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Identify and analysis crotonylation sites in histone by using support vector machines.

, , , , and . Artif. Intell. Medicine, (2017)

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Identify and analysis crotonylation sites in histone by using support vector machines., , , , and . Artif. Intell. Medicine, (2017)iPTM-mLys: identifying multiple lysine PTM sites and their different types., , , , and . Bioinform., 32 (20): 3116-3123 (2016)Computational prediction of ubiquitination protein using evolutionary profiles and functional domains., , , and . BIBM, page 2296. IEEE Computer Society, (2017)Analyzing Surgical Treatment of Intestinal Obstruction in Children with Artificial Intelligence., , , , , and . Comput. Math. Methods Medicine, (2021)idse-HE: Hybrid embedding graph neural network for drug side effects prediction., , , , and . J. Biomed. Informatics, (2022)pSuc-EDBAM: Predicting lysine succinylation sites in proteins based on ensemble dense blocks and an attention module., , , and . BMC Bioinform., 23 (1): 450 (2022)iRNAD: a computational tool for identifying D modification sites in RNA sequence., , , , , and . Bioinform., 35 (23): 4922-4929 (2019)Integrating unsupervised language model with multi-view multiple sequence alignments for high-accuracy inter-chain contact prediction., , , , , and . Comput. Biol. Medicine, (November 2023)MSDSE: Predicting drug-side effects based on multi-scale features and deep multi-structure neural network., , , and . Comput. Biol. Medicine, (February 2024)MF-EFP: Predicting Multi-Functional Enzymes Function Using Improved Hybrid Multi-Label Classifier., , , , , and . IEEE Access, (2020)