기초과학연구원 의생명수학그룹
This talk will be presented online. Zoom link: 997 8258 4700 (pw: 1234) Abstract: 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.
We will discuss about "Physics-informed learning of governing equations from scarce data", Chen et al., Nature Communications, 2021 Abstract: 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 …
This talk will be presented online. Zoom link: 997 8258 4700 (pw: 1234) Abstract: 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, …
We will discuss about "RTransferEntropy — Quantifying information flow between different time series using effective transfer entropy", Behrendt et al., SoftwareX, 2019 Abstract: 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 …
This talk will be presented online. Zoom link: 997 8258 4700 (pw: 1234) Abstract: TBA
This talk will be presented online. Zoom link: 997 8258 4700 (pw: 1234) Abstract: 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 …
We will discuss about "A topological data analysis based classifier", Kindelan et al., arXiv, 2022 Abstract: 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 …
This talk will be presented online. Zoom link: 997 8258 4700 (pw: 1234) Abstract: Metastasis 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 …
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 Abstract: 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 …
This talk will be presented online. Zoom link: 997 8258 4700 (pw: 1234) Abstract: 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 …
We will discuss about "Toroidal topology of population activity in grid cells", Gardner et al., Nature, 2021. Abstract: 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, …