NDLI: Nucleosome positioning based on DNA sequence embedding and deep learning

Content Provider	Springer Nature : BioMed Central
Author	Han, Guo-Sheng Li, Qi Li, Ying
Abstract	Background Nucleosome positioning is the precise determination of the location of nucleosomes on DNA sequence. With the continuous advancement of biotechnology and computer technology, biological data is showing explosive growth. It is of practical significance to develop an efficient nucleosome positioning algorithm. Indeed, convolutional neural networks (CNN) can capture local features in DNA sequences, but ignore the order of bases. While the bidirectional recurrent neural network can make up for CNN's shortcomings in this regard and extract the long-term dependent features of DNA sequence. Results In this work, we use word vectors to represent DNA sequences and propose three new deep learning models for nucleosome positioning, and the integrative model NP_CBiR reaches a better prediction performance. The overall accuracies of NP_CBiR on H. sapiens, C. elegans, and D. melanogaster datasets are 86.18%, 89.39%, and 85.55% respectively. Conclusions Benefited by different network structures, NP_CBiR can effectively extract local features and bases order features of DNA sequences, thus can be considered as a complementary tool for nucleosome positioning.
Related Links	https://bmcgenomics.biomedcentral.com/counter/pdf/10.1186/s12864-022-08508-6.pdf
Ending Page	10
Page Count	10
Starting Page	1
File Format	HTM / HTML
ISSN	14712164
DOI	10.1186/s12864-022-08508-6
Journal	BMC Genomics
Issue Number	1
Volume Number	23
Language	English
Publisher	BioMed Central
Publisher Date	2022-04-13
Access Restriction	Open
Subject Keyword	Life Sciences Microarrays Proteomics Animal Genetics and Genomics Microbial Genetics and Genomics Plant Genetics and Genomics Nucleosome positioning Word vector Deep learning Convolutional neural network Bidirectional recurrent neural network
Content Type	Text
Resource Type	Article
Subject	Biotechnology Genetics
Journal Impact Factor	3.5/2023
5-Year Journal Impact Factor	4.1/2023

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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