SVMcon 1.0 – Protein Contact Map Prediction using Support Vector Machine

SVMcon 1.0

:: DESCRIPTION

SVMcon predicts medium- to long-range residue-residue contacts using Support Vector Machines. The contact predictions are in the CASP format (residue index 1, residue index 2, 0, 8, contact probability). The contact distance threshold is 8 angstrom. The sequence separation between two residues is at least 6 residues.

::DEVELOPER

Dr. Jianlin Cheng

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 SVMcon

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2007 Apr 2;8:113.
Improved residue contact prediction using support vector machines and a large feature set.
Cheng J, Baldi P.

MIEC-SVM 1.1 – Molecular Interaction Energy Component & Support Vector Machine

MIEC-SVM 1.1

:: DESCRIPTION

MIEC-SVM method aims to characterize the energetic patterns of proteins binding to their partners.

::DEVELOPER

Wei Wang’s group

:: SCREENSHOTS

N/A

::REQUIREMENTS

  • Linux
  • Perl

:: DOWNLOAD

 MIEC-SVM

:: MORE INFORMATION

Citation

MIEC-SVM: Automated Pipeline for Protein Peptide/ligand Interaction Prediction.
Li N, Ainsworth RI, Wu M, Ding B, Ainsworth RI, Wang W.
Bioinformatics. 2015 Nov 14. pii: btv666.

MOCSVM 2 – Multiobjective Clustering with Support Vector Machine

MOCSVM 2

:: DESCRIPTION

MOCSVM uses original SVM light implementation for SVM classification.

::DEVELOPER

Bioinformatics Lab (MIU)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows
  • MatLab

:: DOWNLOAD

  MOCSVM

:: MORE INFORMATION

Citation

Maulik U, Mukhopadhyay A, Bandyopadhyay S (2009.)
Combining Pareto-Optimal Clusters using Supervised Learning for Identifying Co-expressed Genes.
BMC Bioinformatics, Vol.10, No. 27.

CompareSVM – Support Vector Machine (SVM) Inference of Gene Regularity Networks

CompareSVM

:: DESCRIPTION

CompareSVM is a tool based on SVM to compare different kernel methods for inference of GRN.

::DEVELOPER

Bioinformatics Group, College of Life Sciences, Zhe Jiang University

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • MatLab

:: DOWNLOAD

 CompareSVM

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2014 Nov 30;15(1):395.
CompareSVM: supervised, Support Vector Machine (SVM) inference of gene regularity networks.
Gillani Z, Akash M, Rahaman M, Chen M.

PSSM-DT – Identifying DNA-binding proteins by combining Support Vector Machine and PSSM Distance Transformation

PSSM-DT

:: DESCRIPTION

SVM-PSSM-DT is a web server for for identifying the DNA-binding proteins by combining Support Vector Machine and PSSM Distance Transformation.

::DEVELOPER

Liu Lab, Harbin Institute of Technology Shenzhen Graduate School.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows/ MacOsX
  • Java

:: DOWNLOAD

 PSSM-DT

 

:: MORE INFORMATION

Citation

BMC Syst Biol. 2015;9 Suppl 1:S10. doi: 10.1186/1752-0509-9-S1-S10. Epub 2015 Feb 6.
Identifying DNA-binding proteins by combining support vector machine and PSSM distance transformation.
Xu R, Zhou J, Wang H, He Y, Wang X, Liu B.

miRPredictor – miRNA Target Predictor based on Support Vector Machine

miRPredictor

:: DESCRIPTION

miRPredictor is a novel miRNA target predictor which is based on support vector machine (SVM), a widely-used machine learning approach, combined with feature selection procedure. We considered different types of features including the flanking sequences of the potential targets and pattern information. The features selected were also analyzed to dig out the intrinsic mechanism of miRNA-target interaction.

::DEVELOPER

BIS @ Zhejiang University

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/MacOsX/Linux
  • Perl

:: DOWNLOAD

 miRPredictor

:: MORE INFORMATION