The OMiMa (the Optimized Mixture Markov model) System is a computational tool for identifying functional motifs in DNA or protein sequences. OMiMa System is based on the Optimized Mixture of Markov models that are able to incorporate most dependencies within a motif. Most important, OMiMa is capable to adjust model complexity according to motif dependency structures, so it can minimize model complexity without compromising prediction accuracy. OMiMa uses our fast Markov chain optimization method, the Directed Neighbor-Joining (DNJ), which makes OMiMa more computationally efficent.
SimTandem is a freely available tool for identification of peptides from LC-MS/MS spectra. It is based on a similarity search of mass spectra in a database of theoretical spectra generated from a database of known protein sequences.
Epitopia is a server for detection of immunogenic regions in protein structures or sequences.Epitopia implements a machine learning scheme to rank individual amino acids in the protein, according to their potential of eliciting a humoral immune response.
NetCTL predicts CTL epitopes in protein sequences. NetCTL expands the MHC class I binding predicition to 12 MHC supertypes including the supertypes A26 and B39. The accuracy of the MHC class I peptide binding affinity is significantly improved compared to the earlier version. Also the prediction of proteasonal cleavage has been improved and is now identical to the predictions obtained by the NetChop-3.0 server. The updated version has been trained on a set of 886 known MHC class I ligands.