Article

DTPSP: A Deep Learning Framework for Optimized Time Point Selection in Time-Series Single-Cell Studies

2024-12-20

Abstract excerpt

Time-series studies are critical for uncovering dynamic biological processes, but achieving comprehensive profiling and resolution across multiple time points and modalities (multi-omics) remains challenging due to cost and scalability constraints. Current methods for studying temporal dynamics, whether at the bulk or single-cell level, often require extensive sampling, making it impractical to deeply profile all...

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Literature Corpus work: d31caebc-a625-5a00-aba5-79d1d5a04fc9
DOI: 10.1101/2024.12.18.629276

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