기초과학연구원 의생명수학그룹
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 …
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 …
We will discuss about “Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics”, Ji et al., The Journal of Physical Chemistry A, 2020 The recently developed physics-informed neural network (PINN) has achieved success in many science and engineering disciplines by encoding physics laws into the loss functions of the neural network such that the network not …
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, …
We will discuss about "Information Integration and Energy Expenditure in Gene Regulation", Estrada et al., Cell, 2016 Abstract: The quantitative concepts used to reason about gene regulation largely derive from bacterial studies. We show that this bacterial paradigm cannot explain the sharp expression of a canonical developmental gene in response to a regulating transcription factor …
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 …
We will discuss about "The Generalized Multiset Sampler", Kim and MacEachern, The Journal of Computation and Graphical Statistics, 2021 Abstract: The multiset sampler, an MCMC algorithm recently proposed by Leman and coauthors, is an easy-to-implement algorithm which is especially well-suited to drawing samples from a multimodal distribution. We generalize the algorithm by redefining the multiset …
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 …
Abstract: Inside living cells, chemical reactions form a large web of networks. Understanding the behavior of those complex reaction networks is an important and challenging problem. In many situations, it is hard to identify the details of the reactions, such as the reaction kinetics and parameter values. It would be good if we can clarify …
Inside living cells, chemical reactions form a large web of networks. Understanding the behavior of those complex reaction networks is an important and challenging problem. In many situations, it is hard to identify the details of the reactions, such as the reaction kinetics and parameter values. It would be good if we can clarify what …
We will discuss about "Fundamental limits on the suppression of molecular fluctuations", Lestas et al, Nature, 2010 Abstract: Negative feedback is common in biological processes and can increase a system’s stability to internal and external perturbations. But at the molecular level, control loops always involve signalling steps with finite rates for random births and deaths …