ClusterTAD: an unsupervised machine learning approach to detecting topologically associated domains of chromosomes from Hi-C data
Abstract 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 chrom...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2017-11-01
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| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12859-017-1931-2 |