MusiteDeep: a deep-learning based webserver for protein post-translational modification site prediction and visualization
Published in Nucleic Acids Research, 2020
Abstract
MusiteDeep is an online resource providing a deep-learning framework for protein post-translational modification (PTM) site prediction and visualization. The predictor only uses protein sequences as input and no complex features are needed, which results in a real-time prediction for a large number of proteins. It takes less than three minutes to predict for 1000 sequences per PTM type. The output is presented at the amino acid level for the user-selected PTM types. The framework has been benchmarked and has demonstrated competitive performance in PTM site predictions by other researchers. In this webserver, we updated the previous framework by utilizing more advanced ensemble techniques, and providing prediction and visualization for multiple PTMs simultaneously for users to analyze potential PTM cross-talks directly. Besides prediction, users can interactively review the predicted PTM sites in the context of known PTM annotations and protein 3D structures through homology-based search. In addition, the server maintains a local database providing pre-processed PTM annotations from Uniport/Swiss-Prot for users to download. This database will be updated every three months..
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Recommended citation: Duolin Wang, Dongpeng Liu, Jiakang Yuchi, Fei He, Yuexu Jiang, Siteng Cai, Jingyi Li, Dong Xu. "MusiteDeep: a deep-learning based webserver for protein post-translational modification site prediction and visualization". Nucleic Acids Research, Volume 48, Issue W1, 02 July 2020, Pages W140–W146
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