ClusterTAD: an unsupervised machine learning approach to detecting topologically associated domains of chromosomes from Hi-C data

BACKGROUND: With the development of chromosomal conformation capturing techniques, particularly, the Hi-C technique, the study of the spatial conformation of a genome is becoming an important topic in bioinformatics and computational biology. The Hi-C technique can generate genome-wide chromosomal i...

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Detalles Bibliográficos
Autores principales: Oluwadare, Oluwatosin, Cheng, Jianlin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5686814/
https://www.ncbi.nlm.nih.gov/pubmed/29137603
http://dx.doi.org/10.1186/s12859-017-1931-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5686814/
https://www.ncbi.nlm.nih.gov/pubmed/29137603
http://dx.doi.org/10.1186/s12859-017-1931-2

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