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  1. KRISHI Publication and Data Inventory Repository
  2. Agricultural Education A1
  3. ICAR-Indian Agricultural Statistics Research Institute B7
  4. AEdu-IASRI-Publication
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Please use this identifier to cite or link to this item: http://krishi.icar.gov.in/jspui/handle/123456789/68655
Title: RBPSpot: Learning on appropriate contextual information for RBP binding sites discovery
Other Titles: Not Available
Authors: Nitesh Kumar Sharma
Sagar Gupta
Ashwani Kumar
Prakash Kumar
Upendra Kumar Pradhan
Ravi Shankar
ICAR Data Use Licennce: http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf
Author's Affiliated institute: ICAR::Indian Agricultural Statistics Research Institute
CSIR-IHBT, Palampur, HP 176061, India
Published/ Complete Date: 2021-12-17
Project Code: Not Available
Keywords: Machine learning
Omics
Systems biology
Publisher: CellPress
Citation: Sharma, N.K., Gupta, S., Kumar, P, Kumar, A, Pradhan, U.K and Shankar, R. (2021) RBPSpot: Deep Learning on Appropriate Contextual Information for RBP Binding Sites Discovery. iScience. 24(12). 103381. https://doi.org/10.1016/j.isci.2021.103381.
Series/Report no.: Not Available;
Abstract/Description: Identifying the factors determining the RBP-RNA interactions remains a big challenge. It involves sparse binding motifs and a suitable sequence context for binding. The present work describes an approach to detect RBP binding sites in RNAs using an ultra-fast inexact k-mers search for statistically significant seeds. The seeds work as an anchor to evaluate the context and binding potential using flanking region information while leveraging from Deep Feed-forward Neural Network. The developed models also received support from MD-simulation studies. The implemented software, RBPSpot, scored consistently high for all the performance metrics including average accuracy of ∼90% across a large number of validated datasets. It outperformed the compared tools, including some with much complex deep-learning models, during a comprehensive benchmarking process. RBPSpot can identify RBP binding sites in the human system and can also be used to develop new models, making it a valuable resource in the area of regulatory system studie
Description: Not Available
ISSN: 2589-0042
Type(s) of content: Article
Sponsors: Not Available
Language: English
Name of Journal: iScience
Journal Type: An interdisciplinary journal covering the life, physical, and earth sciences
NAAS Rating: 11.08
Impact Factor: 5.08
Volume No.: 24(12)
Page Number: 103381
Name of the Division/Regional Station: Statistical Genetics
Source, DOI or any other URL: https://doi.org/10.1016/j.isci.2021.103381
URI: http://krishi.icar.gov.in/jspui/handle/123456789/68655
Appears in Collections:AEdu-IASRI-Publication

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