LPI-HyADBS: a hybrid framework for lncRNA-protein interaction prediction integrating feature selection and classification

Background: Long noncoding RNAs (lncRNAs) have dense linkages with a plethora of important cellular activities. lncRNAs exert functions by linking with corresponding RNA-binding proteins. Since experimental techniques to detect lncRNA-protein interactions (LPIs) are laborious and time-consuming, a f...

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Bibliographic Details
Main Authors:	Duan, Q. (Author), Peng, L. (Author), Tang, J. (Author), Tian, X. (Author), Xu, H. (Author), Zhou, L. (Author)
Format:	Article
Language:	English
Published:	BioMed Central Ltd 2021
Subjects:	Adaptive boosting amino acid sequence Amino Acid Sequence biology Classification (of information) Computational Biology Cross validation C-SVM Deep neural network Deep neural networks Ensemble learning Feature extraction Feature selection Feature selection and classification Features selection Forecasting genetics Hybrid framework Interaction prediction lncRNA-protein interaction Lncrna-protein interaction long untranslated RNA metabolism Neural Networks, Computer Protein interaction Proteins RNA binding protein RNA, Long Noncoding RNA-Binding Proteins Support vector machines Xgboost XGBoost
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LPI-HyADBS: a hybrid framework for lncRNA-protein interaction prediction integrating feature selection and classification

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