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A novel k-mer set memory (KSM) motif representation improves regulatory variant prediction
[article]
2017
bioRxiv
pre-print
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 non-coding genetic variants. We present a novel TF binding motif representation, the K-mer Set Memory (KSM), which consists of a set of aligned k-mers that are over-represented at TF binding sites, and a new method called KMAC for de novo discovery of KSMs. We find that KSMs more accurately predict
doi:10.1101/130815
fatcat:hkrehkj7sfc27lctijg5gzgn3y