기초과학연구원 의생명수학그룹
Abstract: Circadian 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 …
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 …
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. …
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. Abstract: The dynamics of …
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 …
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. …
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). Abstract: The …
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 …
We will discuss about "Chemical Organisation Theory ", Dittrich, Peter, and Pietro Speroni Di Fenizio, Bulletin of mathematical biology 69.4 (2007): 1199-1231. Abstract: Complex dynamical reaction networks consisting of many …
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). Abstract: The standard model describing …
We will discuss about "Learning stable and predictive structures in kinetic systems", Niklas Pfister , Stefan Bauer, and Jonas Peters. PNAS, 2019 Abstract: Learning kinetic systems from data is one …
We will discuss about "Neural Ordinary Differential Equations", Chen, Ricky TQ, et al., Advances in neural information processing systems 31 (2018). Abstract: We introduce a new family of deep neural …