A wider field of view to predict expression

Nat Methods. 2021 Oct;18(10):1155-1156. doi: 10.1038/s41592-021-01259-4.

Authors

Yang Young Lu¹, William Stafford Noble^{2

3}

Affiliations

¹ Department of Genome Sciences, University of Washington, Seattle, WA, USA.
² Department of Genome Sciences, University of Washington, Seattle, WA, USA. william-noble@uw.edu.
³ Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA. william-noble@uw.edu.

Abstract

A sequence-to-expression machine learning model achieves higher accuracy by incorporating information about potential long-range interactions.

Publication types

Research Support, N.I.H., Extramural
Comment

Grants and funding

U01 HG009395/HG/NHGRI NIH HHS/United States