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Learning common and specific patterns from data of multiple interrelated biological scenarios with matrix factorization
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). Integration and differential analysis are two common paradigms for...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Oxford University Press
2019
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6649783/ https://www.ncbi.nlm.nih.gov/pubmed/31175825 http://dx.doi.org/10.1093/nar/gkz488 |