SLIDER (Super-fast predictor of proteins with Long Intrinsically DisordERed regions) predicts whether a given protein sequence has long disordered segment(s), i.e., segment(s) with at least 30 consecutive disordered residues.
Multi-VORFFIP is a structure-based, machine learning, computational method designed to predict protein-protein, protein-peptide, protein-DNA and protein-RNA binding sites. M-VORFFIP integrates a wide and heterogeneous set of residue- and environment-based information using a two-step Random Forest ensemble classifier.
VORFFIP (Voronoi Random Forest Feedback Interface Predictor) is structure-based computational method for prediction of protein binding sites.
STRING (search tool for recurring instances of neighbouring genes) is a database and web resource dedicated to protein-protein interactions, including both physical and functional interactions. It weights and integrates information from numerous sources, including experimental repositories, computational prediction methods and public text collections, thus acting as a meta-database that maps all interaction evidence onto a common set of genomes and proteins.
Hao Lin, Chen Ding, Lu-Feng Yuan, Wei Chen, Hui Ding, Zi-Qiang Li, Feng-Biao Guo, Jian Huang, Ni-Ni Rao. (2013)
Predicting subchloroplast locations of proteins based on the general form of Chou’s pseudo amino acid composition: approached from optimal tripeptide composition.
International Journal of Biomathematics, 6(2): 1350003.