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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Detalles Bibliográficos
Autores principales: Behjati Ardakani, Fatemeh, Schmidt, Florian, Schulz, Marcel H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000 Research Limited 2019
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6823902/
https://www.ncbi.nlm.nih.gov/pubmed/31723409
http://dx.doi.org/10.12688/f1000research.16200.2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6823902/
https://www.ncbi.nlm.nih.gov/pubmed/31723409
http://dx.doi.org/10.12688/f1000research.16200.2

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