기초과학연구원 의생명수학그룹
2023 KSIAM-NIMS School on Biomathematics: Statistical Tools for Mathematical Modeling 2023년 6월 24일 - 6월 26일, 3일간 제주 베스트 웨스턴 호텔에서 2023 KSIAM-NIMS School on Biomathematics: Statistical Tools for Mathematical Modeling이 열립니다. 이 튜토리얼에서는 신시내티 대학교의 장원 교수님과 연세대학교의 박재우 교수님께서 3일간 강의를 해주실 예정입니다. 모든 강의는 한국어로 진행됩니다. 자세한 일정은 아래 홈페이지에서 확인하실 수 …
Hyukpyo Hong: Advancing Infectious Disease Modeling: Estimating Reproduction Number with Realistic Latent and Infectious Periods Seokmin Ha: Systematic inference-driven experiments reveal a fundamental mechanism governing clock protein interactions in plants
We will discuss about “scPrisma infers, filters and enhances topological signals in single-cell data using spectral template matching”, Karin, Jonathan, Yonathan Bornfeld, and Mor Nitzan., Nature Biotechnology (2023): 1-10. Abstract Single-cell RNA sequencing has been instrumental in uncovering cellular spatiotemporal context. This task is challenging as cells simultaneously encode multiple, potentially cross-interfering, biological signals. Here we …
We will discuss about “The singularity response reveals entrainment properties of the plant circadian clock”, Masuda, Kosaku, et al., Nature Communications 12.1 (2021): 864. Abstract Circadian clocks allow organisms to synchronize their physiological processes to diurnal variations. A phase response curve allows researchers to understand clock entrainment by revealing how signals adjust clock genes differently …
Yun Min Song: Noisy delay denoises biochemical oscillators Seokjoo Chae: Reduction of spatiotemporal model and its validity condition
We will discuss about “ The Internal Model Principle for Biomolecular Control Theory ”, Gupta, Ankit, and Mustafa Khammash., IEEE Open Journal of Control Systems 2 (2023): 63-69. Abstract The well-known Internal Model Principle (IMP) is a cornerstone of modern control theory. It stipulates the necessary conditions for asymptotic robustness of disturbance-prone dynamical systems …
2023 제4회 한국분자세포생물학회 생체리듬준분과 심포지엄을 아래와 같이 진행합니다. 일시: 2023년 8월 10일(목) - 8월 11일(금) 장소: 대전 IBS 과학문화센터 학회 홈페이지 링크는 하단에 있습니다. We are pleased to announce the 4th Korean Biological Rhythm Society Symposium. Date: August 10th (Thursday) - August 11th (Friday), 2023 Location: Daejeon IBS Science Culture Center Conference Website Link (below) …
We will discuss about “ Decomposing predictability to identify dominant causal drivers in complex ecosystems ”,Suzuki, Kenta, Shin-ichiro S. Matsuzaki, and Hiroshi Masuya., Proceedings of the National Academy of Sciences 119.42 (2022): e2204405119. Abstract Ecosystems are complex systems of various physical, biological, and chemical processes. Since ecosystem dynamics are composed of a mixture of …
Dongju Lim: Mood Prediction for Bipolar Disorder Patient with Sleep Pattern Information Olive Cawiding: Detecting causality between weather variables and dengue cases in the Philippines
ICIAM 2023 Satellite Workshop: Stochastic Modeling and Data Analysis for Biological Systems We are excited to announce the upcoming ICIAM 2023 Satellite Workshop on Stochastic Modeling and Data Analysis for Biological Systems. This three-day workshop will take place from August 16th to 18th, 2023, at the Institute for Basic Science Headquarters in Daejeon, Korea. The …
We will discuss about “Generalized Michaelis–Menten rate law with time-varying molecular concentrations”, Lim, Roktaek, et al.,bioRxiv (2022): 2022-01 Abstract The Michaelis–Menten (MM) rate law has been the dominant paradigm of modeling biochemical rate processes for over a century with applications in biochemistry, biophysics, cell biology, and chemical engineering. The MM rate law and its …
Abstract Mathematical models of biological systems, including neurons, often feature components that evolve on very different timescales. Mathematical analysis of these multi-timescale systems can be greatly simplified by partitioning them into subsystems that evolve on different time scales. The subsystems are then analyzed semi-independently, using a technique called fast-slow analysis. I will briefly describe the …