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- Guo, Xiaoyi, et al.
(författare)
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Random Fourier features-based sparse representation classifier for identifying DNA-binding proteins
- 2022
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Ingår i: Computers in Biology and Medicine. - London : Elsevier. - 0010-4825 .- 1879-0534. ; 151
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Tidskriftsartikel (refereegranskat)abstract
- DNA-binding proteins (DBPs) protect DNA from nuclease hydrolysis, inhibit the action of RNA polymerase,prevents replication and transcription from occurring simultaneously on a piece of DNA. Most of theconventional methods for detecting DBPs are biochemical methods, but the time cost is high. In recent years,a variety of machine learning-based methods that have been used on a large scale for large-scale screeningof DBPs. To improve the prediction performance of DBPs, we propose a random Fourier features-based sparserepresentation classifier (RFF-SRC), which randomly map the features into a high-dimensional space to solvenonlinear classification problems. And ?2,1-matrix norm is introduced to get sparse solution of model. Toevaluate performance, our model is tested on several benchmark data sets of DBPs and 8 UCI data sets. RFF-SRCachieves better performance in experimental results. © 2022 Elsevier Ltd.
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