BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Biomedical Mathematics Group - ECPv6.15.20//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://www.ibs.re.kr/bimag
X-WR-CALDESC:Events for Biomedical Mathematics Group
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Asia/Seoul
BEGIN:STANDARD
TZOFFSETFROM:+0900
TZOFFSETTO:+0900
TZNAME:KST
DTSTART:20210101T000000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220805T130000
DTEND;TZID=Asia/Seoul:20220805T140000
DTSTAMP:20260507T031542
CREATED:20220804T190000Z
LAST-MODIFIED:20220729T014246Z
UID:6341-1659704400-1659708000@www.ibs.re.kr
SUMMARY:Neural Ordinary Differential Equations
DESCRIPTION:We will discuss about “Neural Ordinary Differential Equations”\, Chen\, Ricky TQ\, et al.\, Advances in neural information processing systems 31 (2018). \nAbstract: We introduce a new family of deep neural network models. Instead of specifying a discrete sequence of hidden layers\, we parameterize the derivative of the hidden state using a neural network. The output of the network is computed using a blackbox differential equation solver. These continuous-depth models have constant memory cost\, adapt their evaluation strategy to each input\, and can explicitly trade numerical precision for speed. We demonstrate these properties in continuous-depth residual networks and continuous-time latent variable models. We also construct continuous normalizing flows\, a generative model that can train by maximum likelihood\, without partitioning or ordering the data dimensions. For training\, we show how to scalably backpropagate through any ODE solver\, without access to its internal operations. This allows end-to-end training of ODEs within larger models.
URL:https://www.ibs.re.kr/bimag/event/2022-08-05-jc/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220729T130000
DTEND;TZID=Asia/Seoul:20220729T140000
DTSTAMP:20260507T031542
CREATED:20220728T190000Z
LAST-MODIFIED:20220728T085252Z
UID:6250-1659099600-1659103200@www.ibs.re.kr
SUMMARY:Learning stable and predictive structures in kinetic systems
DESCRIPTION:We will discuss about “Learning stable and predictive structures in kinetic systems”\, Niklas Pfister \, Stefan Bauer\, and Jonas Peters. PNAS\, 2019 \nAbstract: Learning kinetic systems from data is one of the core challenges in many fields. Identifying stable models is essential for the generalization capabilities of data-driven inference. We introduce a computationally efficient framework\, called CausalKinetiX\, that identifies structure from discrete time\, noisy observations\, generated from heterogeneous experiments. The algorithm assumes the existence of an underlying\, invariant kinetic model\, a key criterion for reproducible research. Results on both simulated and real-world examples suggest that learning the structure of kinetic systems benefits from a causal perspective. The identified variables and models allow for a concise description of the dynamics across multiple experimental settings and can be used for prediction in unseen experiments. We observe significant improvements compared to well-established approaches focusing solely on predictive performance\, especially for out-of-sample generalization.
URL:https://www.ibs.re.kr/bimag/event/2022-07-29-jc/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220722T130000
DTEND;TZID=Asia/Seoul:20220722T140000
DTSTAMP:20260507T031542
CREATED:20220629T010032Z
LAST-MODIFIED:20220629T010032Z
UID:6248-1658494800-1658498400@www.ibs.re.kr
SUMMARY:Accuracy and limitations of extrinsic noise models to describe gene expression in growing cells
DESCRIPTION:We will discuss about “Accuracy and limitations of extrinsic noise models to describe gene expression in growing cells”\, Jia\, Chen\, and Ramon Grima\, bioRxiv (2022). \nAbstract: The standard model describing the fluctuations of mRNA numbers in single cells is the telegraph model which includes synthesis and degradation of mRNA\, and switching of the gene between active and inactive states. While commonly used\, this model does not describe how fluctuations are influenced by the cell cycle phase\, cellular growth and division\, and other crucial aspects of cellular biology. Here we derive the analytical time-dependent solution of a stochastic model that explicitly considers various sources of intrinsic and extrinsic noise: switching between inactive and active states\, doubling of gene copy numbers upon DNA replication\, dependence of the mRNA synthesis rate on cellular volume\, gene dosage compensation\, partitioning of molecules during cell division\, cell-cycle duration variability\, and cell-size control strategies. We show that generally the analytical distribution of transcript numbers in steady-state growth cannot be accurately approximated by the steady-state solution of extrinsic noise models\, i.e. a telegraph model with parameters drawn from probability distributions. This is because the mRNA lifetime is often not small enough compared to the cell cycle duration to erase the memory of division and replication. Accurate approximations are possible when this memory is weak\, e.g. for genes with bursty expression and for which there is sufficient gene dosage compensation when replication occurs.
URL:https://www.ibs.re.kr/bimag/event/2022-07-22-jc/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220708T130000
DTEND;TZID=Asia/Seoul:20220708T140000
DTSTAMP:20260507T031542
CREATED:20220707T190000Z
LAST-MODIFIED:20220629T005506Z
UID:6246-1657285200-1657288800@www.ibs.re.kr
SUMMARY:Chemical Organisation Theory
DESCRIPTION:We will discuss about “Chemical Organisation Theory\n“\, Dittrich\, Peter\, and Pietro Speroni Di Fenizio\, Bulletin of mathematical biology 69.4 (2007): 1199-1231. \nAbstract: Complex dynamical reaction networks consisting of many components that interact and produce each other are difficult to understand\, especially\, when new component types may appear and present component types may vanish completely. Inspired by Fontana and Buss (Bull. Math. Biol.\, 56\, 1–64) we outline a theory to deal with such systems. The theory consists of two parts. The first part introduces the concept of a chemical organisation as a closed and self-maintaining set of components. This concept allows to map a complex (reaction) network to the set of organisations\, providing a new view on the system’s structure. The second part connects dynamics with the set of organisations\, which allows to map a movement of the system in state space to a movement in the set of organisations. The relevancy of our theory is underlined by a theorem that says that given a differential equation describing the chemical dynamics of the network\, then every stationary state is an instance of an organisation. For demonstration\, the theory is applied to a small model of HIV-immune system interaction by Wodarz and Nowak (Proc. Natl. Acad. USA\, 96\, 14464–14469) and to a large model of the sugar metabolism of E. Coli by Puchalka and Kierzek (Biophys. J.\, 86\, 1357–1372). In both cases organisations where uncovered\, which could be related to functions.
URL:https://www.ibs.re.kr/bimag/event/2022-07-08-jc/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220705T160000
DTEND;TZID=Asia/Seoul:20220705T170000
DTSTAMP:20260507T031542
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:20220705T100000
DTEND;TZID=Asia/Seoul:20220705T110000
DTSTAMP:20260507T031542
CREATED:20220704T160000Z
LAST-MODIFIED:20220704T035619Z
UID:6122-1657015200-1657018800@www.ibs.re.kr
SUMMARY:AI Pontryagin or how artificial neural networks learn to control dynamical systems
DESCRIPTION:We will discuss about “AI Pontryagin or how artificial neural networks learn to control dynamical systems”\, Böttcher\, L.\, Antulov-Fantulin\, N. & Asikis\, T.\, Nat Commun 13\, 333 (2022). \nAbstract: The efficient control of complex dynamical systems has many applications in the natural and applied sciences. In most real-world control problems\, both control energy and cost constraints play a significant role. Although such optimal control problems can be formulated within the framework of variational calculus\, their solution for complex systems is often analytically and computationally intractable. To overcome this outstanding challenge\, we present AI Pontryagin\, a versatile control framework based on neural ordinary differential equations that automatically learns control signals that steer high-dimensional dynamical systems towards a desired target state within a specified time interval. We demonstrate the ability of AI Pontryagin to learn control signals that closely resemble those found by corresponding optimal control frameworks in terms of control energy and deviation from the desired target state. Our results suggest that AI Pontryagin is capable of solving a wide range of control and optimization problems\, including those that are analytically intractable
URL:https://www.ibs.re.kr/bimag/event/2022-07-05-jc/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220630T090000
DTEND;TZID=Asia/Seoul:20220701T180000
DTSTAMP:20260507T031542
CREATED:20220629T150000Z
LAST-MODIFIED:20220818T012202Z
UID:5844-1656579600-1656698400@www.ibs.re.kr
SUMMARY:Korea Biological Rhythms Society (KBRS) Symposium
DESCRIPTION:Korea Biological Rhythms Society (KBRS) Symposium\n(한국분자·세포생물학회 생체리듬준분과 심포지엄)\nOfficial Website \nDate\n30 June 2022 (Thursday) – 1 July 2022 (Friday) \nVenue\nIBS Science Culture Center \nProgram\nThe detailed information will be updated. \n 
URL:https://www.ibs.re.kr/bimag/event/202206kbrs/
LOCATION:IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Workshops and Conferences
ATTACH;FMTTYPE=image/png:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2022/06/220623_포스터_v2.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220623T123000
DTEND;TZID=Asia/Seoul:20220623T133000
DTSTAMP:20260507T031542
CREATED:20220622T183000Z
LAST-MODIFIED:20220623T060141Z
UID:6104-1655987400-1655991000@www.ibs.re.kr
SUMMARY:Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering t-SNE\, UMAP\, TriMAP\, and PaCMAP for Data Visualization
DESCRIPTION:We will discuss about “Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering t-SNE\, UMAP\, TriMAP\, and PaCMAP for Data Visualization”\, Wang\, Yingfan\, et al.\, J. Mach. Learn. Res.\, 2021. \nAbstract: Dimension reduction (DR) techniques such as t-SNE\, UMAP\, and TriMAP have demonstrated impressive visualization performance on many real world datasets. One tension that has always faced these methods is the trade-off between preservation of global structure and preservation of local structure: these methods can either handle one or the other\, but not both. In this work\, our main goal is to understand what aspects of DR methods are important for preserving both local and global structure: it is difficult to design a better method without a true understanding of the choices we make in our algorithms and their empirical impact on the lower-dimensional embeddings they produce. Towards the goal of local structure preservation\, we provide several useful design principles for DR loss functions based on our new understanding of the mechanisms behind successful DR methods. Towards the goal of global structure preservation\, our analysis illuminates that the choice of which components to preserve is important. We leverage these insights to design a new algorithm for DR\, called Pairwise Controlled Manifold Approximation Projection (PaCMAP)\, which preserves both local and global structure. Our work provides several unexpected insights into what design choices both to make and avoid when constructing DR algorithms.
URL:https://www.ibs.re.kr/bimag/event/2022-06-23-jc/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220616T160000
DTEND;TZID=Asia/Seoul:20220616T170000
DTSTAMP:20260507T031542
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:20220616T130000
DTEND;TZID=Asia/Seoul:20220616T140000
DTSTAMP:20260507T031542
CREATED:20220615T190000Z
LAST-MODIFIED:20220623T060231Z
UID:6124-1655384400-1655388000@www.ibs.re.kr
SUMMARY:Identifying the critical states of complex diseases by the dynamic change of multivariate distribution
DESCRIPTION:We will discuss about “Identifying the critical states of complex diseases by the dynamic change of multivariate distribution”\, Peng\, Hao\, et al.\, Briefings in Bioinformatics\, 2022. \nAbstract: The dynamics of complex diseases are not always smooth; they are occasionally abrupt\, i.e. there is a critical state transition or tipping point at which the disease undergoes a sudden qualitative shift. There are generally a few significant differences in the critical state in terms of gene expressions or other static measurements\, which may lead to the failure of traditional differential expression-based biomarkers to identify such a tipping point. In this study\, we propose a computational method\, the direct interaction network-based divergence\, to detect the critical state of complex diseases by exploiting the dynamic changes in multivariable distributions inferred from observable samples and local biomolecular direct interaction networks. Such a method is model-free and applicable to both bulk and single-cell expression data. Our approach was validated by successfully identifying the tipping point just before the occurrence of a critical transition for both a simulated data set and seven real data sets\, including those from The Cancer Genome Atlas and two single-cell RNA-sequencing data sets of cell differentiation. Functional and pathway enrichment analyses also validated the computational results from the perspectives of both molecules and networks.
URL:https://www.ibs.re.kr/bimag/event/2022-06-16-jc-2/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220615T160000
DTEND;TZID=Asia/Seoul:20220615T170000
DTSTAMP:20260507T031542
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:20260507T031542
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:20260507T031542
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:20220603T170000
DTEND;TZID=Asia/Seoul:20220603T180000
DTSTAMP:20260507T031542
CREATED:20220602T230000Z
LAST-MODIFIED:20220525T133819Z
UID:6020-1654275600-1654279200@www.ibs.re.kr
SUMMARY:[사전 등록 필요] 논문 글쓰기 워크샵 2/2 – 영어 논문 쓰기: 두려움을 성취로 바꾸는 길 (박영민 연구원님)
DESCRIPTION:2022년 6월 3일 오후 5시 – 6시\, 부산교육정책연구소 박영민 연구원님의 논문 글쓰기 워크샵 강의가 있습니다. 참가를 원하시는 분은 구글 폼(링크)에서 사전 등록을 해주시기 바랍니다. \n[요약] 이 ‘영어 논문 쓰기’ 워크숍은 현재의 영어 수준이나 과거의 영어 학습 경험과 상관 없이 누구나 영어 논문 쓰기를 시작할 수 있는 방법에 관한 것입니다. 우선 영어에 대한 막연한 두려움\, 과거 경험으로 인한 자신감 부족\, 게다가 ‘쓰기’라는 쉽지 않은 인지 활동\, 심지어 논문이라는 큰 벽\, 혹은 섣부른 자신감 등 ‘영어 논문 쓰기’를 방해하는 요인을 생각해 봅니다. 이런 요인을 자세하게 들여다보면 각각의 걸림돌을 넘어갈 방법도 명쾌하게 발견할 수 있습니다. 이 세미나에서 다룰 구체적 내용은 다음과 같습니다. \n\n\n\n한국인들이 ‘영어’와 ‘영어 쓰기’를 어렵게 느끼는 원인 이해하고 극복하기\n‘읽기’와 ‘쓰기’의 서로 다른 두 가지 인지활동의 관련성 이해하고 적용하기\n논문에 적합한 단어\, 시제\, 구두점 선택하고 사용하기\n영문초록\, 제목\, 소제목 스타일 이해하고 작성하기\n영어논문 쓰기를 돕는 디지털 도구 선택하고 활용하기\n\n\n\n이 워크숍에서 안내될 몇 가지 방법은 영어 논문 쓰기가 더 이상 두려운 것이 아닌 연구자로서의 목표를 이루는 디딤돌이 되도록 할 것입니다.
URL:https://www.ibs.re.kr/bimag/event/writing-papers-workshop2/
LOCATION:Conference room\, (B109)\, Daejeon\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Workshops and Conferences
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2022/06/XL.jpeg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220603T160000
DTEND;TZID=Asia/Seoul:20220603T170000
DTSTAMP:20260507T031542
CREATED:20220602T220000Z
LAST-MODIFIED:20220525T133653Z
UID:6016-1654272000-1654275600@www.ibs.re.kr
SUMMARY:[사전 등록 필요] 논문 글쓰기 워크샵 1/2 - 논문 작성 원리: ABC 논문 작성법 (원병묵 교수님)
DESCRIPTION:2022년 6월 3일 오후 4시 – 5시\, 성균관대 신소재공학부의 원병묵 교수님의 논문 글쓰기 워크샵 강의가 있습니다. 참가를 원하시는 분은 구글 폼(링크)에서 사전 등록을 해주시기 바랍니다. \n[요약] \n논문은 저자와 독자 사이의 학문적 소통을 위한 논리적인 글이다. 이번 강연을 통해 논문을 작성하기 위한 기본 원리를 배울 수 있다. 특히\, 연구가 거의 마무리되는 시점에 (After completing your research)\, 연구 결과를 그림과 표로 잘 정리한 다음에 (Based on well-organized figures and tables)\, 본격적으로 논문 작성을 시작하는 (Compose your manuscript from a title to a conclusion) ‘ABC 논문 작성법’을 소개한다. 논문 작성의 준비 과정으로 (A와 B의 과정)\, 연구 노트 작성 방법\, 저널 클럽 운영 방법\, 한 페이지 활용 방법을 설명한다. 논문 작성 준비가 완료되면\, 제목부터 결론까지 순서대 로 논문 원고를 작성할 수 있다 (C의 과정). 이렇게 하면\, 단기간에 집중하여 효율적으 로 논문을 작성할 수 있다. \n*참고: 원병묵 교수의 과학 논문 쓰는 법
URL:https://www.ibs.re.kr/bimag/event/writing-paper-workshop1/
LOCATION:Conference room\, (B109)\, Daejeon\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Workshops and Conferences
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2022/05/writingpaper.jpeg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220603T130000
DTEND;TZID=Asia/Seoul:20220603T140000
DTSTAMP:20260507T031542
CREATED:20220525T170000Z
LAST-MODIFIED:20220529T181413Z
UID:5986-1654261200-1654264800@www.ibs.re.kr
SUMMARY:Approximating Solutions of the Chemical Master Equation using Neural Networks
DESCRIPTION:We will discuss about “Approximating Solutions of the Chemical Master Equation using Neural Networks”\, Sukys et al.\, bioRxiv\, 2022 \nAbstract: The Chemical Master Equation (CME) provides an accurate description of stochastic biochemical reaction networks in well-mixed conditions\, but it cannot be solved analytically for most systems of practical interest. While Monte Carlo methods provide a principled means to probe the system dy- namics\, their high computational cost can render the estimation of molecule number distributions and other numerical tasks infeasible due to the large number of repeated simulations typically required. In this paper we aim to leverage the representational power of neural networks to approximate the solutions of the CME and propose a framework for Neural Estimation of Stochastic Simulations for Inference and Exploration (Nessie). Our approach is based on training a neural network to learn the distributions predicted by the CME from a relatively small number of stochastic simulations\, thereby accelerating computationally intensive tasks such as parameter exploration and inference. We show on biologically relevant examples that simple neural networks with one hidden layer are able to cap- ture highly complex distributions across parameter space. We provide a detailed discussion of the neural network implementation and code for easy reproducibility.
URL:https://www.ibs.re.kr/bimag/event/2022-06-03-jc/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220602T160000
DTEND;TZID=Asia/Seoul:20220602T170000
DTSTAMP:20260507T031542
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:20220601T170000
DTEND;TZID=Asia/Seoul:20220601T180000
DTSTAMP:20260507T031542
CREATED:20220531T223000Z
LAST-MODIFIED:20220317T001720Z
UID:5601-1654102800-1654106400@www.ibs.re.kr
SUMMARY:From live cell imaging to moment-based variational inference
DESCRIPTION:This talk will be presented online. Zoom link: 997 8258 4700 (pw: 1234) \nAbstract: Quantitative characterization of biomolecular networks is important for the analysis and design of network functionality. Reliable models of such networks need to account for intrinsic and extrinsic noise present in the cellular environment. Stochastic kinetic models provide a principled framework for developing quantitatively predictive tools in this scenario. Calibration of such models requires an experimental setup capable of monitoring a large number of individual cells over time\, automatic extraction of fluorescence levels for each cell and a scalable inference approach. In the first part of the talk we will cover our microfluidic setup and a deep-learning based approach to cell segmentation and data extraction. The second part will introduce moment-based variational inference as a scalable framework for approximate inference of kinetic models based on single cell data.
URL:https://www.ibs.re.kr/bimag/event/2022-06-01/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/png:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2022/01/HK_250x250.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220527T080000
DTEND;TZID=Asia/Seoul:20220529T170000
DTSTAMP:20260507T031542
CREATED:20220526T140000Z
LAST-MODIFIED:20220510T132002Z
UID:5879-1653638400-1653843600@www.ibs.re.kr
SUMMARY:KSIAM 2022 Spring Conference
DESCRIPTION:KSIAM 2022 Spring Conference\nDate\nMay 27\, 2022 (Friday) – May 29\, 2022 (Sunday) \nVenue\nDaejeon\, IBS \nProgram\nDetailed information will be updated. \nThe conference will be a joint meeting of the following 6 divisions: \n\n\n\nCombinatorics\nData Science & Machine Learning\nImaging Science\nIndustrial Mathematics\nInverse Problems\nMedical Mathematics\n\n\n\n 
URL:https://www.ibs.re.kr/bimag/event/ksiam-2022-spring-conference/
LOCATION:IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Workshops and Conferences
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2022/05/6C801094EB4A4DA7AB358A04BB799772.jpeg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220525T170000
DTEND;TZID=Asia/Seoul:20220525T180000
DTSTAMP:20260507T031542
CREATED:20220524T230000Z
LAST-MODIFIED:20220224T003504Z
UID:5609-1653498000-1653501600@www.ibs.re.kr
SUMMARY:Multi-resolution methods for modelling intracellular processes
DESCRIPTION:This talk will be presented online. Zoom link: 997 8258 4700 (pw: 1234) \nAbstract: I will discuss the development\, analysis and applications of multi-resolution methods for spatio-temporal modelling of intracellular processes\, which use (detailed) Brownian dynamics or molecular dynamics simulations in localized regions of particular interest (in which accuracy and microscopic details are important) and a (less-detailed) coarser model in other regions in which accuracy may be traded for simulation efficiency. I will discuss the error analysis and convergence properties of the developed multi-resolution methods\, their software implementation and applications of these multiscale methodologies to modelling of intracellular calcium dynamics\, actin dynamics and DNA dynamics. I will also discuss the development of multiscale methods which couple molecular dynamics and coarser stochastic models in the same dynamic simulation.
URL:https://www.ibs.re.kr/bimag/event/2022-05-25-2/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/png:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2022/01/RE_250x250.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220525T163000
DTEND;TZID=Asia/Seoul:20220525T170000
DTSTAMP:20260507T031542
CREATED:20220524T223000Z
LAST-MODIFIED:20220224T003158Z
UID:5606-1653496200-1653498000@www.ibs.re.kr
SUMMARY:Stochastic modelling of reaction-diffusion processes
DESCRIPTION:This talk will be presented online. Zoom link: 997 8258 4700 (pw: 1234) \nAbstract: I will introduce mathematical and computational methods for spatio-temporal modelling in molecular and cell biology\, including all-atom and coarse-grained molecular dynamics (MD)\, Brownian dynamics (BD)\, stochastic reaction-diffusion models and macroscopic mean-field equations. Microscopic (BD\, MD) models are based on the simulation of trajectories of individual molecules and their localized interactions (for example\, reactions). Mesoscopic (lattice-based) stochastic reaction-diffusion approaches divide the computational domain into a finite number of compartments and simulate the time evolution of the numbers of molecules in each compartment\, while macroscopic models are often written in terms of mean-field reaction-diffusion partial differential equations for spatially varying concentrations.
URL:https://www.ibs.re.kr/bimag/event/2022-05-25-1/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/png:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2022/01/RE_250x250.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220512T150000
DTEND;TZID=Asia/Seoul:20220512T160000
DTSTAMP:20260507T031542
CREATED:20220511T210000Z
LAST-MODIFIED:20220509T084329Z
UID:5983-1652367600-1652371200@www.ibs.re.kr
SUMMARY:Optimizing Oscillators for Specific Tasks Predicts Preferred Biochemical Implementations
DESCRIPTION:We will discuss about “Optimizing Oscillators for Specific Tasks Predicts Preferred Biochemical Implementations”\, Agrahar and  Rust.\, bioRxiv\, 2022. \nAbstract: Oscillatory processes are used throughout cell biology to control time-varying physiology including the cell cycle\, circadian rhythms\, and developmental patterning. It has long been understood that free-running oscillations require feedback loops where the activity of one component depends on the concentration of another. Oscillator motifs have been classified by the positive or negative net logic of these loops. However\, each feedback loop can be implemented by regulation of either the production step or the removal step. These possibilities are not equivalent because of the underlying structure of biochemical kinetics. By computationally searching over these possibilities\, we find that certain molecular implementations are much more likely to produce stable oscillations. These preferred molecular implementations are found in many natural systems\, but not typically in artificial oscillators\, suggesting a design principle for future synthetic biology. Finally\, we develop an approach to oscillator function across different reaction networks by evaluating the biosynthetic cost needed to achieve a given phase coherence. This analysis predicts that phase drift is most efficiently suppressed by delayed negative feedback lo op architectures that operate without positive feedback.
URL:https://www.ibs.re.kr/bimag/event/2022-05-12-jc/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220512T110000
DTEND;TZID=Asia/Seoul:20220512T120000
DTSTAMP:20260507T031542
CREATED:20220511T170000Z
LAST-MODIFIED:20220224T002809Z
UID:5599-1652353200-1652356800@www.ibs.re.kr
SUMMARY:Plasticity and balance in neuronal networks
DESCRIPTION:This talk will be presented online. Zoom link: 997 8258 4700 (pw: 1234) \nAbstract: I will first describe how to extend the theory of balanced networks to account for synaptic plasticity. This theory can be used to show when a plastic network will maintain balance\, and when it will be driven into an unbalanced state. I will next discuss how this approach provides evidence for a novel form of rapid compensatory inhibitory plasticity. Experimental evidence for such plasticity comes from optogenetic activation of excitatory neurons in primate visual cortex (area V1) which induces a population-wide dynamic reduction in the strength of neuronal interactions over the timescale of minutes during the awake state\, but not during rest. I will shift gears in the final part of the talk\, and discuss how community detection algorithms can help uncover the large scale organization of neuronal networks from connectome data.
URL:https://www.ibs.re.kr/bimag/event/2022-05-12-2/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/png:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2022/03/KJ_250x250.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220512T103000
DTEND;TZID=Asia/Seoul:20220512T110000
DTSTAMP:20260507T031542
CREATED:20220511T163000Z
LAST-MODIFIED:20220224T002732Z
UID:5596-1652351400-1652353200@www.ibs.re.kr
SUMMARY:Introduction to balanced networks
DESCRIPTION:This talk will be presented online. Zoom link: 997 8258 4700 (pw: 1234) \nAbstract: The idea of balance between excitation and inhibition is central in the theory of biological neural networks.  I will give a brief introduction to the concept of such balance\, and an overview of the mathematical ideas that can be used to study it.
URL:https://www.ibs.re.kr/bimag/event/2022-05-12-1/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/png:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2022/03/KJ_250x250.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220506T130000
DTEND;TZID=Asia/Seoul:20220506T140000
DTSTAMP:20260507T031542
CREATED:20220505T190000Z
LAST-MODIFIED:20220425T061007Z
UID:5980-1651842000-1651845600@www.ibs.re.kr
SUMMARY:The 103\,200-arm acceleration dataset in the UK Biobank revealed a landscape of human sleep phenotypes
DESCRIPTION:We will discuss about “The 103\,200-arm acceleration dataset in the UK Biobank revealed a landscape of human sleep phenotypes”\, Katori et al.\, PNAS\, 2022. \nAbstract: Human sleep phenotypes can be defined and diversified by both genetic and environmental factors. However\, some sleep phenotypes are difficult to evaluate without long-term\, precise sleep monitoring\, for which simple yet accurate sleep measurement is required. To solve this problem\, we recently developed a state-of-the-art sleep/wake classification algorithm based on wristband-type accelerometers\, termed ACCEL (acceleration-based classification and estimation of long-term sleep-wake cycles). In this study\, we optimized and applied ACCEL to large-scale analysis of human sleep phenotypes. The clustering of an about 100\,000-arm acceleration dataset in the UK Biobank using uniform manifold approximation and projection (UMAP) dimension reduction and density-based spatial clustering of applications with noise (DBSCAN) clustering methods identified 16 sleep phenotypes\, including those related to social jet lag\, chronotypes (“morning/night person”)\, and seven different insomnia-like phenotypes. Considering the complex relationship between sleep disorders and other psychiatric disorders\, these unbiased and comprehensive analyses of sleep phenotypes in humans will not only contribute to the advancement of biomedical research on genetic and environmental factors underlying human sleep patterns but also\, allow for the development of better digital biomarkers for psychiatric disorders.
URL:https://www.ibs.re.kr/bimag/event/2022-05-06-jc/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220429T130000
DTEND;TZID=Asia/Seoul:20220429T140000
DTSTAMP:20260507T031542
CREATED:20220329T103359Z
LAST-MODIFIED:20220329T103359Z
UID:5877-1651237200-1651240800@www.ibs.re.kr
SUMMARY:Toroidal topology of population activity in grid cells
DESCRIPTION:We will discuss about “Toroidal topology of population activity in grid cells”\, Gardner et al.\, Nature\, 2021. \nAbstract: The medial entorhinal cortex is part of a neural system for mapping the position of an individual within a physical environment. Grid cells\, a key component of this system\, fire in a characteristic hexagonal pattern of locations\, and are organized in modules that collectively form a population code for the animal’s allocentric position. The invariance of the correlation structure of this population code across environments and behavioral states\, independent of specific sensory inputs\, has pointed to intrinsic\, recurrently connected continuous attractor networks (CANs) as a possible substrate of the grid pattern. However\, whether grid cell networks show continuous attractor dynamics\, and how they interface with inputs from the environment\, has remained unclear owing to the small samples of cells obtained so far. Here\, using simultaneous recordings from many hundreds of grid cells and subsequent topological data analysis\, we show that the joint activity of grid cells from an individual module resides on a toroidal manifold\, as expected in a two-dimensional CAN. Positions on the torus correspond to the positions of the moving animal in the environment. Individual cells are preferentially active at singular positions on the torus. Their positions are maintained between environments and from wakefulness to sleep\, as predicted by CAN models for grid cells but not by alternative feedforward models. This demonstration of network dynamics on a toroidal manifold provides a population-level visualization of CAN dynamics in grid cells.
URL:https://www.ibs.re.kr/bimag/event/2022-04-29-jc/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220428T110000
DTEND;TZID=Asia/Seoul:20220428T120000
DTSTAMP:20260507T031542
CREATED:20220427T170000Z
LAST-MODIFIED:20220224T002639Z
UID:5593-1651143600-1651147200@www.ibs.re.kr
SUMMARY:Scaling behaviors in physiological fluctuations: relevance to circadian regulation and insights into the development of Alzheimer’s disease
DESCRIPTION:This talk will be presented online. Zoom link: 997 8258 4700 (pw: 1234) \nAbstract: Outputs from health biological systems display complex fluctuations that are not random but display robust and often self-similar (fractal) temporal correlations at different time scales— scaling behaviors. The scaling behaviors in the fluctuations of biological outputs such as neural activities\, cardiac dynamics\, motor activity are believed to be originated from feedbacks within the complex biological networks\, reflecting the system adaptability to internal and external inputs. Supporting this concept\, our studies have demonstrated a mechanistic link between the scaling regulation of physiological fluctuations and the circadian control system— a result of evolutionary adaptation to daily environmental light-dark cycles on the earth. In this talk\, I will discuss certain evidence for this ‘scaling-circadian’ link and its related implications. Moreover\, I will review some recent studies\, in which we examined how the scaling patterns of human motor activity fluctuations change with aging and in Alzheimer’s disease. Our results showed that (1) alterations in scaling activity patterns occur before the clinical manifestation of Alzheimer’s disease (i.e.\, cognitive impairment) and predict cognitive decline and the risk for Alzheimer’s dementia; and (2) the progression of Alzheimer’s disease accelerates the aging effect on the scaling activity patterns. Our work provides strong evidence that altered scaling activity patterns may also be a risk factor for neurodegeneration\, playing a role in the development and progression of Alzheimer’s disease.
URL:https://www.ibs.re.kr/bimag/event/2022-04-28/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/png:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2022/01/KH_250x250.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220422T130000
DTEND;TZID=Asia/Seoul:20220422T140000
DTSTAMP:20260507T031542
CREATED:20220421T190000Z
LAST-MODIFIED:20220329T005550Z
UID:5874-1650632400-1650636000@www.ibs.re.kr
SUMMARY:An Efficient Characterization of Complex-Balanced\, Detailed-Balanced\, and Weakly Reversible Systems
DESCRIPTION:We will discuss about “An Efficient Characterization of Complex-Balanced\, Detailed-Balanced\, and Weakly Reversible Systems”\, Craciun et al.\, SIAM Journal on Applied Mathematics\, 2020 \nAbstract: Very often\, models in biology\, chemistry\, physics\, and engineering are systems of polynomial or power-law ordinary differential equations\, arising from a reaction network. Such dynamical systems can be generated by many different reaction networks. On the other hand\, networks with special properties (such as reversibility or weak reversibility) are known or conjectured to give rise to dynamical systems that have special properties: existence of positive steady states\, persistence\, permanence\, and (for well-chosen parameters) complex balancing or detailed balancing. These last two are related to thermodynamic equilibrium\, and therefore the positive steady states are unique and stable. We describe a computationally efficient characterization of polynomial or power-law dynamical systems that can be obtained as complex-balanced\, detailed-balanced\, weakly reversible\, and reversible mass-action systems.
URL:https://www.ibs.re.kr/bimag/event/2022-04-22-jc/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220421T160000
DTEND;TZID=Asia/Seoul:20220421T170000
DTSTAMP:20260507T031542
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:20220415T110000
DTEND;TZID=Asia/Seoul:20220415T130000
DTSTAMP:20260507T031542
CREATED:20220414T182000Z
LAST-MODIFIED:20220414T012030Z
UID:5868-1650020400-1650027600@www.ibs.re.kr
SUMMARY:A topological data analysis based classifier
DESCRIPTION:We will discuss about “A topological data analysis based classifier”\, Kindelan et al.\, arXiv\, 2022 \nAbstract: Topological Data Analysis is an emergent field that aims to discover the underlying dataset’s topological information. Topological Data Analysis tools have been commonly used to create filters and topological descriptors to improve Machine Learning (ML) methods. This paper proposes a different Topological Data Analysis pipeline to classify balanced and imbalanced multi-class datasets without additional ML methods. Our proposed method was designed to solve multi-class problems. It resolves multi-class imbalanced classification problems with no data resampling preprocessing stage. The proposed Topological Data Analysis-based classifier builds a filtered simplicial complex on the dataset representing high-order data relationships. Following the assumption that a meaningful sub-complex exists in the filtration that approximates the data topology\, we apply Persistent Homology to guide the selection of that sub-complex by considering detected topological features. We use each unlabeled point’s link and star operators to provide different sized and multi-dimensional neighborhoods to propagate labels from labeled to unlabeled points. The labeling function depends on the filtration entire history of the filtered simplicial complex and is encoded within the persistent diagrams at various dimensions. We select eight datasets with different dimensions\, degrees of class overlap\, and imbalanced samples per class. The TDABC outperforms all baseline methods classifying multi-class imbalanced data with high imbalanced ratios and data with overlapped classes. Also\, on average\, the proposed method was better than KNN and weighted-KNN and behaved competitively with SVM and Random Forest baseline classifiers in balanced datasets.
URL:https://www.ibs.re.kr/bimag/event/2022-04-15-jc/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
END:VCALENDAR