기초과학연구원 의생명수학그룹
The field of sleep science is rapidly advancing, with increasing attention focused on unraveling the mystery of sleep across various scientific domains. Sleep medicine, which emerged from scientific research on sleep, is a highly important field that can enhance the quality of life and health. Since sleep medicine requires the integration of various specialized knowledge, …
In this talk, we discuss the paper "Plausible, robust biological oscillations through allelic buffering" by F-S. Hsieh et.al, Cell Systems, 2024. at the Journal Club. Abstract Biological oscillators can specify time- and dose-dependent functions via dedicated control of their oscillatory dynamics. However, how biological oscillators, which recurrently activate noisy biochemical processes, achieve robust oscillations remains …
In this talk, we discuss the paper "Self-supervised learning of accelerometer data provides new insights for sleep and its association with mortality" by H. Yuan et.al, npj digital medicine, 2024, at the Journal Club. Abstract Sleep is essential to life. Accurate measurement and classification of sleep/wake and sleep stages is important in clinical studies for …
In this talk, we discuss the paper "A cell atlas foundation model for scalable search of similar human cells" by Graham Heimberg et.al., Nature, 2024 at the Journal Club. Abstract Single-cell RNA sequencing has profiled hundreds of millions of human cells across organs, diseases, development and perturbations to date. Mining these growing atlases could reveal …
In this talk, we discuss the paper "Method for cycle detection in sparse, irregularly sampled, long-term neuro-behavioral timeseries: Basis pursuit denoising with polynomial detrending of long-term, inter-ictal epileptiform activity" by Irena Balzekas et.al., Plos Com., 2024. Abstract Numerous physiological processes are cyclical, but sampling these processes densely enough to perform frequency decomposition and subsequent analyses …
In this talk, we discuss the paper "Constraining nonlinear time series modeling with the metabolic theory of ecology" by S.B. Munch et.al., PNAS, 2023. Abstract Forecasting the response of ecological systems to environmental change is a critical challenge for sustainable management. The metabolic theory of ecology (MTE) posits scaling of biological rates with temperature, but …
In this talk, we discuss the paper "Quantifying information accumulation encoded in the dynamics of biochemical signaling" by Y. Tang, et.al, Nature Communications, 2021. Abstract Cellular responses to environmental changes are encoded in the complex temporal patterns of signaling proteins. However, quantifying the accumulation of information over time to direct cellular decision-making remains an unsolved …
본 세미나에서는 성신여자대학교 서수연 교수님께서 "심리학이 알려주는 연구의 기술: 논리적 사고부터 논문 작성까지"라는 내용으로 강연을 해주실 예정입니다.
In this talk, we discuss the paper "The Large Language Models on Biomedical Data Analysis: A Survey" by Wei Lan et.al, IEEE J. Biomedical and Health Informatics, 2025, at the Journal Club. Abstract With the rapid development of Large Language Model (LLM) technology, it has become an indispensable force in biomedical data analysis research. However, …
Abstract The standard theory of infectious diseases, tracing back to the work of Kermack and McKendrick nearly a century ago, has been a triumph of mathematical biology, a rare marriage of theory and application. Yet the limitations of its most simple representations, which has always been known, have been laid bare in dealing with COVID-19, …
In this talk, we discuss the paper "A biological model of nonlinear dimensionality reduction" by K. Yoshida and T. Toyoizumi, Science Advances, 2025, at the Journal Club. Abstract Obtaining appropriate low-dimensional representations from high-dimensional sensory inputs in an unsupervised manner is essential for straightforward downstream processing. Although nonlinear dimensionality reduction methods such as t-distributed stochastic neighbor …
Abstract Our present healthcare system focuses on treating people when they are ill rather than keeping them healthy. We have been using big data and remote monitoring approaches to monitor people while they are healthy to keep them that way and detect disease at its earliest moment presymptomatically. We use advanced multiomics technologies (genomics, immunomics, …
