200@www.ibs.re.kr
SUMMARY:Kyongwon Kim\, On sufficient graphical models
DESCRIPTION:We introduce a sufficient graphical model by applying the recently developed nonlinear sufficient dimension reduction techniques to the evaluation of conditional independence. The graphical model is nonparametric in nature\, as it does not make distributional assumptions such as the Gaussian or copula Gaussian assumptions. However\, unlike a fully nonparametric graphical model\, which relies on the high-dimensional kernel to characterize conditional independence\,  our graphical model is based on conditional independence given a set of sufficient predictors with a substantially reduced dimension. In this way we avoid the curse of dimensionality that comes with a high-dimensional kernel. We develop the population-level properties\,  convergence rate\, and variable selection consistency of our estimate. \nBy simulation comparisons and an analysis of the DREAM 4 Challenge data set\, we demonstrate that our method outperforms the existing methods when the Gaussian or copula Gaussian assumptions are violated\, and its performance remains excellent in the high-dimensional setting.
URL:https://www.ibs.re.kr/bimag/event/kyongwon-kim-on-sufficient-graphical-models/
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:20230504T161500
DTEND;TZID=Asia/Seoul:20230504T171500
DTSTAMP:20260522T063019
CREATED:20230409T053139Z
LAST-MODIFIED:20230414T024516Z
UID:7585-1683216900-1683220500@www.ibs.re.kr
SUMMARY:Uncovering the mechanisms of pattern formation and emergent collective behaviors in myxobacteria
DESCRIPTION:Collective cell movement is critical to the emergent properties of many multicellular systems including microbial self-organization in biofilms\, wound healing\, and cancer metastasis. However\, even the best-studied systems lack a complete picture of how diverse physical and chemical cues act upon individual cells to ensure coordinated multicellular behavior. Myxococcus xanthus is a model bacteria famous for its coordinated multicellular behavior resulting in dynamic patterns formation. For example\, when starving millions of cells coordinate their movement to organize into fruiting bodies – aggregates containing tens of thousands of bacteria. Relating these complex self-organization patterns to the behavior of individual cells is a complex-reverse engineering problem that cannot be solved solely by experimental research. In collaboration with experimental colleagues\, we use a combination of quantitative microscopy\, image processing\, agent-based modeling\, and kinetic theory PDEs to uncover the mechanisms of emergent collective behaviors.
URL:https://www.ibs.re.kr/bimag/event/understanding-trade-offs-in-biological-information-processing/
LOCATION:KAIST E6-1 1501 Auditorium\, 291 Daehak-ro\, Yuseong-gu\, Daejeon\, 34141\, 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:20230501T160000
DTEND;TZID=Asia/Seoul:20230501T170000
DTSTAMP:20260522T063019
CREATED:20230409T052337Z
LAST-MODIFIED:20230414T024627Z
UID:7582-1682956800-1682960400@www.ibs.re.kr
SUMMARY:Understanding Trade-offs in Biological Information Processing
DESCRIPTION:High accuracy of major biological processes relies on the ability of the participating enzymatic molecules to preferentially select the correct substrate from a pool of chemically similar substrates by activating the so-called proofreading mechanisms. While the importance of such mechanisms is widely accepted\, it is still unclear how evolution has optimized biological systems with respect to their characteristic properties. We developed a comprehensive first-passage theoretical framework that allowed us to quantitatively investigate the trade-offs between the three properties of enzymatic systems: error\, speed\, noise\, and energy dissipation. Within this framework\, we simultaneously analyzed the speed and accuracy of several fundamental biological processes\, including DNA replication\, transcription\, tRNA charging\, and tRNA selection during the translation. The results indicate that the speed-accuracy trade-off is not always observed contrary to typical assumptions. However\, when the trade-off is present\, the biological systems tend to optimize the speed rather than the accuracy of the processes\, as long as the error level is tolerable. When systems function in a regime where no speed-accuracy trade-off is observed\, constraints due to energy dissipation in the proofreading play a key role. Our theory demonstrates a universal Pareto front in error-dissipation trade-off and shows how naturally selected kinetic parameters position their system close to this boundary. Our findings\, therefore\, provide a new system-level picture of how complex biological processes are able to function so fast with high accuracy and low dissipation.
URL:https://www.ibs.re.kr/bimag/event/uncovering-the-mechanisms-of-pattern-formation-and-emergent-collective-behaviors-in-myxobacteria/
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:20230327T160000
DTEND;TZID=Asia/Seoul:20230327T170000
DTSTAMP:20260522T063019
CREATED:20230323T064118Z
LAST-MODIFIED:20230323T064136Z
UID:7536-1679932800-1679936400@www.ibs.re.kr
SUMMARY:Sungwoong Cho\, HyperDeepONet: learning operator with complex target function space using the limited resources via hypernetwork
DESCRIPTION:Fast and accurate predictions for complex physical dynamics are a big challenge across various applications. Real-time prediction on resource-constrained hardware is even more crucial in the real-world problems. The deep operator network (DeepONet) has recently been proposed as a framework for learning nonlinear mappings between function spaces. However\, the DeepONet requires many parameters and has a high computational cost when learning operators\, particularly those with complex (discontinuous or non-smooth) target functions. In this study\, we propose HyperDeepONet\, which uses the expressive power of the hypernetwork to enable learning of a complex operator with smaller set of parameters. The DeepONet and its variant models can be thought of as a method of injecting the input function information into the target function. From this perspective\, these models can be viewed as a special case of HyperDeepONet. We analyze the complexity of DeepONet and conclude that HyperDeepONet needs relatively lower complexity to obtain the desired accuracy for operator learning. HyperDeepONet was successfully applied to various operator learning problems using low computational resources compared to other benchmarks.
URL:https://www.ibs.re.kr/bimag/event/2023-03-27-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:20230320T110000
DTEND;TZID=Asia/Seoul:20230320T120000
DTSTAMP:20260522T063019
CREATED:20230316T004827Z
LAST-MODIFIED:20230316T004827Z
UID:7493-1679310000-1679313600@www.ibs.re.kr
SUMMARY:Marko Ćosić\, Stewart’s Catastrophic Swing
DESCRIPTION:Abstract\nThe standard approach to problem-solving in physics consists of identifying state variables of the system\, setting differential equations governing the state evolution\, and solving the obtained. The behavior of the system for different values of parameters can be examined only as a fourth step. On the contrary\, the modern approach to studying dynamical systems relies on Morphological/Topological analysis which alleviates the necessity for the explicit solution of differential equations. \nThe stability analysis of the parabolic swing will demonstrate the merit of such an approach. It will be shown how to construct a qualitatively correct model of system dynamics that is surprisingly quantitatively correct as well. The sudden (catastrophic) change in the swing’s stability\, caused by a slight change in the critical value of system parameters\, will be linked to the drastic topological change of the corresponding phase-space portraits. \nIt will be shown that for a system’s parameters close to critical ones\, the system’s behavior is identical to a specific simple universal prototype given by catastrophe theory. A short survey of the simplest elementary catastrophes will be given that represents the basis for applying catastrophe theory in other fields of science.
URL:https://www.ibs.re.kr/bimag/event/marko-cosic-stewarts-catastrophic-swing/
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:20230313T110000
DTEND;TZID=Asia/Seoul:20230313T120000
DTSTAMP:20260522T063019
CREATED:20230310T010131Z
LAST-MODIFIED:20230310T010131Z
UID:7445-1678705200-1678708800@www.ibs.re.kr
SUMMARY:Marko Ćosić\, The morphological analysis of the collagen straightness in the colon mucosa away from the cancer
DESCRIPTION:Abstract: The morphological method – based on the topology and singularity theory and originally developed for the analysis of the scattering experiments – was extended to be applicable for the analysis of biological data. The usefulness of the topological viewpoint was demonstrated by quantification of the changes of collagen fiber straightness in the human colon mucosa (healthy mucosa\, colorectal cancer\, and uninvolved mucosa far from cancer).\nThis has been done by modeling the distribution of collagen segment angles by the polymorphic beta-distribution. Its shapes were classified according to the number and type of critical points. We found that biologically relevant shapes could be classified as shapes without any preferable orientation (i.e. shapes without local extrema)\, transitional forms (i.e. forms with one broad local maximum)\, and highly oriented forms (i.e. forms with two minima at both ends and one very narrow maximum between them). Thus\, changes in the fiber organization were linked to the metamorphoses of the beta-distribution forms.\nThe obtained classification was used to define a new\, shape-aware/based\, measure of the collagen straightness\, which revealed a slight\, and moderate increase of the straightness in mucosa samples taken 20 cm and 10 cm away from the tumor. The largest increase of collagen straightness was found in samples of cancer tissue. Samples of the healthy individuals have a uniform distribution of beta-distribution forms. We found that this distribution has the maximal information entropy. At 20 cm and 10 cm away from cancer\, the transition forms redistribute into unoriented and highly oriented forms. Closer to cancer the number of unoriented forms decreases rapidly leaving only highly oriented forms present in the samples of the cancer tissue\, whose distribution has minimal information entropy. The polarization of the distribution was followed by a significant increase in the number of quasi-symmetrical forms in samples 20 cm away from cancer which decreases closer to cancer.\nThis work shows that the evolution of the distribution of the beta-distribution forms – an abstract construction of the mind – follows the familiar laws of statistical mechanics. Additionally\, the polarization of the beta-distribution forms together with the described change in the number of quasi-symmetrical forms\, clearly visible in the parametric space of the beta-distribution and very difficult to notice in the observable space\, can be a useful indicator of the early stages in the development of colorectal cancer.
URL:https://www.ibs.re.kr/bimag/event/marko-cosic-the-morphological-analysis-of-the-collagen-straightness-in-the-colon-mucosa-away-from-the-cancer/
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:20230119T100000
DTEND;TZID=Asia/Seoul:20230119T110000
DTSTAMP:20260522T063019
CREATED:20230109T090635Z
LAST-MODIFIED:20230109T090635Z
UID:7229-1674122400-1674126000@www.ibs.re.kr
SUMMARY:Jong-Eun Park\, Single-cell analysis reveals recurring programs in cancer microenvironment
DESCRIPTION:Complexity of the cellular organization of the tumor microenvironment as an ecosystem remains to be fully appreciated. Here\, for a comprehensive investigation of tumor ecosystems across a wide variety of cancer types\, we performed integrative transcriptome analyses of 4.4 million single cells from 978 tumor and 474 normal samples in combination with 9\,510 TCGA and 1\,339 checkpoint inhibitor-treated bulk tumors. Our analysis enabled us to define 28 different epithelial cell states\, some of which had prognostic effects in cancers of relevant origin. Malignant fibroblast signatures defined according to the organ of origin demonstrated prognostic significance across diverse cancer types and revealed FN1\, BGN\, THBS2\, and CTHRC1 as common cancer-associated fibroblast genes. Novel associations were revealed between the AKR1C1+ inflammatory fibroblast and myeloid-derived PRR-induced activation states and between the CXCL10+ fibroblast and squamous/LAMP3+ DC/SPP1+ macrophage states. We discovered tumor-specific rewiring of the tertiary lymphoid structure (TLS) network\, involving previously unappreciated DC1\, and pDC.. Along with other TLS component states\, the tumor-associated germinal center B cell state identified from adjacent normal tissues was able to predict responses to checkpoint immunotherapy. Distinct groups of pan-cancer ecosystems were identified and characterized along the axis of immunotherapy responses. Our systematic\, high-resolution dissection of tumor ecosystems provides a deeper understanding of inter- and intra-tumoral heterogeneity.
URL:https://www.ibs.re.kr/bimag/event/jong-eun-park-single-cell-analysis-reveals-recurring-programs-in-cancer-microenvironment/
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:20221228T140000
DTEND;TZID=Asia/Seoul:20221228T150000
DTSTAMP:20260522T063019
CREATED:20221215T221715Z
LAST-MODIFIED:20221222T082709Z
UID:7043-1672236000-1672239600@www.ibs.re.kr
SUMMARY:Ji Won Oh\, From Grave to Cradle: Human Somatic Mosaicism and Unsolved Questions
DESCRIPTION:사람이 어떻게 만들어지고 각 기관이 어떻게 발달하는지에 대한 질문은 아주 오래전부터 있었습니다. 체외수정(IVF)의 고유의 장점으로 인해 과학자들이 수정란을 외부에서 관찰할 수 있게 되었습니다. 하지만\, 1979년도에 제정된 14일 규정(the 14-day rule)으로 인해\, 수정 후 최대 14일까지의 배아 만의 연구가 가능합니다. 따라서\, 이 14일 규정은 발생 생물학자들이 사람 발생학 연구에 있어서 수정 후 2주 이상(신경계 발달\, 기관 형성 등)에 나타나는 현상을 연구하고자 할 경우 다른 방향을 모색할 수밖에 없게 되었습니다. 본 연구는 이 지점에서부터 시작합니다. 연구진들은 세포 분열 때 우연히 발생하는 생리학적 체세포 변이(Post-zygotic Variants)를 추적하여 각 세포들의 운명을 재구성하였습니다. 특히 사망 후 기증된 시신에서 단일 세포를 배양하고\, 최근 개발된 차세대 염기서열 분석 기술을 사용하여 인간 발생 연구의 후향적 혈통 추적(Retrospective Lineage Tracing)을 수행하는 과정을 발표하고자 합니다. 이번 발표를 통해서 이런 방법론이 어떻게 가능했는지에 대한 생물학적 및 과학적 배경과 인간 발생학의 미래에서 해결해야 할 과제와 가설을 강조할 예정입니다. 추가로\, 이 과정에서 필요한 수학적인 해석이 필요한 질문들에 대해서도 논의할 예정입니다. 여러분들의 참신한 시각과 질문을 크게 환영합니다. \n\n\n\n\n1) Park\, S.\, Mali\, N.M.\, Kim\, R. et al. Clonal dynamics in early human embryogenesis inferred from somatic mutation. Nature 597\, 393–397 (2021). https://doi.org/10.1038/s41586-021-03786-8 \n2) Kwon\, S.G.\, Bae\, G.H.\, Choi\, J.H. et al. Asymmetric Contribution of Blastomere Lineages of First Division of the Zygote to Entire Human Body Using Post-Zygotic Variants. Tissue Eng Regen Med 19\, 809–821 (2022). https://doi.org/10.1007/s13770-022-00443-7
URL:https://www.ibs.re.kr/bimag/event/from-grave-to-cradle-human-somatic-mosaicism-and-unsolved-questions/
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:20221213T160000
DTEND;TZID=Asia/Seoul:20221213T170000
DTSTAMP:20260522T063019
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:20221109T140000
DTEND;TZID=Asia/Seoul:20221109T150000
DTSTAMP:20260522T063019
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:20260522T063019
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:20220927T160000
DTEND;TZID=Asia/Seoul:20220927T170000
DTSTAMP:20260522T063019
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:20220919T133000
DTEND;TZID=Asia/Seoul:20220919T140000
DTSTAMP:20260522T063019
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/
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:20260522T063019
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/
CATEGORIES:Biomedical Mathematics Seminar
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220816T100000
DTEND;TZID=Asia/Seoul:20220816T110000
DTSTAMP:20260522T063019
CREATED:20220815T160000Z
LAST-MODIFIED:20220815T124820Z
UID:6376-1660644000-1660647600@www.ibs.re.kr
SUMMARY:Circadian Interventions in Shift Workers
DESCRIPTION:This talk will be given online (If you want to join\, please send me an email to jaekkim@ibs.re.kr) \nAbstract \nCoupling Math with User-Centric Design Shift workers experience profound circadian disruption due to the nature of their work\, which often has them on-the-clock at times when their internal clock is sending a strong\, sleep-promoting signal. Mathematical models can be used to generate recommendations for shift workers that move their internal clock state to better align with their work schedules\, promote overall sleep\, promote alertness at key times\, or achieve other desired outcomes. Yet for these schedules to have a positive effect in the real world\, they need to be acceptable to the shift workers themselves. In this talk\, I will survey the types of schedules a shift worker may be recommended by an algorithm\, and how they can collide with the preferences of the real people being asked to follow them\, and how math can be used to arrive at new schedules that take these human factors into account.
URL:https://www.ibs.re.kr/bimag/event/2022-08-16-seminar/
CATEGORIES:Biomedical Mathematics Seminar
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220705T160000
DTEND;TZID=Asia/Seoul:20220705T170000
DTSTAMP:20260522T063019
CREATED:20220704T220000Z
LAST-MODIFIED:20220625T051518Z
UID:6240-1657036800-1657040400@www.ibs.re.kr
SUMMARY:TENET+: a tool for reconstructing gene networks by integrating single cell expression and chromatin accessibility data
DESCRIPTION:Reconstruction of gene regulatory networks (GRNs) is a powerful approach to capture a prioritized gene set controlling cellular processes. In our previous study\, we developed TENET a GRN reconstructor from single cell RNA sequencing (scRNAseq). TENET has a superior capability to identify key regulators compared with other algorithms. However\, accurate inference of gene regulation is still challenging. Here\, we suggest an integrative strategy called TENET+ by combining single cell transcriptome and chromatin accessibility data. By applying TENET+ to a paired scRNAseq and scATACseq dataset of human peripheral blood mononuclear cells\, we found critical regulators and their epigenetic regulations for the differentiations of CD4 T cells\, CD8 T cells\, B cells and monocytes. Interestingly\, TENET+ predicted LRRFIP1 and ZBTB16 as top regulators of CD4 and CD8 T cells which were not predicted in a motif-based tool SCENIC. In sum\, TENET+ is a tool predicting epigenetic gene regulatory programs in unbiased way\, suggesting that novel epigenetic regulations can be identified by TENET+.
URL:https://www.ibs.re.kr/bimag/event/2022-07-05-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:20220616T160000
DTEND;TZID=Asia/Seoul:20220616T170000
DTSTAMP:20260522T063019
CREATED:20220613T130628Z
LAST-MODIFIED:20220613T130628Z
UID:6180-1655395200-1655398800@www.ibs.re.kr
SUMMARY:Deep Learning-based Uncertainty Quantification for Mathematical Models
DESCRIPTION:Over the recent years\, various methods based on deep neural networks have been developed and utilized in a wide range of scientific fields. Deep neural networks are highly suitable for analyzing time series or spatial data with complicated dependence structures\, making them particularly useful for environmental sciences and biosciences where such type of simulation model output and observations are prevalent. In this talk\, I will introduce my recent efforts in utilizing various deep learning methods for statistical analysis of mathematical simulations and observational data in those areas\, including surrogate modeling\, parameter estimation\, and long-term trend reconstruction. Various scientific application examples will also be discussed\, including ocean diffusivity estimation\, WRF-hydro calibration\, AMOC reconstruction\, and SIR calibration.  
URL:https://www.ibs.re.kr/bimag/event/2022-06-13-seminar-wonchang/
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:20220615T160000
DTEND;TZID=Asia/Seoul:20220615T170000
DTSTAMP:20260522T063019
CREATED:20220613T144731Z
LAST-MODIFIED:20220613T144731Z
UID:6188-1655308800-1655312400@www.ibs.re.kr
SUMMARY:Optimized persistent random walk in zebrafish airineme search process
DESCRIPTION:In addition to diffusive signals\, cells in tissue also communicate via long\, thin cellular protrusions\, such as airinemes in zebrafish. Before establishing communication\, cellular protrusions must find their target cell. In this talk\, we demonstrate that the shapes of airinemes in zebrafish are consistent with a persistent random walk model. The probability of contacting the target cell is maximized for a balance between ballistic search (straight) and diffusive search (highly curved\, random). We find that the curvature of airinemes in zebrafish\, extracted from live cell microscopy\, is approximately the same value as the optimum in the simple persistent random walk model. We also explore the ability of the target cell to infer direction of the airineme’s source\, finding that there is a theoretical trade-off between search optimality and directional information. This provides a framework to characterize the shape\, and performance objectives\, of non-canonical cellular protrusions in general.
URL:https://www.ibs.re.kr/bimag/event/2022-06-15-seminar-hjkim/
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:20220613T160000
DTEND;TZID=Asia/Seoul:20220613T170000
DTSTAMP:20260522T063019
CREATED:20220612T220000Z
LAST-MODIFIED:20220529T114627Z
UID:6088-1655136000-1655139600@www.ibs.re.kr
SUMMARY:Dynamical System Perspective for Machine Learning
DESCRIPTION:Abstract: The connection between deep neural networks and ordinary differential equations (ODEs) is an active field of research in machine learning. In this talk\, we view the hidden states of a neural network as a continuous object governed by a dynamical system. The underlying vector field is written using a dictionary representation motivated by the equation discovery method. Within this framework\, we develop models for two particular machine learning tasks: time-series classification and dimension reduction. We train the parameters in the models by minimizing a loss\, which is defined using the solution to the governing ODE. To attain a regular vector field\, we introduce a regularization term measuring the mean total kinetic energy of the flow\, which is motivated by optimal transportation theory. We solve the optimization problem using a gradient-based method where the gradients are computed via the adjoint method from optimal control theory. Through various experiments on synthetic and real-world datasets\, we demonstrate the performance of the proposed models. We also interpret the learned models by visualizing the phase plots of the underlying vector field and solution trajectories.  \n 
URL:https://www.ibs.re.kr/bimag/event/2022-06-13-sem/
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:20220610T130000
DTEND;TZID=Asia/Seoul:20220610T140000
DTSTAMP:20260522T063019
CREATED:20220530T075825Z
LAST-MODIFIED:20220530T075825Z
UID:6133-1654866000-1654869600@www.ibs.re.kr
SUMMARY:Phase Estimation of Nonlinear State-space Model of the Circadian Pacemaker Using Level Set Kalman Filter and Raw Wearable Data
DESCRIPTION:Abstract: \nCircadian rhythm is a robust internal 24 hours timekeeping mechanism maintained by the master circadian pacemaker Suprachiasmatic Nuclei (SCN). Numerous mathematical models have been proposed to capture SCN’s timekeeping mechanism and predict the circadian phase. There has been an increased demand for applying these models to the various unexplored data sets. One potential application is on data from commercially available wearable devices\, which provide the noninvasive measurements of physiological proxies\, such as activity and heart rate. Using these physiological proxies\, we can estimate the circadian phase of the central and peripheral circadian pacemakers. Here\, we propose a new framework for estimating the circadian phase using wearable data and the Level Set Kalman Filter on the nonlinear state-space model of the human circadian pacemaker. Analysis of over 200\,000 days of wearable data from over 3\,000 subjects using our framework successfully identified misalignment in central and peripheral pacemakers with a significantly smaller uncertainty than previous methods.
URL:https://www.ibs.re.kr/bimag/event/2022-06-10-sem/
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:20220602T160000
DTEND;TZID=Asia/Seoul:20220602T170000
DTSTAMP:20260522T063019
CREATED:20220520T122202Z
LAST-MODIFIED:20220520T122202Z
UID:6028-1654185600-1654189200@www.ibs.re.kr
SUMMARY:Introduction to matrix and tensor factorization models and related stochastic nonconvex and constrained optimization algorithms
DESCRIPTION:Abstract. Matrix/tensor factorization models such as principal component analysis \, nonnegative matrix factorization\, and CANDECOM/PARAFAC tensor decomposition provide powerful framework for dimension reduction and interpretable feature extraction\, which are important in analyzing high-dimensional data that comes in large volume. Their diverse applications include image denoising and reconstruction\, dictionary learning\, topic modeling\, and network data analysis. Fitting such factorization models to training data gives rise to various nonconvex and constrained optimization algorithms. Moreover\, such models can be trained efficiently for streaming data using stochastic/online versions of such algorithms. After introducing matrix/tensor factorization models and their applications in various contexts\, we survey some well-known nonconvex constrained optimization algorithms such as block coordinate descent and projected gradient descent. We also discuss some recent developments in general stochastic optimization algorithms such as stochastic proximal gradient descent and stochastic regularized majorization-minimization and their convergence and complexity guarantees under general Markovian streaming data.
URL:https://www.ibs.re.kr/bimag/event/2022-06-02-sem/
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:20220421T160000
DTEND;TZID=Asia/Seoul:20220421T170000
DTSTAMP:20260522T063019
CREATED:20220420T220000Z
LAST-MODIFIED:20220416T063046Z
UID:5864-1650556800-1650560400@www.ibs.re.kr
SUMMARY:Dynamical and topological hallmarks of regulatory networks driving phenotypic plasticity and heterogeneity in cancers
DESCRIPTION:This talk will be presented online. Zoom link: 997 8258 4700 (pw: 1234) \nAbstract: \nMetastasis and therapy resistance cause over 90% of cancer-related deaths. Despite extensive ongoing efforts\, no unique genetic or mutational signature has emerged for metastasis. Instead\, the ability of genetically identical cells to adapt reversibly by exhibiting multiple phenotypes (phenotypic/non-genetic heterogeneity) and switch among them (phenotypic plasticity) is proposed as a hallmark of metastasis. Also\, drug resistance can emerge from such non-genetic adaptive cellular changes. However\, the origins of such non-genetic heterogeneity in most cancers are poorly understood. I will present our findings on a) how non-genetic heterogeneity emerges in a population of cancer\, and b) what design principles underlie regulatory networks enabling non-genetic heterogeneity across multiple cancers. Our results unravel how systems-levels approaches integrating mechanistic mathematical modeling with in vitro and in vivo data can identify causes and consequences of such non-genetic heterogeneity.
URL:https://www.ibs.re.kr/bimag/event/2022-04-21/
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:20220208T113000
DTEND;TZID=Asia/Seoul:20220208T120000
DTSTAMP:20260522T063019
CREATED:20220208T173000Z
LAST-MODIFIED:20220207T064404Z
UID:5673-1644319800-1644321600@www.ibs.re.kr
SUMMARY:수리모델을 통한 전염병 통제 분석
DESCRIPTION:Abstract: TBA
URL:https://www.ibs.re.kr/bimag/event/2022-02-09-2/
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:20220208T110000
DTEND;TZID=Asia/Seoul:20220208T113000
DTSTAMP:20260522T063019
CREATED:20220208T170000Z
LAST-MODIFIED:20220207T064429Z
UID:5670-1644318000-1644319800@www.ibs.re.kr
SUMMARY:Stochastic Modeling of Foot and Mouth Diseases with Vehicle Network & Assessment of Social Distancing for Controlling COVID-19 in Korea
DESCRIPTION:Abstract: TBA
URL:https://www.ibs.re.kr/bimag/event/2022-02-09/
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:20220127T110000
DTEND;TZID=Asia/Seoul:20220127T130000
DTSTAMP:20260522T063019
CREATED:20220126T170000Z
LAST-MODIFIED:20220125T115708Z
UID:5507-1643281200-1643288400@www.ibs.re.kr
SUMMARY:Introduction to Bayesian Variable Selection.  
DESCRIPTION:Abstract:\nVariable selection is an approach to identifying a set of covariates that are truly important to explain the feature of a response variable. It is closely connected or belongs to model selection approaches. This talk provides a gentle introduction to Bayesian variable selection methods. The basic notion of variable selection is introduced\, followed by several Bayesian approaches with a simple application example.
URL:https://www.ibs.re.kr/bimag/event/2022-01-27-2/
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:20220118T160000
DTEND;TZID=Asia/Seoul:20220118T170000
DTSTAMP:20260522T063019
CREATED:20220117T220000Z
LAST-MODIFIED:20220115T115221Z
UID:5466-1642521600-1642525200@www.ibs.re.kr
SUMMARY:다중 오믹스 분야의 현황 및 유전자-환경 상호 모델링의 필요성 (Current status of multi-omics research field and necessity of gene-by-environment (GxE) interaction modeling)
DESCRIPTION:본 발표에서는 다양한 기초 생명-의학 분야에서 생성되고 있는 오믹스 자료의 연구 개발 현황에 대해서 다룰 예정이다. 보다 큰 규모로\, 보다 빠르게\, 보다 정확하게\, 보다 정밀하게 라는 궁극적인 목표하에 이뤄지고 있는 오믹스 자료의 진화에 발맞춰\, 이를 분석하는 수리통계적 모형 역시 진화하고 있다. 그 중\, 이번 발표에서는 미국의 초 대형 정밀의료 프로젝트인 TopMed에서 진행하고 있는 COPD에 관한 다중 오믹스 자료의 통합 분석 방법 및 결과에 대해서 자세히 다룰 예정이다. 아울러 정밀의료라는 목표를 달성하기 위해 반드시 모형에서 고려해야 하는 “환경 특이적 효과”에 대해 강연할 예정이다. \n 
URL:https://www.ibs.re.kr/bimag/event/2022-01-18/
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:20220106T160000
DTEND;TZID=Asia/Seoul:20220106T173000
DTSTAMP:20260522T063019
CREATED:20220105T220000Z
LAST-MODIFIED:20211224T001917Z
UID:5369-1641484800-1641490200@www.ibs.re.kr
SUMMARY:Structure-based analysis of chemical reaction networks 2/2
DESCRIPTION:Inside living cells\, chemical reactions form a large web of networks. Understanding the behavior of those complex reaction networks is an important and challenging problem. In many situations\, it is hard to identify the details of the reactions\, such as the reaction kinetics and parameter values. It would be good if we can clarify what we can say about the behavior of reaction systems\, when we know the structure of reaction networks but reaction kinetics is unknown. In these talks\, I plan to introduce two approaches in this spirit. Firstly\, we will discuss the sensitivity analysis of reaction systems based on the structural information of reaction networks [1]. I will give an introduction to the method of identifying subnetworks inside which the effects of the perturbation of reaction parameters are confined. Secondly\, I will introduce the reduction method that we developed recently [2]. In those two methods\, an integer determined by the topology of a subnetwork\, which we call an influence index\, plays a crucial role. \n[1] T. Okada\, A. Mochizuki\, “Law of Localization in Chemical Reaction Networks\,” Phys. Rev. Lett. 117\, 048101 (2016); T. Okada\, A. Mochizuki\, “Sensitivity and network topology in chemical reaction systems\,” Phys. Rev. E 96\, 022322 (2017). \n[2] Y. Hirono\, T. Okada\, H. Miyazaki\, Y. Hidaka\, “Structural reduction of chemical reaction networks based on topology”\, Phys. Rev. Research 3\, 043123 (2021).
URL:https://www.ibs.re.kr/bimag/event/2022-01-06/
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
END:VCALENDAR