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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...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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BioMed Central
2017
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| 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 |