Kyongwon Kim, On sufficient graphical models

B378 Seminar room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Korea, Republic of

We introduce a sufficient graphical model by applying the recently developed nonlinear sufficient dimension reduction techniques to the evaluation of conditional independence. The graphical model is nonparametric in nature, as it does not make distributional assumptions such as the Gaussian or copula Gaussian assumptions. However, unlike a fully nonparametric graphical model, which relies on the

Nonparametric predictive model for sparse and irregular longitudinal data

B378 Seminar room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Korea, Republic of

We propose a kernel-based estimator to predict the mean response trajectory for sparse and irregularly measured longitudinal data. The kernel estimator is constructed by imposing weights based on the subject-wise similarity on L2 metric space between predictor trajectories, where we assume that an analogous fashion in predictor trajectories over time would result in a similar

Seonjin Kim, Nonparametric vs Parametric Regression

B378 Seminar room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Korea, Republic of

To understand nonparametric regression, we should know first what the parametric model is. Simply speaking, the parametric regression model consists of many assumptions and the nonparametric regression model eases the assumptions. I will introduce what assumptions the parametric regression model has and how the nonparametric regression model relieves them. In addition, their pros and cons will

Jonathan Rubin, Multiple timescale modeling for neural systems

B378 Seminar room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Korea, Republic of

Abstract Mathematical models of biological systems, including neurons, often feature components that evolve on very different timescales. Mathematical analysis of these multi-timescale systems can be greatly simplified by partitioning them into subsystems that evolve on different time scales. The subsystems are then analyzed semi-independently, using a technique called fast-slow analysis. I will briefly describe the

Hyung Jin Choi, A Normative Framework Dissociates Need and Motivation in Hypothalamic Neurons

B232 Seminar Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Daejeon, Korea, Republic of

Abstract: Physiological needs evoke motivational drives to produce natural behaviours for survival. However, the temporally intertwined dynamics of need and motivation have made it challenging to differentiate these two components in previous experimental paradigms. Based on classic homeostatic theories, we established a normative framework to derive computational models of neural activity and behaviours for need-encoding

Junil Kim, TENET+: a tool for reconstructing gene networks by integrating single cell expression and chromatin accessibility data

B232 Seminar Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Daejeon, Korea, Republic of

Abstract: 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

Jong Kyoung Kim, Dissecting cellular heterogeneity and plasticity in adipose tissue

B232 Seminar Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Daejeon, Korea, Republic of

Abstract: Cell-to-cell variability in gene expression exists even in a homogeneous population of cells. Dissecting such cellular heterogeneity within a biological system is a prerequisite for understanding how a biological system is developed, homeostatically regulated, and responds to external perturbations. Single-cell RNA sequencing (scRNA-seq) allows the quantitative and unbiased characterization of cellular heterogeneity by providing

Kang MIn Lee, Oscillation in brain and its potential role in inter-areal communication

B232 Seminar Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Daejeon, Korea, Republic of

Abstract: Through the past decades, electrophysiological experiments have revealed that extracellular electrical potential of brain show diverse rhythmic activity. Called ‘Local Field Potential(LFP)’, those rhythmic activities are thought to reflect populational activity of neurons. In this talk, I will introduce basic concepts on LFP and its generation mechanisms. Then, roles of LFP in brain inter-areal

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