Protein ubiquitination site detection software tools | Post-translational modification data analysis
Protein ubiquitination is one of the most important reversible post-translational modifications (PTMs). In many biochemical, pathological and pharmaceutical studies on understanding the function of proteins in biological processes, identification of ubiquitination sites is an important first step.
An informative physicochemical property mining algorithm for mining informative physicochemical properties from protein sequences to build an SVM-based prediction system. UbiPred can predict ubiquitylation sites accompanied with a prediction score each to help biologists in identifying promising sites for experimental verification.
Enables mapping of thousands of novel and known protein phosphorylation sites across species, accessible through an easy-to-use web interface. This is achieved through pairwise sequence alignment of orthologous protein residues. PhosphOrtholog is generic being applicable to other PTM datasets such as acetylation, ubiquitination and methylation.
A human-specific ubiquitination site predictor through the integration of multiple complementary classifiers. Firstly, a Support Vector Machine (SVM) classier was constructed based on the composition of k-spaced amino acid pairs (CKSAAP) encoding, which has been utilized in our previous yeast ubiquitination site predictor. To further exploit the pattern and properties of the ubiquitination sites and their flanking residues, three additional SVM classifiers were constructed using the binary amino acid encoding, the AAindex physicochemical property encoding and the protein aggregation propensity encoding, respectively. Through an integration that relied on logistic regression, the resulting predictor termed hCKSAAP_UbSite achieved an area under ROC curve (AUC) of 0.770 in 5-fold cross-validation test on a class-balanced training dataset.
A web server that could predict ubiquitination sites in proteins. With the assistance of SVM, the highlight of iUbiq-Lys is to employ amino acid sequence features extracted from the sequence evolution information via grey system model (Grey-PSSM).
Allows users to identify lysine ubiquitylation sites based on MDDLogo-identified substrate motifs. UbiSite permits users to submit their protein sequences through a web-based interface. This tool assists users to develop prediction models that can be scaled to big data. It also represents a web resource and contains several information about the identification of protein ubiquitination sites.