A novel k-mer set memory (KSM) motif representation improves regulatory variant prediction

The representation and discovery of transcription factor (TF) sequence binding specificities is critical for understanding gene regulatory networks and interpreting the impact of disease-associated noncoding genetic variants. We present a novel TF binding motif representation, the k-mer set memory (...

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Bibliographic Details
Main Authors: Guo, Yuchun, Tian, Kevin J., Zeng, Haoyang, Guo, Xiaoyun, Gifford, David K
Other Authors: Massachusetts Institute of Technology. Computational and Systems Biology Program
Format: Article
Published: Cold Spring Harbor Laboratory 2018
Online Access:http://hdl.handle.net/1721.1/119653
https://orcid.org/0000-0003-2357-1546
https://orcid.org/0000-0003-1057-2865
https://orcid.org/0000-0003-1709-4034