Seokjoo Chae, Holimap: an accurate and efficient method for solving stochastic gene network dynamics

In this talk, we discuss the paper "Holimap: an accurate and efficient method for solving stochastic gene network dynamics" by Chen Jia and Ramon Grima, bioRxiv, 2024. Abstract  Gene-gene interactions are crucial to the control of sub-cellular processes but our understanding of their stochastic dynamics is hindered by the lack of simulation methods that can accurately and efficiently

Dongju Lim, Stochastic representations of ion channel kinetics and exact stochastic simulation of neuronal dynamics.

In this talk, we discuss the paper "Stochastic representations of ion channel kinetics and exact stochastic simulation of neuronal dynamics" by D. F. Anderson, B. Ermentrout and P. J. Thomas, Journal of Computational Neuroscience, 2015. Abstract In this paper we provide two representations for stochastic ion channel kinetics, and compare the perfor- mance of exact

Eui Min Jeong, Temperature compensation through kinetic regulation in biochemical oscillators.

In this talk, we discuss the paper "Temperature compensation through kinetic regulation in biochemical oscillators" by HaochenFu, Chenyi Fei, Qi Ouyang, and Yuhai Tu, to appear in PNAS.  Abstract  Although individual kinetic rates in biochemical reactions are sensitive to temperature, most circadian clocks exhibit a relatively constant period across a wide range of temperatures, a phenomenon called

Yun Min Song, RNA velocity of single cells

B232 Seminar Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Daejeon, Korea, Republic of

In this talk, we discuss the paper "RNA velocity of single sells" by Gioele La Manno et.al., Nature, 2018. Abstract RNA abundance is a powerful indicator of the state of individual cells. Single-cell RNA sequencing can reveal RNA abundance with high quantitative accuracy, sensitivity and throughput. However, this approach captures only a static snapshot at

Gyuyoung Hwang, A universal description of stochastic oscillators

In this talk, we discuss the paper "A universal description of stochastic oscillators", by Alberto Perez-Cervera et. al., PNAS, 2023. Abstract  Many systems in physics, chemistry, and biology exhibit oscillations with a pronounced random component. Such stochastic oscillations can emerge via different mechanisms, for example, linear dynamics of a stable focus with fluctuations, limit-cycle systems

Kevin Spinicci, SMSSVD : Submatrix selection singular value decomposition

In this talk, we discuss the paper, "SMSSVD : Submatrix selection singular value decomposition", by Rasmus Henningsson and Magnus Fontes, Bioinformatics, 2019. Abstract Motivation High throughput biomedical measurements normally capture multiple overlaid biologically relevant signals and often also signals representing different types of technical artefacts like e.g. batch effects. Signal identification and decomposition are accordingly

Olive Cawiding, Predicting multiple observations in complex systems through low-dimensional embeddings

B232 Seminar Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Daejeon, Korea, Republic of

In this talk, we discuss the paper, "Predicting multiple observations in complex systems through low-dimensional embeddings", by Tao Wu et. al., Nature Communications, 2024. Zoom : https://us06web.zoom.us/j/99567630778?pwd=N2ZrUWtqZzJ0YURVTzlZT3JJR3FUQT09 Abstract Forecasting all components in complex systems is an open and challenging task, possibly due to high dimensionality and undesirable predictors. We bridge this gap by proposing a data-driven

Hyun Kim, Deep learning linking mechanistic models to single-cell transcriptomics data reveals transcriptional bursting in response to DNA damage

B232 Seminar Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Daejeon, Korea, Republic of

In this talk, we discuss the paper "Deep learning linking mechanistic models to single-cell transcriptomics data reveals transcriptional bursting in response to DNA damage" by Zhiwei Huang, et. al., bioRxiv, 2024. Zoom : https://us06web.zoom.us/j/99567630778?pwd=N2ZrUWtqZzJ0YURVTzlZT3JJR3FUQT09 Abstract Cells must adopt flexible regulatory strategies to make decisions regarding their fate, including differentiation, apoptosis, or survival in the face of

Brenda Gavina, Achieving Occam’s razor: Deep learning for optimal model reduction

In this talk, we discuss the paper "Achieving Occam’s razor: Deep learning for optimal model reduction" by Botond B. Antal et.al., PLOS Computational Biology, 2024. Abstract  All fields of science depend on mathematical models. Occam’s razor refers to the principle that good models should exclude parameters beyond those minimally required to describe the systems they represent. This

Dongju Lim, Mathematical model for the distribution of DNA replication origins

B232 Seminar Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Daejeon, Korea, Republic of

In this talk we discuss the paper "Mathematical model for the distribution of DNA replication origins" by Alessandro de Moura and Jens Karschau, Physical Review E, 2024. Abstract  DNAreplication in yeast and in many other organisms starts from well-defined locations on the DNA known as replication origins. The spatial distribution of these origins in the genome is particularly

Eui Min Jeong, A frequency-amplitude coordinator and its optimal energy consumption for biological oscillators

In this talk, we discuss the paper, “A frequency-amplitude coordinator and its optimal energy consumption for biological oscillators”, by Bo-Wei Qin et. al., Nature Communications, 2021. Zoom : https://us06web.zoom.us/j/99567630778?pwd=N2ZrUWtqZzJ0YURVTzlZT3JJR3FUQT09 Abstract  Biorhythm including neuron firing and protein-mRNA interaction are fundamental activities with diffusive effect. Their well-balanced spatiotemporal dynamics are beneficial for healthy sustainability. Therefore, calibrating both anomalous

Yun Min Song – Noise robustness and metabolic load determine the principles of central dogma regulation

In this talk, we discuss the paper : "Noise robustness and metabolic load determine the principles of central dogma regulation" by Teresa W. Lo et al, Sci. Adv, https://doi.org/10.1126/sciadv.ado3095. Zoom: https://us06web.zoom.us/j/99567630778?pwd=N2ZrUWtqZzJ0YURVTzlZT3JJR3FUQT09 Abstract The processes of gene expression are inherently stochastic, even for essential genes required for growth. How does the cell maximize fitness in light

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