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X-WR-CALNAME:Biomedical Mathematics Group
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:20200101T000000
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END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220106T160000
DTEND;TZID=Asia/Seoul:20220106T173000
DTSTAMP:20260424T214913
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
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220105T160000
DTEND;TZID=Asia/Seoul:20220105T173000
DTSTAMP:20260424T214913
CREATED:20220104T220000Z
LAST-MODIFIED:20211224T001927Z
UID:5366-1641398400-1641403800@www.ibs.re.kr
SUMMARY:Structure-based analysis of chemical reaction networks 1/2
DESCRIPTION:Abstract: 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. \nReferences \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/2022-01-05/
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:20220104T111000
DTEND;TZID=Asia/Seoul:20220104T120000
DTSTAMP:20260424T214913
CREATED:20220103T002320Z
LAST-MODIFIED:20220103T002320Z
UID:5432-1641294600-1641297600@www.ibs.re.kr
SUMMARY:Stem cell dynamics in the intestine and stomach
DESCRIPTION:In adult tissues\, stem cells undergo clonal competition because they proliferate while the stem cell niche provides limited space. This clonal competition allows the selection of healthy stem cells over time as unfit stem cells tend to lose from the competition. It could also be a mechanism to select a supercompetitor with tumorigenic mutations\, which may lead to tumorigenesis. I am going to explain general concepts of clonal competition and how a simple model can explain the behaviour of adult stem cells. I will also show how geometric constraints affect the overall dynamics of stem cell competition.
URL:https://www.ibs.re.kr/bimag/event/2022-01-03/
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:20211231T130000
DTEND;TZID=Asia/Seoul:20211231T140000
DTSTAMP:20260424T214913
CREATED:20211230T190000Z
LAST-MODIFIED:20211227T004211Z
UID:5306-1640955600-1640959200@www.ibs.re.kr
SUMMARY:The Generalized Multiset Sampler
DESCRIPTION:We will discuss about “The Generalized Multiset Sampler”\, Kim and MacEachern\, The Journal of Computation and Graphical Statistics\, 2021 \nAbstract: The multiset sampler\, an MCMC algorithm recently proposed by Leman and coauthors\, is an easy-to-implement algorithm which is especially well-suited to drawing samples from a multimodal distribution. We generalize the algorithm by redefining the multiset sampler with an explicit link between target distribution and sampling distribution. The generalized formulation replaces the multiset with a K-tuple\, which allows us to use the algorithm on unbounded parameter spaces\, improves estimation\, and sets up further extensions to adaptive MCMC techniques. Theoretical properties of the algorithm are provided and guidance is given on its implementation. Examples\, both simulated and real\, confirm that the generalized multiset sampler provides a simple\, general and effective approach to sampling from multimodal distributions. Supplementary materials for this article are available online.
URL:https://www.ibs.re.kr/bimag/event/2021-12-31/
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:20211229T150000
DTEND;TZID=Asia/Seoul:20211229T160000
DTSTAMP:20260424T214913
CREATED:20211228T210000Z
LAST-MODIFIED:20211227T001218Z
UID:5385-1640790000-1640793600@www.ibs.re.kr
SUMMARY:디지털 표현형의 진단 및 치료적 적용
DESCRIPTION:디지털 표현형의 진단 및 치료적 적용 조철현(세종충남대학교병원) 디지털 표현형(digital phenotype)은 각 개개인이 일상생활에서 사용하는 다양한 디지털 기기를 통해서 실시간으로 얻어지는 다양한 형태의 데이터를 뜻하는 것으로\, 디지털 기기의 사용이 보편화되면서 의료적 적용에 대한 가능성이 한층 높아지고 있다. 디지털 표현형은 이전에는 측정(measure)하기 힘들었던 영역에 대한 측정을 가능케 함으로써\, 의학적 평가나 진단적인 측면에서 임상적 함의를 갖는다고 볼 수 있겠다. 실제 의료현장에서 충분히 접근하고 파악하지 못했던 임상적인 의미를 도출해 내거나 새로운 발견을 할 수 있는 근거로 활용할 수도 있겠다. 임상적 상태의 변화나 치료 효과\, 예후 평가를 위한 기준으로 활용할 수도 있겠다. 또한\, 디지털치료제의 개발과 적용에 있어서 디지털 표현형을 고려하고 반영하는 것은 매우 중요한 부분이 될 것이다. 디지털치료제(Digital Therapeutics)는 사람을 대상으로 치료\, 예방\, 예후 개선 등을 목적으로 인지\, 행동\, 생활습관 등의 변화를 이끌어내기 위한 소프트웨어 형태로서 디지털 시대의 새로운 치료적 옵션으로 주목받고 있다. 특히\, 개인별\, 맞춤형 치료적 접근을 위해서는 디지털 표현형에 대한 이해를 높이고 잘 활용하는 것이 필수적이다. 본 발표에서는 디지털 표현형의 정의와 특성\, 임상적으로 어떤 함의를 가지고 있는 지에 대해 논의하고자 한다. 아울러\, 디지털 표현형의 활용 가능성\, 실제적 적용\, 디지털치료제에의 적용을 위한 방향성에 대해 발표하고자 한다.
URL:https://www.ibs.re.kr/bimag/event/2021-12-29/
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:20211224T130000
DTEND;TZID=Asia/Seoul:20211224T140000
DTSTAMP:20260424T214913
CREATED:20211223T190000Z
LAST-MODIFIED:20211221T043551Z
UID:5302-1640350800-1640354400@www.ibs.re.kr
SUMMARY:Information Integration and Energy Expenditure in Gene Regulation
DESCRIPTION:We will discuss about “Information Integration and Energy Expenditure in Gene Regulation”\, Estrada et al.\, Cell\, 2016 \nAbstract: The quantitative concepts used to reason about gene regulation largely derive from bacterial studies. We show that this bacterial paradigm cannot explain the sharp expression of a canonical developmental gene in response to a regulating transcription factor (TF). In the absence of energy expenditure\, with regulatory DNA at thermodynamic equilibrium\, information integration across multiple TF binding sites can generate the required sharpness\, but with strong constraints on the resultant “higher-order cooperativities.” Even with such integration\, there is a “Hopfield barrier” to sharpness; for n TF binding sites\, this barrier is represented by the Hill function with the Hill coefficient n. If\, however\, energy is expended to maintain regulatory DNA away from thermodynamic equilibrium\, as in kinetic proofreading\, this barrier can be breached and greater sharpness achieved. Our approach is grounded in fundamental physics\, leads to testable experimental predictions\, and suggests how a quantitative paradigm for eukaryotic gene regulation can be formulated.
URL:https://www.ibs.re.kr/bimag/event/2021-12-24/
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:20211223T163000
DTEND;TZID=Asia/Seoul:20211223T173000
DTSTAMP:20260424T214913
CREATED:20211222T220000Z
LAST-MODIFIED:20211220T121513Z
UID:5357-1640277000-1640280600@www.ibs.re.kr
SUMMARY:Methods for characterizing circadian physiology from wearables
DESCRIPTION:Abstract \nNon-invasive data collection in real-world settings with wearables provides a new opportunity for characterizing daily physiology. However\, accurate and efficient characterization remains an open problem because the complex autoregressive noise of the data makes it challenging to use a simple and efficient method for inference of clock proxies\, least squares method. In this talk\, we will introduce a simple approximation that alters the noise structure and thus enables one to use the least squares method. We will show its usefulness for real-time personalized fever detection in cancer patients.
URL:https://www.ibs.re.kr/bimag/event/2021-12-23-2/
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:20211215T143000
DTEND;TZID=Asia/Seoul:20211215T160000
DTSTAMP:20260424T214913
CREATED:20211214T190000Z
LAST-MODIFIED:20211214T070933Z
UID:5299-1639578600-1639584000@www.ibs.re.kr
SUMMARY:Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics
DESCRIPTION:We will discuss about “Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics”\, Ji et al.\, The Journal of Physical Chemistry A\, 2020 \nThe recently developed physics-informed neural network (PINN) has achieved success in many science and engineering disciplines by encoding physics laws into the loss functions of the neural network such that the network not only conforms to the measurements and initial and boundary conditions but also satisfies the governing equations. This work first investigates the performance of the PINN in solving stiff chemical kinetic problems with governing equations of stiff ordinary differential equations (ODEs). The results elucidate the challenges of utilizing the PINN in stiff ODE systems. Consequently\, we employ quasi-steady-state assumption (QSSA) to reduce the stiffness of the ODE systems\, and the PINN then can be successfully applied to the converted non-/mild-stiff systems. Therefore\, the results suggest that stiffness could be the major reason for the failure of the regular PINN in the studied stiff chemical kinetic systems. The developed stiff-PINN approach that utilizes QSSA to enable the PINN to solve stiff chemical kinetics shall open the possibility of applying the PINN to various reaction-diffusion systems involving stiff dynamics.
URL:https://www.ibs.re.kr/bimag/event/2021-12-15/
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:20211210T150000
DTEND;TZID=Asia/Seoul:20211210T170000
DTSTAMP:20260424T214914
CREATED:20211209T210000Z
LAST-MODIFIED:20211209T112916Z
UID:5122-1639148400-1639155600@www.ibs.re.kr
SUMMARY:The Graph convolutional Networks (GCN) with Persistent Homology and its applications 3/4
DESCRIPTION:Neural Networks with the Persistent Diagrams and Graph Classification. We introduce the first paper connecting persistent diagrams to the Neural Networks by Carrier et al\,” A neural Network Layer for Persistent Diagrams and New Graph Topological Signatures\, 2019\, arXiv. We are going to analyse the End-to-End algorithm and learning processes and applications.\nCode; tensorflow at https:// github.com/MathieuCarriere/perslay
URL:https://www.ibs.re.kr/bimag/event/2021-12-10/
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:20211126T100000
DTEND;TZID=Asia/Seoul:20211126T110000
DTSTAMP:20260424T214914
CREATED:20211124T190000Z
LAST-MODIFIED:20211122T014405Z
UID:5190-1637920800-1637924400@www.ibs.re.kr
SUMMARY:A Random Matrix Theory Approach to Denoise Single-Cell Data
DESCRIPTION:We will discuss about “A Random Matrix Theory Approach to Denoise Single-Cell Data”\, Aparicio et al.\, Patterns\, 2020 \nSingle-cell technologies provide the opportunity to identify new cellular states. However\, a major obstacle to the identification of biological signals is noise in single-cell data. In addition\, single-cell data are very sparse. We propose a new method based on random matrix theory to analyze and denoise single-cell sequencing data. The method uses the universal distributions predicted by random matrix theory for the eigenvalues and eigenvectors of random covariance/Wishart matrices to distinguish noise from signal. In addition\, we explain how sparsity can cause spurious eigenvector localization\, falsely identifying meaningful directions in the data. We show that roughly 95% of the information in single-cell data is compatible with the predictions of random matrix theory\, about 3% is spurious signal induced by sparsity\, and only the last 2% reflects true biological signal. We demonstrate the effectiveness of our approach by comparing with alternative techniques in a variety of examples with marked cell populations.
URL:https://www.ibs.re.kr/bimag/event/a-random-matrix-theory-approach-to-denoise-single-cell-data/
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:20211125T180000
DTEND;TZID=Asia/Seoul:20211125T190000
DTSTAMP:20260424T214914
CREATED:20211124T230000Z
LAST-MODIFIED:20211111T104319Z
UID:4808-1637863200-1637866800@www.ibs.re.kr
SUMMARY:Quantitative comparisons between models and data to provide new insights in cell and developmental biology
DESCRIPTION:This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234) \nAbstract: \nSimple mathematical models have had remarkable successes in biology\, framing how we understand a host of mechanisms and processes. However\, with the advent of a host of new experimental technologies\, the last ten years has seen an explosion in the amount and types of quantitative data now being generated. This sets a new challenge for the field – to develop\, calibrate and analyse new models to interpret these data. In this talk I will use examples relating to intracellular transport and cell motility to showcase how quantitative comparisons between models and data can help tease apart subtle details of biological mechanisms. \nReferences: \n• T. P. Prescott\, K. Zhu\, M. Zhao and R. E. Baker (2021). Quantifying the impact of electric fields on single-cell motility. Biophys. J. In press. \n• J. U. Harrison\, R. M. Parton\, I. Davis and R. E. Baker (2019). Testing models of mRNA localization reveals robustness regulated by reducing transport between cells. Biophys. J. 117(11):2154-2165.
URL:https://www.ibs.re.kr/bimag/event/2021-11-25/
LOCATION:ZOOM ID: 709 120 4849 (ibsbimag)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2021/07/RuthBaker_profile.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20211118T130000
DTEND;TZID=Asia/Seoul:20211118T140000
DTSTAMP:20260424T214914
CREATED:20211117T190000Z
LAST-MODIFIED:20211101T080821Z
UID:5187-1637240400-1637244000@www.ibs.re.kr
SUMMARY:Solving Singular Control Problems in Mathematical Biology\, Using PASA
DESCRIPTION:We will discuss about “Solving Singular Control Problems in Mathematical Biology\, Using PASA”\, Atkins et al.\, arXiv\, 2020 \nIn this paper\, we will demonstrate how to use a nonlinear polyhedral constrained optimization solver called the Polyhedral Active Set Algorithm (PASA) for solving a general singular control problem. We present methods of discretizing a general optimal control problem that involves the use of the gradient of the Lagrangian for computing the gradient of the cost functional so that PASA can be applied. When a numerical solution contains artifacts that resemble “chattering”\, a phenomenon where the control oscillates wildly along the singular region\, we recommend a method of regularizing the singular control problem by adding a term to the cost functional that measures a scalar multiple of the total variation of the control\, where the scalar is viewed as a tuning parameter. We then demonstrate PASA’s performance on three singular control problems that give rise to different applications of mathematical biology. We also provide some exposition on the heuristics that we use in determining an appropriate size for the tuning parameter.
URL:https://www.ibs.re.kr/bimag/event/2021-11-18-2/
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:20211118T110000
DTEND;TZID=Asia/Seoul:20211118T120000
DTSTAMP:20260424T214914
CREATED:20211117T170000Z
LAST-MODIFIED:20211230T031249Z
UID:4820-1637233200-1637236800@www.ibs.re.kr
SUMMARY:Following the energy in cellular information processing
DESCRIPTION:This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234) \nAbstract: John Hopfield first pointed out that there are barriers – we call them Hopfield barriers – to biological information-processing at thermodynamic equilibrium. I will explain how the widely-used Hill function with coefficient n is the universal Hopfield barrier to the sharpness of binding to n sites. Away from thermodynamic equilibrium\, I will describe the challenge of path dependent  complexity and introduce the entropy-production index as a measure of non-equilibrium complexity.
URL:https://www.ibs.re.kr/bimag/event/2021-11-18/
LOCATION:ZOOM ID: 709 120 4849 (ibsbimag)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/png:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2021/11/jeremy-scaled_250x250.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20211112T133000
DTEND;TZID=Asia/Seoul:20211112T153000
DTSTAMP:20260424T214914
CREATED:20211111T210000Z
LAST-MODIFIED:20211109T062309Z
UID:5120-1636723800-1636731000@www.ibs.re.kr
SUMMARY:The Graph convolutional Networks (GCN) with Persistent Homology and its application 2/4
DESCRIPTION:Simplicial Complexes\, Persistent Homology and Persistent Diagrams. After a brief review on the persistent homology( Cohen-Steiner\, Edelsbrunner\, Harer\,2010)\, we discuss constructive procedures persistent diagrams from the persistent homology. Code; 9 software packages generating persistent homology are introduced at ” A roadmap for the computation of persistent homology”\, EPJ Data Science\, a Springer Open Journal.
URL:https://www.ibs.re.kr/bimag/event/2021-11-12/
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:20211112T110000
DTEND;TZID=Asia/Seoul:20211112T120000
DTSTAMP:20260424T214914
CREATED:20211111T170000Z
LAST-MODIFIED:20211111T084242Z
UID:5185-1636714800-1636718400@www.ibs.re.kr
SUMMARY:Detecting and quantifying causal associations in large nonlinear time series datasets
DESCRIPTION:We will discuss about “Detecting and quantifying causal associations in large nonlinear time series datasets”\, Runge et al.\, Science Advances\, 2019 \nIdentifying causal relationships and quantifying their strength from observational time series data are key problems in disciplines dealing with complex dynamical systems such as the Earth system or the human body. Data-driven causal inference in such systems is challenging since datasets are often high dimensional and nonlinear with limited sample sizes. Here\, we introduce a novel method that flexibly combines linear or nonlinear conditional independence tests with a causal discovery algorithm to estimate causal networks from large-scale time series datasets. We validate the method on time series of well-understood physical mechanisms in the climate system and the human heart and using large-scale synthetic datasets mimicking the typical properties of real-world data. The experiments demonstrate that our method outperforms state-of-the-art techniques in detection power\, which opens up entirely new possibilities to discover and quantify causal networks from time series across a range of research fields.
URL:https://www.ibs.re.kr/bimag/event/2021-11-12-2/
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:20211111T110000
DTEND;TZID=Asia/Seoul:20211111T120000
DTSTAMP:20260424T214914
CREATED:20211110T170000Z
LAST-MODIFIED:20210826T000813Z
UID:4816-1636628400-1636632000@www.ibs.re.kr
SUMMARY:Biofluiddynamics of reproduction
DESCRIPTION:This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234) \nAbstract: From fertilization to birth\, successful mammalian reproduction relies on interactions of elastic structures with a fluid environment. Sperm flagella must move through cervical mucus to the uterus and into the oviduct\, where fertilization occurs. In fact\, some sperm may adhere to oviductal epithelia\, and must change their pattern of oscillation to escape. In addition\, coordinated beating of oviductal cilia also drive the flow. Sperm-egg penetration\, transport of the fertilized ovum from the oviduct to its implantation in the uterus and\, indeed\, birth itself are rich examples of elasto-hydrodynamic coupling. We will discuss successes and challenges in the mathematical and computational modeling of the biofluids of reproduction.
URL:https://www.ibs.re.kr/bimag/event/2021-11-11/
LOCATION:ZOOM ID: 709 120 4849 (ibsbimag)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2021/07/fauci_profile_sqr-e1627697850446.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20211029T150000
DTEND;TZID=Asia/Seoul:20211029T170000
DTSTAMP:20260424T214914
CREATED:20211028T210000Z
LAST-MODIFIED:20211029T113540Z
UID:5117-1635519600-1635526800@www.ibs.re.kr
SUMMARY:The Graph convolutional Networks (GCN) with Persistent Homology and its application 1/4
DESCRIPTION:(1) GCN and its Application.\nWe introduce the GCN by reviewing the monumental paper ” Semi-Supervised Classification with the Graph Convolutional Networks”\, ICLR 2018 by Kipf and Welling. We are going to much detail the algorithm of message aggregation and passings and learning processes.\nCode ; https://github.com/tkipf/gcn \n(2) Graph Attention networks(GAT) and its Applications. Bengio et al improved greatly the capability of GCN by employing the Attention mechanism to GCN on the paper\,” Graph Attention Networks\, ICLR\,2018. We review closely the derivation of algirithms\, learning processes and discuss its super performance.\nCode; https://github.com/PetarV-/GAT
URL:https://www.ibs.re.kr/bimag/event/2021-10-29/
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:20211027T170000
DTEND;TZID=Asia/Seoul:20211027T180000
DTSTAMP:20260424T214914
CREATED:20211026T230000Z
LAST-MODIFIED:20210901T070035Z
UID:4812-1635354000-1635357600@www.ibs.re.kr
SUMMARY:Systems pharmacology towards personalized chronotherapy
DESCRIPTION:This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234) \nAbstract: \nChronotherapeutics- that is administering drugs following the patient’s biological rhythms over the 24 h span- may largely impact on both drug toxicities and efficacy in various pathologies including cancer [1]. However\, recent findings highlight the critical need of personalizing circadian delivery according to the patient sex\, genetic background or chronotype. Chronotherapy personalization requires to reliably account for the temporal dynamics of molecular pathways of patient’s response to drug administration [2]. In a context where clinical molecular data is usually minimal in individual patients\, multi-scale- from preclinical to clinical- systems pharmacology stands as an adapted solution to describe gene and protein networks driving circadian rhythms of treatment efficacy and side effects and allow for the design of personalized chronotherapies.\nSuch a multiscale approach is being undertaken for personalizing the circadian administration of irinotecan\, one of the cornerstones of chemotherapies against digestive cancers. Irinotecan molecular chronopharmacology was studied at the cellular level in an in vitro/in silico investigation. Large transcription rhythms of period T= 28 h 06 min (SD 1 h 41 min) moderated drug bioactivation\, detoxification\, transport\, and target in synchronized Caco-2 colorectal cancer cell cultures. These molecular rhythms translated into statistically significant changes according to drug timing in irinotecan pharmacokinetics\, pharmacodynamics\, and drug-induced apoptosis. Clock silencing through siBMAL1 exposure ablated all the chronopharmacology mechanisms. Mathematical modeling highlighted circadian bioactivation and detoxification as the most critical determinants of irinotecan chronopharmacology [3]. The cellular model of irinotecan chronoPK-PD was further tested on SW480 and SW620 cell lines\, and connected to a new clock model to investigate the feasibility of irinotecan timing personalization solely based on clock gene expression monitoring (Hesse\, Martinelli et al.\, under review).\nTo step towards the clinics\, on one side\, mathematical models of irinotecan\, oxaliplatin and 5-fluorouracil pharmacokinetics were designed to precisely compute the exposure concentration of tissue over time after complex chronomodulated drug administration through programmable pumps [4]. On the other side\, we aimed to design a model learning methodology predicting from non-invasively measured circadian biomarkers (e.g. rest-activity\, body temperature\, cortisol\, food intake\, melatonin)\, the patient peripheral circadian clocks and associated optimal drug timing [5]. We investigated at the molecular scale the influence of systemic regulators on peripheral clocks in four classes of mice (2 strains\, 2 sexes). Best models involved a modulation of either Bmal1 or Per2 transcription most likely by temperature or nutrient exposure cycles. The strengths of systemic regulations were found to be significantly different according to mouse sex and genetic background.\nReferences\n1. Ballesta\, A.\, et al.\, Systems Chronotherapeutics. Pharmacol Rev\, 2017. 69(2): p. 161-199.\n2. Sancar\, A. and R.N. Van Gelder\, Clocks\, cancer\, and chronochemotherapy. Science\, 2021. 371(6524).\n3. Dulong\, S.\, et al.\, Identification of Circadian Determinants of Cancer Chronotherapy through In Vitro Chronopharmacology and Mathematical Modeling. Mol Cancer Ther\, 2015.\n4. Hill\, R.J.W.\, et al.\, Optimizing circadian drug infusion schedules towards personalized cancer chronotherapy. PLoS Comput Biol\, 2020. 16(1): p. e1007218.\n5. Martinelli\, J.\, et al.\, Model learning to identify systemic regulators of the peripheral circadian clock. 2021. \n 
URL:https://www.ibs.re.kr/bimag/event/2021-10-27/
LOCATION:ZOOM ID: 709 120 4849 (ibsbimag)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2021/07/AnnabelleBallesta_profile_sqr-e1627697556509.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20211027T110000
DTEND;TZID=Asia/Seoul:20211027T120000
DTSTAMP:20260424T214914
CREATED:20211028T190000Z
LAST-MODIFIED:20211024T160104Z
UID:5058-1635332400-1635336000@www.ibs.re.kr
SUMMARY:Inferring causality in biological oscillators
DESCRIPTION:Abstract \nTBA
URL:https://www.ibs.re.kr/bimag/event/2021-10-29-2/
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:20211022T130000
DTEND;TZID=Asia/Seoul:20211022T140000
DTSTAMP:20260424T214914
CREATED:20211021T190000Z
LAST-MODIFIED:20211001T062513Z
UID:5061-1634907600-1634911200@www.ibs.re.kr
SUMMARY:Filtering and inference for stochastic oscillators with distributed delays
DESCRIPTION:We will discuss about “Filtering and inference for stochastic oscillators with distributed delays”\, Calderazzo et al.\, Bioinformatics\, 2018 at the Journal Club \n\n\n\n\nMotivation\nThe time evolution of molecular species involved in biochemical reaction networks often arises from complex stochastic processes involving many species and reaction events. Inference for such systems is profoundly challenged by the relative sparseness of experimental data\, as measurements are often limited to a small subset of the participating species measured at discrete time points. The need for model reduction can be realistically achieved for oscillatory dynamics resulting from negative translational and transcriptional feedback loops by the introduction of probabilistic time-delays. Although this approach yields a simplified model\, inference is challenging and subject to ongoing research. The linear noise approximation (LNA) has recently been proposed to address such systems in stochastic form and will be exploited here. \n\n\nResults\nWe develop a novel filtering approach for the LNA in stochastic systems with distributed delays\, which allows the parameter values and unobserved states of a stochastic negative feedback model to be inferred from univariate time-series data. The performance of the methods is tested for simulated data. Results are obtained for real data when the model is fitted to imaging data on Cry1\, a key gene involved in the mammalian central circadian clock\, observed via a luciferase reporter construct in a mouse suprachiasmatic nucleus. \n\n\nAvailability and implementation\nProgrammes are written in MATLAB and Statistics Toolbox Release 2016 b\, The MathWorks\, Inc.\, Natick\, Massachusetts\, USA. Sample code and Cry1 data are available on GitHub https://github.com/scalderazzo/FLNADD.
URL:https://www.ibs.re.kr/bimag/event/2021-10-22-2/
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:20211021T110000
DTEND;TZID=Asia/Seoul:20211021T120000
DTSTAMP:20260424T214914
CREATED:20211103T170000Z
LAST-MODIFIED:20210930T040222Z
UID:4787-1634814000-1634817600@www.ibs.re.kr
SUMMARY:Scaling in development
DESCRIPTION:This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234)\n\nAbstract: \n Within a given species\, fluctuations in egg or embryo size is unavoidable. Despite this\, the gene expression pattern and hence the embryonic structure often scale in proportion with the body length. This scaling phenomenon is very common in development and regeneration and has long fascinated scientists. I will first discuss a generic theoretical framework to show how scaling gene expression pattern can emerge from non-scaling morphogen gradients. I will then demonstrate that the Drosophila gap gene system achieves scaling in a way that is entirely consistent with our theory. Remarkably\, a parameter-free model based on the theory quantitatively accounts for the gap gene expression pattern in nearly all morphogen mutants. Furthermore\, the regulation logic and the coding/decoding strategy of the gap gene system can be revealed. Our work provides a general theoretical framework on a large class of problems where scaling output is induced by non-scaling input\, as well as a unified understanding of scaling\, mutants’ behavior and regulation in the Drosophila gap gene and related systems.
URL:https://www.ibs.re.kr/bimag/event/2021-10-21/
LOCATION:ZOOM ID: 709 120 4849 (ibsbimag)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/png:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2021/07/resize.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20211008T140000
DTEND;TZID=Asia/Seoul:20211008T150000
DTSTAMP:20260424T214914
CREATED:20211007T190000Z
LAST-MODIFIED:20211006T081805Z
UID:4912-1633701600-1633705200@www.ibs.re.kr
SUMMARY:Balanced truncation for model reduction of biological oscillators
DESCRIPTION:We will discuss about “Balanced truncation for model reduction of biological oscillators”\, Padoan et al.\, Biological Cybernetics\, 2021 \nModel reduction is a central problem in mathematical biology. Reduced order models enable modeling of a biological system at different levels of complexity and the quantitative analysis of its properties\, like sensitivity to parameter variations and resilience to exogenous perturbations. However\, available model reduction methods often fail to capture a diverse range of nonlinear behaviors observed in biology\, such as multistability and limit cycle oscillations. The paper addresses this need using differential analysis. This approach leads to a nonlinear enhancement of classical balanced truncation for biological systems whose behavior is not restricted to the stability of a single equilibrium. Numerical results suggest that the proposed framework may be relevant to the approximation of classical models of biological systems.
URL:https://www.ibs.re.kr/bimag/event/2021-10-8/
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:20211007T110000
DTEND;TZID=Asia/Seoul:20211007T120000
DTSTAMP:20260424T214914
CREATED:20211006T170000Z
LAST-MODIFIED:20211230T031435Z
UID:4850-1633604400-1633608000@www.ibs.re.kr
SUMMARY:A temporal signaling code to specify immune responses
DESCRIPTION:This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234) \nAbstract: \nImmune sentinel cells must initiate the appropriate immune response upon sensing the presence of diverse pathogens or immune stimuli. To generate stimulus-specific gene expression responses\, immune sentinel cells have evolved a temporal code in the dynamics of stimulus responsive transcription factors. I will present recent works 1) using an information theoretic approach to identify the codewords\, termed “signaling codons”\, 2) using a machine learning approach to characterize their reliability and points of confusion\, and 3) dynamical systems modeling to characterize the molecular circuits that allow for their encoding. I will present progress on how the temporal code may be decoded to specify immune responses.  Further\, I will discuss to what extent such a code may be harnessed to achieve greater pharmacological specificity when therapeutically targeting pleiotropic signaling hubs. \nNFκB Signaling: information theory\, signaling codons \nAdelaja\, A.\, Taylor\, B.\, Sheu\, K.M.\, Liu\, Y.\, Luecke\, S.\, Hoffmann\, A. 2021 Six distinct NFκB signaling codons convey discrete information to distinguish stimuli and enable appropriate macrophage responses. Immunity\, 54\, pp.916-930. e7. PMID: 33979588 \nTang\, Y.\, Adelaja\, A.\, Ye\, X\, Deeds\, E.\, Wollman\, R.\, Hoffmann\, A. 2021. Quantifying information accumulation encoded in the dynamics of biochemical signaling. Nature Communications 12\, pp.1-10 \nDecoding signaling codons to specify immune responses \nSen S.\, Cheng\, Z.\, Sheu\, K.\, Chen\, E.Y.H.\, Hoffmann\, A. 2020 Gene Regulatory Strategies that Decode the Duration of NFkB Dynamics Contribute to LPS- versus TNF-Specific Gene Expression. Cell Systems\, 10\, pp.1-14. PMID:31972132\, PMC7047529 \nCheng\, Q.J.\, Ohta\, S.\, Sheu\, K.M.\, Spreafico\, R.\, Adelaja\, A.\, Taylor\, B.\, Hoffmann\, A.  2021 NFκB dynamics determine the stimulus-specificity of epigenomic reprogramming in macrophages. Science\, 372\, pp.1349-1353; PMID: 34140389. \nPharmacologic manipulation of the code \nBehar\, M.\, Barken\, D.\, Werner\, S.L.\, Hoffmann\, A. 2013  The Dynamics of Signaling as a Pharmacological Target.  Cell\, 155\, pp.448-461. PMID: 24120141\, PMC3856316
URL:https://www.ibs.re.kr/bimag/event/2021-10-07/
LOCATION:ZOOM ID: 709 120 4849 (ibsbimag)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/png:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2021/10/AlexanderHoffmann_profile_250x250.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20210924T130000
DTEND;TZID=Asia/Seoul:20210924T140000
DTSTAMP:20260424T214914
CREATED:20210922T190000Z
LAST-MODIFIED:20210831T052818Z
UID:4910-1632488400-1632492000@www.ibs.re.kr
SUMMARY:A spatio-temporal model to reveal oscillator phenotypes in molecular clocks: Parameter estimation elucidates circadian gene transcription dynamics in single-cells
DESCRIPTION:We will discuss about “A spatio-temporal model to reveal oscillator phenotypes in molecular clocks: Parameter estimation elucidates circadian gene transcription dynamics in single-cells”\, Unosson et al.\, bioRxiv\, 2021 \nWe propose a stochastic distributed delay model together with a Markov random field prior and a measurement model for bioluminescence-reporting to analyse spatiotemporal gene expression in intact networks of cells. The model describes the oscillating time evolution of molecular mRNA counts through a negative transcriptional-translational feedback loop encoded in a chemical Langevin equation with a probabilistic delay distribution. The model is extended spatially by means of a multiplicative random effects model with a first order Markov random field prior distribution. Our methodology effectively separates intrinsic molecular noise\, measurement noise\, and extrinsic noise and phenotypic variation driving cell heterogeneity\, while being amenable to parameter identification and inference. Based on the single-cell model we propose a novel computational stability analysis that allows us to infer two key characteristics\, namely the robustness of the oscillations\, i.e. whether the reaction network exhibits sustained or damped oscillations\, and the profile of the regulation\, i.e. whether the inhibition occurs over time in a more distributed versus a more direct manner\, which affects the cells’ ability to phase-shift to new schedules. We show how insight into the spatio-temporal characteristics of the circadian feedback loop in the suprachiasmatic nucleus (SCN) can be gained by applying the methodology to bioluminescence-reported expression of the circadian core clock gene Cry1 across mouse SCN tissue. We find that while (almost) all SCN neurons exhibit robust cell-autonomous oscillations\, the parameters that are associated with the regulatory transcription profile give rise to a spatial division of the tissue between the central region whose oscillations are resilient to perturbation in the sense that they maintain a high degree of synchronicity\, and the dorsal region which appears to phase shift in a more diversified way as a response to large perturbations and thus could be more amenable to entrainment.
URL:https://www.ibs.re.kr/bimag/event/2021-09-24/
LOCATION:B305 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:20210917T130000
DTEND;TZID=Asia/Seoul:20210917T140000
DTSTAMP:20260424T214914
CREATED:20210915T190000Z
LAST-MODIFIED:20210831T052758Z
UID:4908-1631883600-1631887200@www.ibs.re.kr
SUMMARY:The Oscillation Amplitude\, Not the Frequency of Cytosolic Calcium\, Regulates Apoptosis Induction
DESCRIPTION:We will discuss about “The Oscillation Amplitude\, Not the Frequency of Cytosolic Calcium\, Regulates Apoptosis Induction ”\, Qi et al.\, iScience\, 2020 \nAbstract: \nAlthough a rising concentration of cytosolic Ca2+ has long been recognized as an essential signal for apoptosis\, the dynamical mechanisms by which Ca2+ regulates apoptosis are not clear yet. To address this\, we constructed a computational model that integrates known biochemical reactions and can reproduce the dynamical behaviors of Ca2+-induced apoptosis as observed in experiments. Model analysis shows that oscillating Ca2+ signals first convert into gradual signals and eventually transform into a switch-like apoptotic response. Via the two processes\, the apoptotic signaling pathway filters the frequency of Ca2+ oscillations effectively but instead responds acutely to their amplitude. Collectively\, our results suggest that Ca2+ regulates apoptosis mainly via oscillation amplitude\, rather than frequency\, modulation. This study not only provides a comprehensive understanding of how oscillatory Ca2+ dynamically regulates the complex apoptotic signaling network but also presents a typical example of how Ca2+ controls cellular responses through amplitude modulation.
URL:https://www.ibs.re.kr/bimag/event/2021-09-17/
LOCATION:B305 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:20210916T110000
DTEND;TZID=Asia/Seoul:20210916T120000
DTSTAMP:20260424T214914
CREATED:20210915T170000Z
LAST-MODIFIED:20211230T030915Z
UID:4529-1631790000-1631793600@www.ibs.re.kr
SUMMARY:Stochastic processes as scientific instruments: efficient inference based on stochastic dynamical systems
DESCRIPTION:This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234)\n\nAbstract: Questions about the mechanistic operation of biological systems are naturally formulated as stochastic processes\, but confronting such models with data can be challenging.  In this talk\, I describe the essence of the difficulty\, highlighting both the technical issues and the importance of the “plug-and-play property”.  I then illustrate some effective approaches to efficient inference based on such models.  I conclude by sketching promising new developments and describing some open problems.
URL:https://www.ibs.re.kr/bimag/event/2021-09-16/
LOCATION:ZOOM ID: 709 120 4849 (ibsbimag)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2021/09/imagev2.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20210909T110000
DTEND;TZID=Asia/Seoul:20210909T120000
DTSTAMP:20260424T214914
CREATED:20210902T140000Z
LAST-MODIFIED:20210903T055016Z
UID:4981-1631185200-1631188800@www.ibs.re.kr
SUMMARY:COVID19 – Mathematical Modeling and Machine Learning
DESCRIPTION:Abstract \nThis presentation include the following two topics. First of all\, we consider a spread model of COVID-19 with time-dependent parameters via deep learning. We developed a SIR model with time-dependent parameters via deep learning methods. Furthermore\, we validated the model with the conventional model to confirm its convergent nature. Next\, We also developed a machine learning model that predicts the mortality of infected patients by using basic patients information such as age\, residence\, comorbidity\, and past medical history. Furthermore\, we aim to establish a medical system that allows patients to check their own severity\, and informs them to visit the appropriate clinic center by referring to the past treatment details of other patients with similar severity.
URL:https://www.ibs.re.kr/bimag/event/covid19-mathematical-modeling-and-machine-learning/
LOCATION:B305 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:20210909T090000
DTEND;TZID=Asia/Seoul:20210909T100000
DTSTAMP:20260424T214914
CREATED:20210908T190000Z
LAST-MODIFIED:20210903T055048Z
UID:4906-1631178000-1631181600@www.ibs.re.kr
SUMMARY:Nonlinear delay differential equations and their application to modeling biological network motifs
DESCRIPTION:We will discuss about “Nonlinear delay differential equations and their application to modeling biological network motifs”\, Glass et al.\, Nature Communications\, 2021 \nAbstract: \nBiological regulatory systems\, such as cell signaling networks\, nervous systems and ecological webs\, consist of complex dynamical interactions among many components. Network motif models focus on small sub-networks to provide quantitative insight into overall behavior. However\, such models often overlook time delays either inherent to biological processes or associated with multi-step interactions. Here we systematically examine explicit-delay versions of the most common network motifs via delay differential equation (DDE) models\, both analytically and numerically. We find many broadly applicable results\, including parameter reduction versus canonical ordinary differential equation (ODE) models\, analytical relations for converting between ODE and DDE models\, criteria for when delays may be ignored\, a complete phase space for autoregulation\, universal behaviors of feedforward loops\, a unified Hill-function logic framework\, and conditions for oscillations and chaos. We conclude that explicit-delay modeling simplifies the phenomenology of many biological networks and may aid in discovering new functional motifs.
URL:https://www.ibs.re.kr/bimag/event/2021-09-09/
LOCATION:B305 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:20210908T170000
DTEND;TZID=Asia/Seoul:20210908T180000
DTSTAMP:20260424T214914
CREATED:20210907T230000Z
LAST-MODIFIED:20210907T103108Z
UID:4648-1631120400-1631124000@www.ibs.re.kr
SUMMARY:[CANCELED] Approaches to understanding tumour-immune interactions
DESCRIPTION:CANCELED due to unexpected circumstances\nThis talk will be presented online. Zoom link: 709 120 4849 (pw: 1234) \nAbstract: While the presence of immune cells within solid tumours was initially viewed positively\, as the host fighting to rid itself of a foreign body\, we now know that the tumour can manipulate immune cells so that they promote\, rather than inhibit\, tumour growth. Immunotherapy aims to correct for this by boosting and/or restoring the normal function of the immune system. Immunotherapy has delivered some extremely promising results. However\, the complexity of the tumour-immune interactions means that it can be difficult to understand why one patient responds well to immunotherapy while another does not. In this talk\, we will show how mathematical\, statistical and topological methods can contribute to resolving this issue and present recent results which illustrate the complementary insight that different approaches can deliver.
URL:https://www.ibs.re.kr/bimag/event/2021-09-08/
LOCATION:ZOOM ID: 709 120 4849 (ibsbimag)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/png:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2021/06/Helen-Byrne_Photo_crop2.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20210902T130000
DTEND;TZID=Asia/Seoul:20210902T140000
DTSTAMP:20260424T214914
CREATED:20210902T190000Z
LAST-MODIFIED:20210831T052727Z
UID:4841-1630587600-1630591200@www.ibs.re.kr
SUMMARY:Machine learning of stochastic gene network phenotypes
DESCRIPTION:We will discuss about “Machine learning of stochastic gene network phenotypes”\, Park et al.\, bioRxiv\, 2019 \nAbstract: \nA recurrent challenge in biology is the development of predictive quantitative models because most molecular and cellular parameters have unknown values and realistic models are analytically intractable. While the dynamics of the system can be analyzed via computer simulations\, substantial computational resources are often required given uncertain parameter values resulting in large numbers of parameter combinations\, especially when realistic biological features are included. Simulation alone also often does not yield the kinds of intuitive insights from analytical solutions. Here we introduce a general framework combining stochastic/mechanistic simulation of reaction systems and machine learning of the simulation data to generate computationally efficient predictive models and interpretable parameter-phenotype maps. We applied our approach to investigate stochastic gene expression propagation in biological networks\, which is a contemporary challenge in the quantitative modeling of single-cell heterogeneity. We found that accurate\, predictive machine-learning models of stochastic simulation results can be constructed. Even in the simplest networks existing analytical schemes generated significantly less accurate predictions than our approach\, which revealed interesting insights when applied to more complex circuits\, including the extensive tunability of information propagation enabled by feedforward circuits and how even single negative feedbacks can utilize stochastic fluctuations to generate robust oscillations. Our approach is applicable beyond biology and opens up a new avenue for exploring complex dynamical systems.
URL:https://www.ibs.re.kr/bimag/event/2021-09-02-2/
LOCATION:B305 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