Integrating genome sequence and structural data for statistical learning to predict transcription factor binding sites

We report an approach to predict DNA specificity of the tetracycline repressor (TetR) family transcription regulators (TFRs). First, a genome sequence-based method was streamlined with quantitative P-values defined to filter out reliable predictions. Then, a framework was introduced to incorporate s...

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Detalles Bibliográficos
Autores principales: Long, Pengpeng, Zhang, Lu, Huang, Bin, Chen, Quan, Liu, Haiyan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Computational Biology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7736823/
https://www.ncbi.nlm.nih.gov/pubmed/33264415
http://dx.doi.org/10.1093/nar/gkaa1134

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7736823/
https://www.ncbi.nlm.nih.gov/pubmed/33264415
http://dx.doi.org/10.1093/nar/gkaa1134

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