PHOSFER uses a novel machine-learning approach in order to predict phosphorylation sites in soybean proteins, and will be expanded to predict for other plants in the future.
PhosSNP is a database of Phosphorylation-related SNP. we defined a phosphorylation-related SNP (phosSNP) as a non-synonymous SNP (nsSNP) that affects the protein phosphorylation status.
PhosphoPICK is a method for predicting kinase substrates using cellular context information, and is currently able to make predictions for 59 human kinases.
HMMpTM is a Hidden Markov Model based method capable of predicting the topology of transmembrane proteins and the existence of kinase specific phosphorylation and N/O-linked glycosylation sites across the protein sequence.
DAPPLE is a homology-based method for predicting phosphorylation sites in an organism of interest. It uses BLAST searches of experimentally-determined phosphorylation sites in one organism (or several organisms) to predict phosphorylation sites in an organism of interest. It outputs a table containing information helpful for choosing phosphorylation sites that are of interest to you, such as the number of sequence differences between the query site and the hit site, the location of the query site and the hit site in their respective intact proteins, and whether the corresponding intact proteins are reciprocal BLAST hits (and thus predicted orthologues).
MPTM is a web-based text mining tool that extracts and incorporates comprehensive knowledge about post-translational modification with their underlying substrate,enzyme,site,disease,and etc. This tool integrates available data not only from the published literature but also from the biological databases. Currently, users can browse the web server MPTM and see the results by entering the name of protein or other terms. Moreover, users can download data in the MPTMDB. In addition, using the “Interaction Search” to find potential substrate-enzyme associations.
NetPhorest integrates in vitro kinase and phosphopeptide-binding domain specificity assays with publically accessible known in vivo substrate lists in order to generate substrate specificity descriptions for individual proteins as well as protein families.
PhosNetConstruct is a tool to predict novel phosphorylation networks based on the preference of certain kinase families to phosphorylate specific functional protein families (domains). It identifies the potentially phosphorylated proteins from a given set of proteins and predicts target kinases which in turn would phosphorylate these identified phosphoproteins based on their domain compositions.
