기초과학연구원 의생명수학그룹
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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 … |
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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 … |
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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 … |
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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 … |
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