LeNup: learning nucleosome positioning from DNA sequences with improved convolutional neural networks.

Journal: Bioinformatics (Oxford, England)

PMID: 29329398

Abstract

MOTIVATION: Nucleosome positioning plays significant roles in proper genome packing and its accessibility to execute transcription regulation. Despite a multitude of nucleosome positioning resources available on line including experimental datasets of genome-wide nucleosome occupancy profiles and computational tools to the analysis on these data, the complex language of eukaryotic Nucleosome positioning remains incompletely understood.

Authors

Juhua Zhang

Department of Biomedical Engineering.
Wenbo Peng

Department of Biomedical Engineering.
Lei Wang

Department of Nursing, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.

Keywords

Algorithms Animals Caenorhabditis elegans Chromatin Assembly and Disassembly DNA Drosophila melanogaster Genome Humans Neural Networks, Computer Nucleosomes Saccharomyces cerevisiae Software

External Resources

View on PubMed Access via DOI PubMed (29329398)

LeNup: learning nucleosome positioning from DNA sequences with improved convolutional neural networks.

Abstract

Authors

Keywords

External Resources

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