PSP – Prediction of Structural Aspects of Protein Residues

PSP

:: DESCRIPTION

PSP server contains a collection of web services that address several protein structure prediction (PSP) sub-problems. Each of these sub-problems focuses on a single structural feature of a protein and the PSP server is using a Learning Classifier System to predict them for a given sequence of amino acids.

::DEVELOPER

PSP team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Web Browser

:: DOWNLOAD

:: MORE INFORMATION

Citation:

Bioinformatics. 2012 Oct 1;28(19):2441-8. Epub 2012 Jul 25.
Contact map prediction using a large-scale ensemble of rule sets and the fusion of multiple predicted structural features.
Bacardit J, Widera P, Márquez-Chamorro A, Divina F, Aguilar-Ruiz JS, Krasnogor N.

InterMap3D – Predicting and Visualizing Co-evolving Protein Residues

InterMap3D

:: DESCRIPTION

InterMap3D predicts interacting protein residues by identifying co-evolving pairs of aminoacids from an alignment of protein sequences.

::DEVELOPER

DTU Health Tech

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Web browser

:: DOWNLOAD

:: MORE INFORMATION

Citation:

InterMap3D: predicting and visualizing co-evolving protein residues.
Gouveia-Oliveira R, Roque FS, Wernersson R, Sicheritz-Ponten T, Sackett PW, Mølgaard A, Pedersen AG.
Bioinformatics. 2009 Aug 1;25(15):1963-5. doi: 10.1093/bioinformatics/btp335.

CCMpred 0.3.2 – Prediction of Protein Residue-residue Contacts from Correlated Mutations

CCMpred 0.3.2

:: DESCRIPTION

CCMpred is a C implementation of a Markov Random Field pseudo-likelihood maximization for learning protein residue-residue contacts

::DEVELOPER

Söding Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux
C Compiler

:: DOWNLOAD

CCMpred

:: MORE INFORMATION

Citation:

Bioinformatics. 2014 Jul 26. pii: btu500.
CCMpred-fast and precise prediction of protein residue-residue contacts from correlated mutations.
Seemayer S1, Gruber M1, Söding J

ProSAT – PROtein reSidue Annotation Toolkit

ProSAT

:: DESCRIPTION

ProSAT toolkit is a set of programs that allow building SVM based models for annotating amino acid residues in protein sequences using user supplied features (like PSI-BLAST profiles, or PSIPred profiles). In particular, the toolkit builds features using a window around the residue, and is equipped with a specialized kernel function (normalized second order exponential kernel function nsoe ) along with the standard svm kernel function.

:: DEVELOPER

Professsor Huzefa Rangwala (rangwala@cs.gmu.edu) and Professsor George Karypis

:: SCREENSHOTS

N/a

:: REQUIREMENTS

Windows/ Linux

:: DOWNLOAD

ProSAT

:: MORE INFORMATION

Citation

“A kernel framework for protein residue annotation“.
Huzefa Rangwala, Christopher Kauffman and George Karypis.
Lecture Notes in Computer Science Volume 5476, 2009, pp 439-451

svmPRAT 1.0 – svm-Based Protein Residue Annotation Toolkit

svmPRAT 1.0

:: DESCRIPTION

svmPRAT is a general purpose protein residue annotation toolkit to allow biologists to formulate residue-wise prediction problems. svmPRAT formulates annotation problem as a classification or regression problem using support vector machines. The key features of svmPRAT are its ease of use to incorporate any user-provided information in the form of feature matrices. For every residue svmPRAT captures local information around the reside to create fixed length feature vectors. svmPRAT implements accurate and fast kernel functions, and also introduces a flexible window-based encoding scheme that allows better capture of signals for certain prediction problems.

::DEVELOPER

Huzefa Rangwala

:: SCREENSHOTS

Command Line

:: REQUIREMENTS

Linux / MacOsX / Windows

:: DOWNLOAD

svmPRAT

:: MORE INFORMATION

Citation:

BMC Bioinformatics. 2009 Dec 22;10:439.
svmPRAT: SVM-based protein residue annotation toolkit.
Rangwala H, Kauffman C, Karypis G.

Coevolution – Coevolution Analysis of Protein Residues

Coevolution

:: DESCRIPTION

Coevolution , an integrated online system that enables comparative analyses of residue coevolution with a comprehensive set of commonly used scoring functions, including Statistical Coupling Analysis (SCA), Explicit Likelihood of Subset Variation (ELSC), mutual information and correlation-based methods.

::DEVELOPER

Gerstein Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

Coevolution

:: MORE INFORMATION

Citation:

Kevin Y. Yip, Prianka Patel, Philip M. Kim, Donald M. Engelman, Drew McDermott and Mark Gerstein
An Integrated System for Studying Residue Coevolution in Proteins
Bioinformatics (2008) 24 (2): 290-292.