| APSSP2 | This server predicts secondary structure of protein's from their amino acid sequence with high accuracy. It uses the multiple alignment, neural network and MBR techniques. This server participates in number of world wide competition like CASP, CAFASP and EVA (Raghava 2002; CASP5 A-31). |
| PROCLASS | Prediction of structural class of proteins such as Alpha or Beta or Alpha+Beta or Alpha/Beta (Raghava 1999; J. Biosciences 24:176). |
| PSA | This server allow user to analysis of protein sequence and present the analysis in Graphical and Textual format. This allows property plots of 36 parameter (like Hydrophobicity Plot, Polarity, Charge) of single sequence and multiple sequence alignment (Raghava 2001; Biotech Software and Internet Report, 2:255). |
| RPFOLD | It allows to predict top 5 similar fold in PDB (Protein DataBank) for a given protein sequence (query). |
| BTeval | Benchmarking of Beta Turn prediction methods on-line via Internet (Kaur and Raghava 2002; Bioinformatics 18:1508-14). The user can see the performance of their method or existing methods (Kaur and Raghava 2003; Journal of Bioinformatics and Computational Biology 1:495-504) |
| BetatTPred2 | Prediction of Beta Turns in Proteins using Neural Network and multiple alignment techniques. This is highly accurate method for beta turn prediction (Kaur and Raghava 2003; Protein Science 12:627). |
| GammaPred | Prediction of Gamma-turns in Proteins using Multiple Alignment and Secondary Structure Information (Kaur and Raghava 2003; Protein Science; 12:923). |
| AlphaPred | Prediction of Alpha-turns in Proteins using Multiple Alignment and Secondary Structure Information (Kaur & Raghava 2004; Proteins 55:83-90). |
| BetaTPred | A server for predicting Beta Turns in proteins using existing statistical methods. This allows consensus prediction from various methods (Kaur and Raghava 2002; Bioinformatics 18:498). |
| CHpredict | The CHpredict server predict two types of interactions: C-H...O and C-H...PI interactions. For C-H...O interaction, the server predicts the residues whose backbone Calpha atoms are involved in interaction with backbone oxygen atoms and for C-H...PI interactions, it predicts the residues whose backbone Calpha atoms are involved in interaction with PI ring system of side chain aromatic moieties. |
| AR_NHPred | A web server for predicting the aromatic backbone NH interaction in a given amino acid sequence where the pi ring of aromatic residues interact with the backbone NH groups. The method is based on the neural network training on PSI-BLAST generated position specific matrices and PSIPRED predicted secondary structure (Kaur and Raghava 2004; Febs Lett. 564:47-57) |
| TBBpred | It predicts the whether a protein is outer membrane betat-barrel protein or not. It also predicts transmembrane Beta barrel regions in a given protein sequence. (Natt et al. 2004; Proteins 56:11-8). |
| Betaturns | This server predicts the beta turns and their types in a protein from its amino acid sequence (Kaur and Raghava 2004; Bioinformatics 20:2751-8). |
| PEPstr | The Pepstr server predicts the tertiary structure of small peptides with sequence length varying between 7 to 25 residues. The prediction strategy is based on the realization that ?-turn is an important and consistent feature of small peptides in addition to regular structures. |
| BhairPred | Prediction of beta hairpins in proteins using ANN and SVM techniques. In this method secondary structure and multiple sequence alignment are used to predict the beta hairpins (Kumar et al. 2005; Nucleic Acids Res. 33:W154-9) |
| SARpred | Prediction of real value of surface accessibility instead of buried or exposed residues in proteins from amino acid sequence (Garg et al. 2005; Proteins) |
| OXbench | A bench-mark for evaluation of protein multiple sequence alignment accuracy (Raghava et al. 2003; BMC Bioinformatics 4-47). |
