Rxivist logo

Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 67,095 bioRxiv papers from 295,233 authors.

Enter the matrix: factorization uncovers knowledge from omics

By Genevieve L. Stein-O'Brien, Raman Arora, Aedin C. Culhane, Alexander Favorov, Lana X. Garmire, Casey S. Greene, Loyal A. Goff, Yifeng Li, Alioune Ngom, Michael F. Ochs, Yanxun Xu, Elana J. Fertig

Posted 02 Oct 2017
bioRxiv DOI: 10.1101/196915 (published DOI: 10.1016/j.tig.2018.07.003)

Omics data contains signal from the molecular, physical, and kinetic inter- and intra-cellular interactions that control biological systems. Matrix factorization techniques can reveal low-dimensional structure from high-dimensional data that reflect these interactions. These techniques can uncover new biological knowledge from diverse high-throughput omics data in topics ranging from pathway discovery to time course analysis. We review exemplary applications of matrix factorization for systems-level analyses. We discuss appropriate application of these methods, their limitations, and focus on analysis of results to facilitate optimal biological interpretation. The inference of biologically relevant features with matrix factorization enables discovery from high-throughput data beyond the limits of current biological knowledge-answering questions from high-dimensional data that we have not yet thought to ask.

Download data

  • Downloaded 2,822 times
  • Download rankings, all-time:
    • Site-wide: 1,318 out of 67,044
    • In systems biology: 28 out of 1,863
  • Year to date:
    • Site-wide: 7,477 out of 67,044
  • Since beginning of last month:
    • Site-wide: 21,447 out of 67,044

Altmetric data

Downloads over time

Distribution of downloads per paper, site-wide

Sign up for the Rxivist weekly newsletter! (Click here for more details.)