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Predicting transcription factor binding using ensemble random forest models
Background: Understanding the location and cell-type specific binding of Transcription Factors (TFs) is important in the study of gene regulation. Computational prediction of TF binding sites is challenging, because TFs often bind only to short DNA motifs and cell-type specific co-factors may work t...
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| Veröffentlicht in: | F1000Res |
|---|---|
| Hauptverfasser: | , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
F1000 Research Limited
2019
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6823902/ https://ncbi.nlm.nih.gov/pubmed/31723409 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.12688/f1000research.16200.2 |
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