Cargando…
BayesPI-BAR2: A New Python Package for Predicting Functional Non-coding Mutations in Cancer Patient Cohorts
Most of somatic mutations in cancer occur outside of gene coding regions. These mutations may disrupt the gene regulation by affecting protein-DNA interaction. A study of these disruptions is important in understanding tumorigenesis. However, current computational tools process DNA sequence variants...
Autores principales: | Batmanov, Kirill, Delabie, Jan, Wang, Junbai |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6454009/ https://www.ncbi.nlm.nih.gov/pubmed/31001324 http://dx.doi.org/10.3389/fgene.2019.00282 |
Ejemplares similares
-
BayesPI-BAR: a new biophysical model for characterization of regulatory sequence variations
por: Wang, Junbai, et al.
Publicado: (2015) -
The effect of prior assumptions over the weights in BayesPI with application to study protein-DNA interactions from ChIP-based high-throughput data
por: Wang, Junbai
Publicado: (2010) -
Quality versus accuracy: result of a reanalysis of protein-binding microarrays from the DREAM5 challenge by using BayesPI2 including dinucleotide interdependence
por: Wang, Junbai
Publicado: (2014) -
BayesPI - a new model to study protein-DNA interactions: a case study of condition-specific protein binding parameters for Yeast transcription factors
por: Wang, Junbai, et al.
Publicado: (2009) -
Integrative whole-genome sequence analysis reveals roles of regulatory mutations in BCL6 and BCL2 in follicular lymphoma
por: Batmanov, Kirill, et al.
Publicado: (2017)