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Open Access Highly Accessed Research article

Prediction of vitamin interacting residues in a vitamin binding protein using evolutionary information

Bharat Panwar, Sudheer Gupta and Gajendra P S Raghava*

Author Affiliations

Bioinformatics Centre, Institute of Microbial Technology (CSIR), Sector 39A, Chandigarh, India

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BMC Bioinformatics 2013, 14:44  doi:10.1186/1471-2105-14-44

Published: 7 February 2013

Additional files

Additional file 1: Figure S1–S5:

The TSL representation of sliding patterns (17-residues length) of ATP, GTP, NAD, FAD and mannose. The central residue (9th position) is showing interacting (positive) and non-interacting (negative) residues. Figure S6–S9. The TSL representation of sliding patterns (17-residues length) for prediction of VIRs, VAIRs, VBIRs and PLPIRs. The central residue (9th position) is showing VIRs (positive) and non-VIRs (negative). Table S1. SVM-based prediction performances of surface accessibility (SA) and Hybrid (PSSM + SA) approaches for four different types of prediction methods on both realistic and balanced datasets. The values of standard errors are also given with performances. Table S2. SVM-based prediction performances (at the default threshold) of PSSM approach; according to their total number PSI-BLAST hits of different independent datasets. Table S3. SVM-based prediction performances (at the default threshold) of binary approach on the different independent datasets.

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