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:20220602T160000
DTEND;TZID=Asia/Seoul:20220602T170000
DTSTAMP:20260424T165240
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:20260424T165240
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:20220525T170000
DTEND;TZID=Asia/Seoul:20220525T180000
DTSTAMP:20260424T165240
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:20260424T165240
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:20260424T165240
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:20260424T165240
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:20260424T165240
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:20260424T165240
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:20260424T165240
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:20260424T165240
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:20260424T165240
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:20260424T165240
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:20260424T165240
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
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220414T110000
DTEND;TZID=Asia/Seoul:20220414T120000
DTSTAMP:20260424T165240
CREATED:20220413T170000Z
LAST-MODIFIED:20220224T002525Z
UID:5591-1649934000-1649937600@www.ibs.re.kr
SUMMARY:A systems biology approach using multi-scale modeling to understand the immune response to tuberculosis infection and treatment
DESCRIPTION:This talk will be presented online. Zoom link: 997 8258 4700 (pw: 1234) \nAbstract: Tuberculosis (TB) is one of the world’s deadliest infectious diseases. Caused by the pathogen Mycobacterium tuberculosis (Mtb)\, the standard regimen for treating TB consists of treatment with multiple antibiotics for at least six months. There are a number of complicating factors that contribute to the need for this long treatment duration and increase the risk of treatment failure. The structure of granulomas\, lesions forming in lungs in response to Mtb infection\, create heterogeneous antibiotic distributions that limit antibiotic exposure to Mtb.   We can use a systems biology approach pairing experimental data from non-human primates with computational modeling to represent and predict how factors impact antibiotic regimen efficacy and granuloma bacterial sterilization. We utilize an agent-based\, computational model that simulates granuloma formation\, function and treatment\, called GranSim.  A goal in improving antibiotic treatment for TB is to find regimens that can shorten the time it takes to sterilize granulomas while minimizing the amount of antibiotic required. We also created a whole host model\, called HOSTSIM\, to study Mtb dynamics within a human host.  Overall\, we use these models to help better understand TB treatment and strengthen our ability to predict regimens that can improve clinical treatment of TB.
URL:https://www.ibs.re.kr/bimag/event/2022-04-14-2/
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/DK_250x250.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220414T103000
DTEND;TZID=Asia/Seoul:20220414T110000
DTSTAMP:20260424T165240
CREATED:20220413T163000Z
LAST-MODIFIED:20220130T045637Z
UID:5588-1649932200-1649934000@www.ibs.re.kr
SUMMARY:An overview of methods used for multi-scale modeling and analysis
DESCRIPTION:This talk will be presented online. Zoom link: 997 8258 4700 (pw: 1234) \nAbstract: TBA
URL:https://www.ibs.re.kr/bimag/event/2022-04-14-1/
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/DK_250x250.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220408T130000
DTEND;TZID=Asia/Seoul:20220408T140000
DTSTAMP:20260424T165240
CREATED:20220407T190000Z
LAST-MODIFIED:20220405T042614Z
UID:5870-1649422800-1649426400@www.ibs.re.kr
SUMMARY:RTransferEntropy — Quantifying information flow between different time series using effective transfer entropy
DESCRIPTION:We will discuss about “RTransferEntropy — Quantifying information flow between different time series using effective transfer entropy”\, Behrendt et al.\, SoftwareX\, 2019 \nAbstract: This paper shows how to quantify and test for the information flow between two time series with Shannon transfer entropy and Rényi transfer entropy using the R package RTransferEntropy. We discuss the methodology\, the bias correction applied to calculate effective transfer entropy and outline how to conduct statistical inference. Furthermore\, we describe the package in detail and demonstrate its functionality by means of several simulated processes and present an application to financial time series.
URL:https://www.ibs.re.kr/bimag/event/2022-04-08-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:20220407T110000
DTEND;TZID=Asia/Seoul:20220407T120000
DTSTAMP:20260424T165240
CREATED:20220406T170000Z
LAST-MODIFIED:20220224T002321Z
UID:5585-1649329200-1649332800@www.ibs.re.kr
SUMMARY:Universal biology in adaptation and evolution: dimensional reduction\, and fluctuation-response relationship
DESCRIPTION:This talk will be presented online. Zoom link: 997 8258 4700 (pw: 1234) \nAbstract: A macroscopic theory for cellular states with steady-growth is presented\, based on consistency between cellular growth and molecular replication\, together with robustness of phenotypes against perturbations. Adaptive changes in high-dimensional phenotypes are shown to be restricted within a low-dimensional slow manifold\, from which a macroscopic law for cellular states is derived\, as is confirmed by adaptation experiments of bacteria under stress. The theory is extended to phenotypic evolution\, leading to proportionality between phenotypic responses against genetic evolution and by environmental adaptation\, which explains the evolutionary fluctuation-response relationship previously uncovered.   \nReferences \n\n Kaneko K.\, Life: An Introduction to Complex Systems Biology\, Springer (2006)\n K. Kaneko\, C.Furusawa\, T. Yomo\, “Macroscopic phenomenology for cells in steady-growth state”\, Phys.Rev.X(2015) 011014\n C. Furusawa\, K. Kaneko “Global Relationships in Fluctuation and Response in Adaptive Evolution”\, J of Royal Society Interface 12(2015)\, 20150482.\n C. Furusawa\, K. Kaneko ” Formation of Dominant Mode by Evolution in Biological Systems” Phys. Rev. E 97(2018)042410\n K. Kaneko\, C. Furusawa “Macroscopic Theory for Evolving Biological Systems Akin to Thermodynamics”\, Annual Rev. Biophys. (2018) 47\, 273-290\n A. Sakata and K. Kaneko\, “Dimensional Reduction in Evolving Spin-Glass Model: Correlation of Phenotypic Responses to Environmental and Mutational Changes”\, Phys. Rev. Lett. (2020) 124\, 218101\n Q-Y. Tang and K. Kaneko\, “ Dynamics-evolution correspondence in protein structures”\,  Phys. Rev. Lett. (2021) 127\, 098103
URL:https://www.ibs.re.kr/bimag/event/2022-04-07/
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/Kunihiko-Kaneko.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220401T130000
DTEND;TZID=Asia/Seoul:20220401T140000
DTSTAMP:20260424T165240
CREATED:20220331T190000Z
LAST-MODIFIED:20220320T093117Z
UID:5564-1648818000-1648821600@www.ibs.re.kr
SUMMARY:Physics-informed learning of governing equations from scarce data
DESCRIPTION:We will discuss about “Physics-informed learning of governing equations from scarce data”\, Chen et al.\, Nature Communications\, 2021 \nAbstract: Extracting governing equations from data is a central challenge in many diverse areas of science and engineering. Data are abundant whereas models often remain elusive\, as in climate science\, neuroscience\, ecology\, finance\, and epidemiology\, to name only a few examples. In this work\, we combine sparsity-promoting techniques and machine learning with nonlinear dynamical systems to discover governing equations from noisy measurement data. The only assumption about the structure of the model is that there are only a few important terms that govern the dynamics\, so that the equations are sparse in the space of possible functions; this assumption holds for many physical systems in an appropriate basis. In particular\, we use sparse regression to determine the fewest terms in the dynamic governing equations required to accurately represent the data. This results in parsimonious models that balance accuracy with model complexity to avoid overfitting. We demonstrate the algorithm on a wide range of problems\, from simple canonical systems\, including linear and nonlinear oscillators and the chaotic Lorenz system\, to the fluid vortex shedding behind an obstacle. The fluid example illustrates the ability of this method to discover the underlying dynamics of a system that took experts in the community nearly 30 years to resolve. We also show that this method generalizes to parameterized systems and systems that are time-varying or have external forcing.
URL:https://www.ibs.re.kr/bimag/event/2022-04-01/
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:20220331T110000
DTEND;TZID=Asia/Seoul:20220331T120000
DTSTAMP:20260424T165240
CREATED:20220330T170000Z
LAST-MODIFIED:20220317T000754Z
UID:5582-1648724400-1648728000@www.ibs.re.kr
SUMMARY:Design principles of physiological circuits
DESCRIPTION:This talk will be presented online. Zoom link: 997 8258 4700 (pw: 1234) \nAbstract: We will discuss hormone circuits and their dynamics using new models that take into account timescales of weeks due to growth of the hormone glands. This explains some mysteries in diabetes and autoimmune disease.
URL:https://www.ibs.re.kr/bimag/event/2022-03-31/
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/UA_250x250.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220325T130000
DTEND;TZID=Asia/Seoul:20220325T140000
DTSTAMP:20260424T165240
CREATED:20220317T190000Z
LAST-MODIFIED:20220224T015444Z
UID:5562-1648213200-1648216800@www.ibs.re.kr
SUMMARY:Universal structural requirements for maximal robust perfect adaptation in biomolecular networks
DESCRIPTION:Abstract: Consider a biomolecular reaction network that exhibits robust perfect adaptation to disturbances from several parallel sources. The well-known Internal Model Principle of control theory suggests that such systems must include a subsystem (called the “internal model”) that is able to recreate the dynamic structure of the disturbances. This requirement poses certain structural constraints on the network which we elaborate in this paper for the scenario where constant-in-time disturbances maximally affect network interactions and there is model uncertainty and possible stochasticity in the dynamics. We prove that these structural constraints are primarily characterized by a simple linear-algebraic stoichiometric condition which remains the same for both deterministic and stochastic descriptions of the dynamics. Our results reveal the essential requirements for maximal robust perfect adaptation in biology\, with important implications for both systems and synthetic biology. We exemplify our results through many known examples of robustly adapting networks and we construct new examples of such networks with the aid of our linear-algebraic characterization.
URL:https://www.ibs.re.kr/bimag/event/2022-03-18/
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:20220324T110000
DTEND;TZID=Asia/Seoul:20220324T120000
DTSTAMP:20260424T165240
CREATED:20220323T170000Z
LAST-MODIFIED:20220224T002127Z
UID:5579-1648119600-1648123200@www.ibs.re.kr
SUMMARY:Topological data analysis of spatial systems
DESCRIPTION:This talk will be presented online. Zoom link: 997 8258 4700 (pw: 1234) \nAbstract: From the venation patterns of leaves to spider webs\, roads in cities\, social networks\, and the spread of COVID-19 infections and vaccinations\, the structure of many systems is influenced significantly by space. In this talk\, I will discuss the application of topological data analysis (specifically\, persistent homology) to spatial systems. I will present a few examples\, such as voting in presidential elections\, city street networks\, spatiotemporal dynamics of COVID-19 infections and vaccinations\, and webs that were spun by spiders under the influence of various drugs.
URL:https://www.ibs.re.kr/bimag/event/2022-03-24-2/
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/MP_250x250.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220324T103000
DTEND;TZID=Asia/Seoul:20220324T110000
DTSTAMP:20260424T165240
CREATED:20220323T163000Z
LAST-MODIFIED:20220324T045408Z
UID:5575-1648117800-1648119600@www.ibs.re.kr
SUMMARY:Introduction to topological data analysis
DESCRIPTION:This talk will be presented online. Zoom link: 997 8258 4700 (pw: 1234) \nAbstract: I will give an introduction to topological data analysis (TDA)\, in which one uses ideas from algebraic topology to study the “shape” of data. I will focus on persistent homology (PH)\, which is the most common approach in TDA.
URL:https://www.ibs.re.kr/bimag/event/2022-03-24-1/
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/MP_250x250.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220318T130000
DTEND;TZID=Asia/Seoul:20220318T140000
DTSTAMP:20260424T165240
CREATED:20220310T190000Z
LAST-MODIFIED:20220224T015419Z
UID:5560-1647608400-1647612000@www.ibs.re.kr
SUMMARY:Data-driven discovery of coordinates and governing equations
DESCRIPTION:Abstract: The discovery of governing equations from scientific data has the potential to transform data-rich fields that lack well-characterized quantitative descriptions. Advances in sparse regression are currently enabling the tractable identification of both the structure and parameters of a nonlinear dynamical system from data. The resulting models have the fewest terms necessary to describe the dynamics\, balancing model complexity with descriptive ability\, and thus promoting interpretability and generalizability. This provides an algorithmic approach to Occam’s razor for model discovery. However\, this approach fundamentally relies on an effective coordinate system in which the dynamics have a simple representation. In this work\, we design a custom deep autoencoder network to discover a coordinate transformation into a reduced space where the dynamics may be sparsely represented. Thus\, we simultaneously learn the governing equations and the associated coordinate system. We demonstrate this approach on several example high-dimensional systems with low-dimensional behavior. The resulting modeling framework combines the strengths of deep neural networks for flexible representation and sparse identification of nonlinear dynamics (SINDy) for parsimonious models. This method places the discovery of coordinates and models on an equal footing.
URL:https://www.ibs.re.kr/bimag/event/2022-03-11/
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:20220311T130000
DTEND;TZID=Asia/Seoul:20220311T140000
DTSTAMP:20260424T165240
CREATED:20220303T190000Z
LAST-MODIFIED:20220224T015356Z
UID:5558-1647003600-1647007200@www.ibs.re.kr
SUMMARY:Transcription factor competition facilitates self-sustained oscillations in single gene genetic circuits
DESCRIPTION:Abstract: Genetic feedback loops can be used by cells as a means to regulate internal processes or keep track of time. It is often thought that\, for a genetic circuit to display self-sustained oscillations\, a degree of cooperativity is needed in the binding and unbinding of actor species. This cooperativity is usually modeled using a Hill function\, regardless of the actual promoter architecture. Moreover\, genetic circuits do not operate in isolation and often transcription factors are shared between different promoters. In this work we show how mathematical modelling of genetic feedback loops can be facilitated with a mechanistic fold-change function that takes into account the titration effect caused by competing binding sites for transcription factors. The model shows how the titration effect aids self-sustained oscillations in a minimal genetic feedback loop: a gene that produces its own repressor directly — without cooperative transcription factor binding. The use of delay differential equations leads to a stability contour that predicts whether a genetic feedback loop will show self-sustained oscillations\, even when taking the bursty nature of transcription into account. \n 
URL:https://www.ibs.re.kr/bimag/event/2022-03-04/
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:20220304T130000
DTEND;TZID=Asia/Seoul:20220304T140000
DTSTAMP:20260424T165240
CREATED:20220224T190000Z
LAST-MODIFIED:20220224T015333Z
UID:5556-1646398800-1646402400@www.ibs.re.kr
SUMMARY:Modeling polypharmacy side effects with graph convolutional networks
DESCRIPTION:We will discuss about “Modeling polypharmacy side effects with graph convolutional networks”\, Zitnik\, Agrawal\, and Leskovec\, Bioinformatics\, 2018 \nMotivation\nThe use of drug combinations\, termed polypharmacy\, is common to treat patients with complex diseases or co-existing conditions. However\, a major consequence of polypharmacy is a much higher risk of adverse side effects for the patient. Polypharmacy side effects emerge because of drug-drug interactions\, in which activity of one drug may change\, favorably or unfavorably\, if taken with another drug. The knowledge of drug interactions is often limited because these complex relationships are rare\, and are usually not observed in relatively small clinical testing. Discovering polypharmacy side effects thus remains an important challenge with significant implications for patient mortality and morbidity. \nResults\nHere\, we present Decagon\, an approach for modeling polypharmacy side effects. The approach constructs a multimodal graph of protein-protein interactions\, drug-protein target interactions and the polypharmacy side effects\, which are represented as drug-drug interactions\, where each side effect is an edge of a different type. Decagon is developed specifically to handle such multimodal graphs with a large number of edge types. Our approach develops a new graph convolutional neural network for multirelational link prediction in multimodal networks. Unlike approaches limited to predicting simple drug-drug interaction values\, Decagon can predict the exact side effect\, if any\, through which a given drug combination manifests clinically. Decagon accurately predicts polypharmacy side effects\, outperforming baselines by up to 69%. We find that it automatically learns representations of side effects indicative of co-occurrence of polypharmacy in patients. Furthermore\, Decagon models particularly well polypharmacy side effects that have a strong molecular basis\, while on predominantly non-molecular side effects\, it achieves good performance because of effective sharing of model parameters across edge types. Decagon opens up opportunities to use large pharmacogenomic and patient population data to flag and prioritize polypharmacy side effects for follow-up analysis via formal pharmacological studies.
URL:https://www.ibs.re.kr/bimag/event/2022-02-25/
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:20220303T110000
DTEND;TZID=Asia/Seoul:20220303T120000
DTSTAMP:20260424T165240
CREATED:20220302T170000Z
LAST-MODIFIED:20220224T001605Z
UID:5529-1646305200-1646308800@www.ibs.re.kr
SUMMARY:Spatiotemporal reconstruction of static single-cell genomics data
DESCRIPTION:This talk will be presented online. Zoom link: 997 8258 4700 (pw: 1234) \nAbstract: Cells make fate decisions in response to dynamic environments and multicellular structure emerges from interplays among cells in space and time. The recent single-cell genomics technology provides an unprecedented opportunity to profile cells. However\, those measurements are taken as snapshots for groups of individual cells with only static information. Can one infer interactions among cells from such datasets? Is it possible to recover spatial information from non-spatial datasets? How to obtain temporal relationships of cells from the static measurements? In this talk I will present our newly developed computational tools that reconstruct interactions and spatiotemporal relationships for cells using single-cell RNA-seq\, ATAC-seq\, and spatial transcriptomics datasets. Through applications of those methods to systems in development and regeneration\, we show the discovery power of such methods and identify areas for further development in spatiotemporal reconstruction.
URL:https://www.ibs.re.kr/bimag/event/2022-03-03/
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/QN_250x250.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220218T130000
DTEND;TZID=Asia/Seoul:20220218T140000
DTSTAMP:20260424T165240
CREATED:20220130T031904Z
LAST-MODIFIED:20220130T031904Z
UID:5554-1645189200-1645192800@www.ibs.re.kr
SUMMARY:A Deficiency-Based Approach to Parametrizing Positive Equilibria of Biochemical Reaction Systems
DESCRIPTION:We will discuss about “A Deficiency-Based Approach to Parametrizing Positive Equilibria of Biochemical Reaction Systems”\, Johnston\, Müller\, and Pantea\, Bulletin of Mathematical Biology\, 2019 \nWe present conditions which guarantee a parametrization of the set of positive equilibria of a generalized mass-action system. Our main results state that (1) if the underlying generalized chemical reaction network has an effective deficiency of zero\, then the set of positive equilibria coincides with the parametrized set of complex-balanced equilibria and (2) if the network is weakly reversible and has a kinetic deficiency of zero\, then the equilibrium set is nonempty and has a positive\, typically rational\, parametrization. Via the method of network translation\, we apply our results to classical mass-action systems studied in the biochemical literature\, including the EnvZ–OmpR and shuttled WNT signaling pathways. A parametrization of the set of positive equilibria of a (generalized) mass-action system is often a prerequisite for the study of multistationarity and allows an easy check for the occurrence of absolute concentration robustness\, as we demonstrate for the EnvZ–OmpR pathway.
URL:https://www.ibs.re.kr/bimag/event/2022-02-18/
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:20220211T130000
DTEND;TZID=Asia/Seoul:20220211T140000
DTSTAMP:20260424T165240
CREATED:20220210T190000Z
LAST-MODIFIED:20220208T054847Z
UID:5552-1644584400-1644588000@www.ibs.re.kr
SUMMARY:Phiclust: a clusterability measure for single-cell transcriptomics reveals phenotypic subpopulations
DESCRIPTION:We will discuss about “Phiclust: a clusterability measure for single-cell transcriptomics reveals phenotypic subpopulations”\, Mircea et al.\, 2022\, Genome Biology \nThe ability to discover new cell phenotypes by unsupervised clustering of single-cell transcriptomes has revolutionized biology. Currently\, there is no principled way to decide whether a cluster of cells contains meaningful subpopulations that should be further resolved. Here\, we present phiclust (ϕ_clust)\, a clusterability measure derived from random matrix theory that can be used to identify cell clusters with non-random substructure\, testably leading to the discovery of previously overlooked phenotypes.
URL:https://www.ibs.re.kr/bimag/event/2022-02-11/
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:20220208T113000
DTEND;TZID=Asia/Seoul:20220208T120000
DTSTAMP:20260424T165240
CREATED:20220208T173000Z
LAST-MODIFIED:20220207T064404Z
UID:5673-1644319800-1644321600@www.ibs.re.kr
SUMMARY:수리모델을 통한 전염병 통제 분석
DESCRIPTION:Abstract: TBA
URL:https://www.ibs.re.kr/bimag/event/2022-02-09-2/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Biomedical Mathematics Seminar
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220208T110000
DTEND;TZID=Asia/Seoul:20220208T113000
DTSTAMP:20260424T165240
CREATED:20220208T170000Z
LAST-MODIFIED:20220207T064429Z
UID:5670-1644318000-1644319800@www.ibs.re.kr
SUMMARY:Stochastic Modeling of Foot and Mouth Diseases with Vehicle Network & Assessment of Social Distancing for Controlling COVID-19 in Korea
DESCRIPTION:Abstract: TBA
URL:https://www.ibs.re.kr/bimag/event/2022-02-09/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Biomedical Mathematics Seminar
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
END:VCALENDAR