Please use this identifier to cite or link to this item: http://hdl.handle.net/10995/102698
Title: DNA physical properties outperform sequence compositional information in classifying nucleosome-enriched and -depleted regions
Authors: Liu, G.
Liu, G. -J.
Tan, J. -X.
Lin, H.
Issue Date: 2019
Publisher: Academic Press Inc.
Citation: DNA physical properties outperform sequence compositional information in classifying nucleosome-enriched and -depleted regions / G. Liu, G. -J. Liu, J. -X. Tan, et al. — DOI 10.1016/j.ygeno.2018.07.013 // Genomics. — 2019. — Vol. 111. — Iss. 5. — P. 1167-1175.
Abstract: The nucleosome is the fundamental structural unit of eukaryotic chromatin and plays an essential role in the epigenetic regulation of cellular processes, such as DNA replication, recombination, and transcription. Hence, it is important to identify nucleosome positions in the genome. Our previous model based on DNA deformation energy, in which a set of DNA physical descriptors was used, performed well in predicting nucleosome dyad positions and occupancy. In this study, we established a machine-learning model for predicting nucleosome occupancy in order to further verify the physical descriptors. Results showed that (1) our model outperformed several other sequence compositional information-based models, indicating a stronger dependence of nucleosome positioning on DNA physical properties; (2) nucleosome-enriched and -depleted regions have distinct features in terms of DNA physical descriptors like sequence-dependent flexibility and equilibrium structure parameters; (3) gene transcription start sites and termination sites can be well characterized with the distribution patterns of the physical descriptors, indicating the regulatory role of DNA physical properties in gene transcription. In addition, we developed a web server for the model, which is freely accessible at http://lin-group.cn/server/iNuc-force/. © 2018 Elsevier Inc.
Keywords: FLEXIBILITY
FORCE CONSTANT
NUCLEOSOME OCCUPANCY
PHYSICAL DESCRIPTOR
ARTICLE
GENE EXPRESSION
MACHINE LEARNING
NUCLEOSOME
TRANSCRIPTION INITIATION SITE
ANIMAL
CHEMISTRY
CHROMATIN ASSEMBLY AND DISASSEMBLY
DNA SEQUENCE
GENETICS
HUMAN
NUCLEOSOME
PROCEDURES
SOFTWARE
DNA
ANIMALS
CHROMATIN ASSEMBLY AND DISASSEMBLY
DNA
HUMANS
MACHINE LEARNING
NUCLEOSOMES
SEQUENCE ANALYSIS, DNA
SOFTWARE
URI: http://hdl.handle.net/10995/102698
Access: info:eu-repo/semantics/openAccess
SCOPUS ID: 85050507489
PURE ID: 10771948
d21ee404-a28b-40ae-9143-85b354b366c1
ISSN: 8887543
DOI: 10.1016/j.ygeno.2018.07.013
Appears in Collections:Научные публикации, проиндексированные в SCOPUS и WoS CC

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