Inferring causality in biological oscillators
B378 Seminar room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Korea, Republic ofAbstract TBA
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This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234) Abstract: Chronotherapeutics- that is administering drugs following the patient's biological rhythms over the 24 h span- may largely impact on both drug toxicities and efficacy in various pathologies including cancer . However, recent findings highlight the critical need of personalizing circadian delivery …
(1) GCN and its Application. We introduce the GCN by reviewing the monumental paper " Semi-Supervised Classification with the Graph Convolutional Networks", ICLR 2018 by Kipf and Welling. We are going to much detail the algorithm of message aggregation and passings and learning processes. Code ; https://github.com/tkipf/gcn (2) Graph Attention networks(GAT) and its Applications. Bengio …
This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234) Abstract: From fertilization to birth, successful mammalian reproduction relies on interactions of elastic structures with a fluid environment. Sperm flagella must move through cervical mucus to the uterus and into the oviduct, where fertilization occurs. In fact, some sperm may adhere to …
We will discuss about “Detecting and quantifying causal associations in large nonlinear time series datasets”, Runge et al., Science Advances, 2019 Identifying causal relationships and quantifying their strength from observational time series data are key problems in disciplines dealing with complex dynamical systems such as the Earth system or the human body. Data-driven causal inference …
Simplicial Complexes, Persistent Homology and Persistent Diagrams. After a brief review on the persistent homology( Cohen-Steiner, Edelsbrunner, Harer,2010), we discuss constructive procedures persistent diagrams from the persistent homology. Code; 9 software packages generating persistent homology are introduced at " A roadmap for the computation of persistent homology", EPJ Data Science, a Springer Open Journal.
This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234) Abstract: John Hopfield first pointed out that there are barriers - we call them Hopfield barriers - to biological information-processing at thermodynamic equilibrium. I will explain how the widely-used Hill function with coefficient n is the universal Hopfield barrier to the sharpness …
We will discuss about “Solving Singular Control Problems in Mathematical Biology, Using PASA”, Atkins et al., arXiv, 2020 In this paper, we will demonstrate how to use a nonlinear polyhedral constrained optimization solver called the Polyhedral Active Set Algorithm (PASA) for solving a general singular control problem. We present methods of discretizing a general optimal …
This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234) Abstract: Simple mathematical models have had remarkable successes in biology, framing how we understand a host of mechanisms and processes. However, with the advent of a host of new experimental technologies, the last ten years has seen an explosion in the amount …
We will discuss about “A Random Matrix Theory Approach to Denoise Single-Cell Data”, Aparicio et al., Patterns, 2020 Single-cell technologies provide the opportunity to identify new cellular states. However, a major obstacle to the identification of biological signals is noise in single-cell data. In addition, single-cell data are very sparse. We propose a new method …
IBS BIMAG Vision Workshop This is a workshop for sharing the direction of the IBS BIMAG with leading mathematical biology researchers and receiving feedback. Date Nov. 27, 2021 (Saturday) Venue B378 Seminar room, IBS
Neural Networks with the Persistent Diagrams and Graph Classification. We introduce the first paper connecting persistent diagrams to the Neural Networks by Carrier et al," A neural Network Layer for Persistent Diagrams and New Graph Topological Signatures, 2019, arXiv. We are going to analyse the End-to-End algorithm and learning processes and applications. Code; tensorflow at …