Analysis of sleep-wake cycles via machine learning and mathematical modeling
B305 Seminar room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Korea, Republic ofAbstract: TBA
Abstract: TBA
Abstract: Inference method for a stochastic target-mediated drug disposition model via ABC-MCMC In this study, we discuss model robustness. Model robustness is consistent performance over variations of parameters. We formulate a stochastic target-mediated drug (TMDD) model, one of the pharmacokinetic models, to capture bi-exponential drug decay in plasma. A stochastic process is used to account …
Abstract: Systems biology seeks to build quantitative predictive models of biological system behavior. Biological systems, such as the mammalian immune system, operate across multiple spatiotemporal scales with a myriad of molecular and cellular players. Thus, mechanistic, predictive models describing such systems need to address this multiscale nature. A general outstanding problem is to cope with …
Abstract: Most organisms exhibit various endogenous oscillating behaviors, which provides crucial information about how the internal biochemical processes are connected and regulated. Along with physical experiments, studying such periodicity of organisms often utilizes computer experiments relying on ordinary differential equations (ODE) because configuring the internal processes is difficult. Simultaneously utilizing both experiments, however, poses a …
Abstract This presentation include the following two topics. First of all, we consider a spread model of COVID-19 with time-dependent parameters via deep learning. We developed a SIR model with time-dependent parameters via deep learning methods. Furthermore, we validated the model with the conventional model to confirm its convergent nature. Next, We also developed a …
Abstract TBA
(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 …
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.
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 …
Abstract Non-invasive data collection in real-world settings with wearables provides a new opportunity for characterizing daily physiology. However, accurate and efficient characterization remains an open problem because the complex autoregressive noise of the data makes it challenging to use a simple and efficient method for inference of clock proxies, least squares method. In this talk, …
디지털 표현형의 진단 및 치료적 적용 조철현(세종충남대학교병원) 디지털 표현형(digital phenotype)은 각 개개인이 일상생활에서 사용하는 다양한 디지털 기기를 통해서 실시간으로 얻어지는 다양한 형태의 데이터를 뜻하는 것으로, 디지털 기기의 사용이 보편화되면서 의료적 적용에 대한 가능성이 한층 높아지고 있다. 디지털 표현형은 이전에는 측정(measure)하기 힘들었던 영역에 대한 측정을 가능케 함으로써, 의학적 평가나 진단적인 측면에서 임상적 함의를 갖는다고 볼 수 …
In adult tissues, stem cells undergo clonal competition because they proliferate while the stem cell niche provides limited space. This clonal competition allows the selection of healthy stem cells over time as unfit stem cells tend to lose from the competition. It could also be a mechanism to select a supercompetitor with tumorigenic mutations, which …