Performance of Existing Predictor of SubCellular Localization of Long Non-Coding RNA on the New Database
Authors: 
Ying Yuan, Bin Yuan, Hanqiu MaoAuthors Info & Claims
Abstract
Long non-coding RNAs (lncRNAs) have important functions in the regulation of life activities at multiple levels, such as chromatin remodeling, transcriptional and posttranscriptional regulation. They have different functions according to the different locations in the cell. Therefore, it is important to obtain the sub-cellular location information to understand the functions of lncRNAs. However, the biochemical experimental way of sub-cellular localization requires a long period and high cost. Currently, many methods of predicting sub-cellular location based on the machine learning and deep learning have been developed to ease the difficulty in detecting the sub-cellular location. We fetched the latest version RNA database to evaluate the performance of existing predictors, lncLocator and iLoc-lncRNA.
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- Performance of Existing Predictor of SubCellular Localization of Long Non-Coding RNA on the New Database
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Published In
October 2020
552 pages
ISBN:9781450387835
DOI:10.1145/3436369
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- Beijing University of Technology
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Association for Computing Machinery
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Published: 11 January 2021
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ICCPR 2020
ICCPR 2020: 2020 9th International Conference on Computing and Pattern Recognition
October 30 - November 1, 2020
Xiamen, China
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