2-hydroxyisobutyrylation sites prediction tools

1) iLys-Khib: Identify lysine 2-Hydroxyisobutyrylation sites using mRMR feature selection and fuzzy SVM algorithm, Chemometrics Intelligent Laboratory Systems 2019.

2) KhibPred: Accurate prediction of species-specific 2-hydroxyisobutyrylation sites based on machine learning frameworks, Analytical Biochemistry 2020.

3) DeepKhib: A deep-learning framework for lysine 2-Hydroxyisobutyrylation sites prediction, Frontiers in Cell and Development Biology 2020.

Crotonylation sites prediction tools

1) CrotPred: A discrete hidden markov model for detecting histone crotonyllysine sites, Communications in Mathematical and in Computer Chemistry 2016.

2) Deep-Kcr: Accurate detection of lysine crotonylation sites using deep learning method, Briefings in Bioinformatics 2021.

3) LightGBM-CroSite: Prediction of protein crotonylation sites through LightGBM classifier based on SMOTE and elastic net, Analtical Biochemistry 2020.

4) nhKcr: A new bioinformatics tool for predicting crotonylation sites on human nonhistone proteins based on deep learning, Briefings in Bioinformatics 2021.

Malonylation sites prediction tools

1) Mal-Lys: Prediction of lysine malonylation sites in proteins integrated sequence-based features with mRMR feature selection, Scientific Reports 2016.

2) SPRINT-Mal: Predicting lysine-malonylation sites of proteins using sequence and predicted structural features, Jounal of Computational Chemistry 2018.

3) LEMP: Integration of a deep learning classifier with a random forest approach for predicting malonylation sites, Genomics, Proteomics & Bioinformatics 2018.

4) Mal-Prec: Computational prediction of protein Malonylation sites via machine learning based feature integration, BMC Genomic 2020.

Ubiquitination sites prediction tools

1) ESA-UbiSite: Accurate prediction of human ubiquitination sites by identifying a set of effective negatives, Bioinformatics 2017.

2) deepUbiquitylation: Large-scale prediction of protein ubiquitination sites using a multimodal deep architecture, BMC Systems Biology 2018.

3) ArabidopsisUbq: Computational prediction of protein ubiquitination sites mapping on Arabidopsis thaliana, Computational Biology and Chemistry 2020.

Succinylation sites prediction tools

1) DeepSuccinySite: A deep learning based approach for protein succinylation site prediction, BMC Bioinformatics 2020.

2) SuccSite: Incorporating amino acid composition and informative k-spaced amino acid pairs to identify protein succinylation sites, Genomics Proteomics & Bioinformatics 2020.

3) HybridSucc: A hybrid-learning architecture for general and species-specific succinylation site prediction, Genomics Proteomics & Bioinformatics 2020.

Acetylation sites prediction tools

1) PHOSIDA: Predicting post-translational lysine acetylation using support vector machines, Bioinformatics 2010.

2) ProAcePred: Prokaryote lysine acetylation sites prediction based on elastic net feature optimization, Bioinformatics 2018.