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http://elar.urfu.ru/handle/10995/102698
Название: | DNA physical properties outperform sequence compositional information in classifying nucleosome-enriched and -depleted regions |
Авторы: | Liu, G. Liu, G. -J. Tan, J. -X. Lin, H. |
Дата публикации: | 2019 |
Издатель: | Academic Press Inc. |
Библиографическое описание: | 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. |
Аннотация: | 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. |
Ключевые слова: | 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://elar.urfu.ru/handle/10995/102698 |
Условия доступа: | info:eu-repo/semantics/openAccess |
Идентификатор SCOPUS: | 85050507489 |
Идентификатор WOS: | 000485764600020 |
Идентификатор PURE: | d21ee404-a28b-40ae-9143-85b354b366c1 10771948 |
ISSN: | 8887543 |
DOI: | 10.1016/j.ygeno.2018.07.013 |
Располагается в коллекциях: | Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC |
Файлы этого ресурса:
Файл | Описание | Размер | Формат | |
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2-s2.0-85050507489.pdf | 1,97 MB | Adobe PDF | Просмотреть/Открыть |
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