Article

Learning common and specific patterns from data of multiple interrelated biological scenarios with matrix factorization

2018-02-27

Abstract excerpt

High-throughput biological technologies (e.g., ChIP-seq, RNA-seq and single-cell RNA-seq) rapidly accelerate the accumulation of genome-wide omics data in diverse interrelated biological scenarios (e.g., cells, tissues and conditions). Data dimension reduction and differential analysis are two common paradigms for exploring and analyzing such data. However, they are typically used in a separate or/and sequential m...

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Literature Corpus work: f0d2d466-13b1-5bfa-b4b0-9640caa1d8a8
DOI: 10.1101/272443

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