Pattern recognition of topologically associating domains using deep learning

Background Recent increasing evidence indicates that three-dimensional chromosome structure plays an important role in genomic function. Topologically associating domains (TADs) are self-interacting regions that have been shown to be a chromosomal structural unit. During evolution, these are conserv...

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Veröffentlicht in:	BMC bioinformatics Jg. 22; H. Suppl 10; S. 634 - 15
Hauptverfasser:	Yang, Jhen Yuan, Chang, Jia-Ming
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London BioMed Central 08.12.2022 BioMed Central Ltd Springer Nature B.V BMC
Schlagworte:	Accuracy Algorithms Animals Artificial neural networks Bioinformatics Biomedical and Life Sciences Cell lines Chromosome organization Chromosomes Classification Computational Biology/Bioinformatics Computer Appl. in Life Sciences Deep Learning Domains Evolution Gene mapping Genetic research Genomes Genomics Hi-C Humans Image classification Interactomes Life Sciences Machine learning Methods Mice Microarrays Neural networks Nucleotide sequence Object recognition Object recognition (Computers) Pattern recognition Performance evaluation Structure Synteny TAD Topologically associating domain Taiwan Deep learning Topologically associating domain Hi-C TAD Chromosome organization
ISSN:	1471-2105, 1471-2105
Online-Zugang:	Volltext
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