MHC-I peptide Screening using Fuzzy Inference System - Leishmania donovani proteome
About MHC-FIS-LdDB is a database of peptides (L. donovani proteome) categorized by the fuzzy inference system. The categorization is based on the six different epitope features including normalized score based on binding prediction of 27 major alleles by four different machine learning tools, normalized score from prediction of T-cell propensity, normalized score from prediction of pro-inflammatory response, normalized score form proteasome cleavage prediction, normalized score of TAP transport efficiency, and normalized score based on BLSAT continuous similarity with human proteins. A total of 60 fuzzy rules were implemented to determine the probable epitope for the peptide: "Low", "Moderate", "High", or "Very High". The database has easy search capabilities and gives complete access to data.
Access:
The web interface to access the database can be found here
Cite: Saravanan V. (2022). "Harnessing Fuzzy Rule Based System for Screening Major Histocompatibility Complex Class I Peptide Epitopes from the Whole Proteome: An Implementation on the Proteome of Leishmania donovani", Journal of Computational Biology (Accepted). DOI: 10.1089/cmb.2021.0464.