Prediction of RNA-protein interactions by combining deep convolutional neural network with feature selection ensemble method
DOI10.1016/j.jtbi.2018.10.029zbMath1406.92220OpenAlexW2897712722WikidataQ57471709 ScholiaQ57471709MaRDI QIDQ1716911
Xiao-Fei Sun, Xin Yan, Wen-Wen Pan, Meng-Lin Liu, Lei Wang, Ke-Jian Song
Publication date: 5 February 2019
Published in: Journal of Theoretical Biology (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jtbi.2018.10.029
extreme learning machineposition-specific scoring matrixRNA-protein interactionconvolution neural network
Applications of statistics to biology and medical sciences; meta analysis (62P10) Learning and adaptive systems in artificial intelligence (68T05) Biochemistry, molecular biology (92C40)
Uses Software
Cites Work
- Predicting rRNA-, RNA-, and DNA-binding proteins from primary structure with support vector machines
- Exploring the role of cation-\(\pi\) interactions in glycoproteins lipid-binding proteins and RNA-binding proteins
- Sequence-based discrimination of protein-RNA interacting residues using a probabilistic approach
- Measuring the Accuracy of Diagnostic Systems
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