ISSPred
From DrugPedia: A Wikipedia for Drug discovery
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[edit] ISSPred
ISSPred is a prediction server that predicts Intein Post-translational modification (Protein Splicing) in proteins.It is SVM based method that exploits different features of protein such as amino acid composition, dipeptide composition. it has three models of prediction; Prediction of Intein Domains, prediction of intein containing proteins and Prediction of Intein's N and C terminal Splice sites.
[edit] Availability of ISSPred Webserver:
This server is hosted at Bioinformatics Center, IMTECH, Chandigarh and is available at ISSPred
[edit] Algorithm behind TBpred
[edit] Dataset
Intein data was obtained from Inbase database. It represents intein sequences with corresponding N and C Terminal Splice Sites, covering all 3 kingdoms of life i.e. Archea (147), prokaryotes (201) and Eukaryotes (89).
From this they selected a total of 69 experimentally proved Inteins as annotated by Inbase Database. For Intein prediction they took these 69 as positive dataset and 600 protein sequences (randomly selected from three species as Archaeoglobus fulgidus (Archea) , Neisseria meningitidis (Prokaryote), Drosophila melanogaster (Eukaryote) due to absence of a single intein sequence in them as reported by InBase) as negative dataset.
For Intein's Splice Site prediction they collected N and C terminal splice site of 16 amino acid length as positive and 16 amino acid motifs obtained from the corresponding protein sequences by sliding window method considered as negative dataset.All protein sequences were obtained from Swiss-Prot Database.
[edit] Support Vector Machine & Evaluation Procedures
Support vector machines (SVMs) are a set of related supervised learning methods used for classification and regression.Machine learning tools have been proved useful and successful in identification of molecular patterns. Previously concept of SVM has been successfully utilized in the protein structure prediction, B-cell , T-cell epitope prediction, identification of the MHC binding peptides, sub cellular localization etc. In the present study, a freely downloadable package of SVM ie SVM light has been used to exploit different sequence features like Amino acid, Dipeptide composition and Binary patterns. For evaluation of prediction they used threshold dependent measures like Sensitivity and Specificity.
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[edit] Useful Links to various PTM related resources
- dbPTM Useful information repository of protein post-translational modification (PTMs).
- ProMoST Calculate the effect of single or multiple posttranslational modifications (PTMs) on protein isoelectric point (pI) and molecular weight and displays the calculated patterns as two-dimensional (2D) gel images.
- PhosphoELM A Database of S/T/Y Phosphorylation sites
- Expasy Proteomics ToolsLinks of Database and prediction servers for different types of PTM at Expasy
