PON-Diso is a machine learning based prediction method, which is developed using Random Forest classifier on AAIndex features and Evolutionary features. PON-Diso is a method to predict changes in disorder regions contained in protein caused by amino acid substitutions.
Instructions for submitting queries
PON-Diso allows users to submit queries in three formats.
1) Identifier submission
The users are required to submit protein identifier(s) and variation(s) in fasta-like format. Ensembl protein identifier, NCBI protein ID and UniProtKB/Swiss-Prot accession can be used as identifiers. The identifier should be preceded by greater than sign (>). Multiple variations in a single protein or in multiple proteins can be submitted in a single query.
Example: #Ensembl protein identifier >ENSP00000288602 G10V Q94E #UniProtKB/Swiss-Prot accession identifier >Q16518 P363T R44Q #GI number for protein sequence >6980459 W28L
This format requires users to submit fasta-format amino acid sequence(s) and variation(s) (in fasta-like format) corresponding to the sequence(s). Each sequence should have a header line starting with greater than sign (>) followed by description. The sequence in upper-case characters follows the header line. No characters except the universal 20 amino acid codes are accepted in the sequence(s). The variation(s) corresponding to a sequence should contain the same header line as the sequence. Variation(s) follow the header line and only one variation is allowed per line. The sequence(s) and variation(s) can be pasted in the correponding text-boxes or separate files containing sequence(s) and variation(s) can be submitted.
Example sequences: >ADA_HUMAN MAQTPAFDKPKVELHVHLDGSIKPETILYYGRRRGIALPANTAEGLLNVIGMDKPLTLPD FLAKFDYYMPAIAGCREAIKRIAYEFVEMKAKEGVVYVEVRYSPHLLANSKVEPIPWNQA EGDLTPDEVVALVGQGLQEGERDFGVKARSILCCMRHQPNWSPKVVELCKKYQQQTVVAI DLAGDETIPGSSLLPGHVQAYQEAVKSGIHRTVHAGEVGSAEVVKEAVDILKTERLGHGY HTLEDQALYNRLRQENMHFEICPWSSYLTGAWKPDTEHAVIRLKNDQANYSLNTDDPLIF KSTLDTDYQMTKRDMGFTEEEFKRLNINAAKSSFLPEDEKRELLDLLYKAYGMPPSASAG QNL >Retinal pigment MSIQVEHPAGGYKKLFETVEELSSPLTAHVTGRIPLWLTGSLLRCGPGLFEVGSEPFYHL FDGQALLHKFDFKEGHVTYHRRFIRTDAYVRAMTEKRIVITEFGTCAFPDPCKNIFSRFF SYFRGVEVTDNALVNVYPVGEDYYACTETNFITKINPETLETIKQVDLCNYVSVNGATAH PHIENDGTVYNIGNCFGKNFSIAYNIVKIPPLQADKEDPISKSEIVVQFPCSDRFKPSYV HSFGLTPNYIVFVETPVKINLFKFLSSWSLWGANYMDCFESNETMGVWLHIADKKRKKYL NNKYRTSPFNLFHHINTYEDNGFLIVDLCCWKGFEFVYNYLYLANLRENWEEVKKNARKA PQPEVRRYVLPLNIDKADTGKNLVTLPNTTATAILCSDETIWLEPEVLFSGPRQAFEFPQ INYQKYCGKPYTYAYGLGLNHFVPDRLCKLNVKTKETWVWQEPDSYPSEPIFVSHPDALE EDDGVVLSVVVSPGAGQKPAYLLILNAKDLSEVARAEVEINIPVTFHGLFKKS
Example variations: >ADA_HUMAN R101H R101L S291L >Retinal pigment G75R R97P
Users are required to submit a valid email address where the results will be sent when they are ready.
Ali, H., Urolagin, S., Gurarslan, Ö. and Vihinen, M. (2014), Performance of Protein Disorder Prediction Programs on Amino Acid Substitutions. Hum. Mutat., 35: 794-804. doi: 10.1002/humu.22564
If you have any queries, please feel free to contact us.
|Last updated: 2014-03-06||© Protein Structure and Bioinformatics Group, Lund University 2015|