CateGOrizer 3.218 – Gene Ontology (GO) Terms Classifications Tool

CateGOrizer 3.218

:: DESCRIPTION

CateGOrizer, previously known as “GO Terms Classifications Counter”, is a free web tool for users to batch analyze GO term data sets in terms of GO classes they represent.

::DEVELOPER

NAGRP Bioinformatics Team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

  NO

:: MORE INFORMATION

Citation

Zhi-Liang Hu, Jie Bao and James M. Reecy (2008)
CateGOrizer: A Web-Based Program to Batch Analyze Gene Ontology Classification Categories“.
Online J Bioinform. 9 (2):108-112.

CLARK 1.2.6.1 – Fast and Accurate Classification of Metagenomic and Genomic Sequences

CLARK 1.2.6.1

:: DESCRIPTION

Clark is a novel approach to classify metagenomic reads at the species or genus level with high accuracy and high speed.

::DEVELOPER

Algorithms and Computational Biology Lab ,University of California

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 CLARK

:: MORE INFORMATION

Citation

Ounit R, Wanamaker S, Close TJ, Lonardi S,
CLARK: fast and accurate classification of metagenomic and genomic sequences using discriminative k-mers
BMC Genomics 2015, 16:236.

Microtaxi – Microbial Taxonomic Identification and Classification Server

Microtaxi

:: DESCRIPTION

Microtaxi uses an taxon-specific gene based approach and provides an alternate valuable methodology to carry out the taxonomic classification of newly sequenced or existing bacterial genomes.

::DEVELOPER

MetaBioSys laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Perl

:: DOWNLOAD

 Microtaxi

:: MORE INFORMATION

Citation

BMC Genomics. 2015 May 20;16:396. doi: 10.1186/s12864-015-1542-0.
Using the taxon-specific genes for the taxonomic classification of bacterial genomes.
Gupta A, Sharma VK

Freescore – Classification of Conotoxin Proteins

Freescore

:: DESCRIPTION

Freescore is a scoring system based on local alignment partition functions for the classification of conotoxin proteins

::DEVELOPER

Nazar Zaki , Dr S. Wolfsheimer (stefan.wolfsheimer@mi.parisdescartes.fr)

:: SCREENSHOTS

N/A

::REQUIREMENTS

  • Linux

:: DOWNLOAD

 Freescore

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2011 May 29;12:217. doi: 10.1186/1471-2105-12-217.
Conotoxin protein classification using free scores of words and support vector machines.
Zaki N, Wolfsheimer S, Nuel G, Khuri S.

Strike – Protein-protein Interaction Classification tool

Strike

:: DESCRIPTION

Strike (String Kernel) is a program which classifies protein-protein interaction into “interacting” and “non-interacting” sets based solely on amino acid sequence information. The classification is made by applying the string kernel technique. Two proteins are classified “interacting” if they contain similar subsequences of amino acids.

::DEVELOPER

Nazar Zaki , Bioinformatics Laboratory, UAE University.

:: SCREENSHOTS

N/A

::REQUIREMENTS

:: DOWNLOAD

  Strike

:: MORE INFORMATION

Citation

Adv Exp Med Biol. 2011;696:263-70. doi: 10.1007/978-1-4419-7046-6_26.
Strike: a protein-protein interaction classification approach.
Zaki N, El-Hajj W, Kamel HM, Sibai F.

Magnolia – Classification of Coding and Noncoding RNAs

Magnolia

:: DESCRIPTION

Magnolia is a program suite to classify RNA sequences as protein-coding or noncoding genes by comparative analysis. It also produces advanced multiple sequence alignment for the data.

::DEVELOPER

Bonsai Bioinformatics

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

MAGNOLIA: multiple alignment of protein-coding and structural RNA sequences
Arnaud Fontaine, Antoine de Monte, Helene Touzet
Nucleic Acids Research 36(Web-Server-Issue): 14-18 (2008)

SPACC 2.0 – Spectral Analysis for Class Discovery and Classification

SPACC 2.0

:: DESCRIPTION

SPACC is a classifier that can perform both class discovery and classification

::DEVELOPER

Peng Qiu

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows
  • Matlab

:: DOWNLOAD

 SPACC

:: MORE INFORMATION

Citation

Peng Qiu, and Sylvia K. Plevritis,
Simultaneous Class Discovery and Classification of Microarray Data using Spectral Analysis“,
Journal of Computational Biology, 16(7):935-944, 2009.

CoRAL 1.1.1 – Classification of RNAs by Analysis of Length

CoRAL 1.1.1

:: DESCRIPTION

CoRAL is a machine learning package that can predict the precursor class of small RNAs present in a high-throughput RNA-sequencing dataset. In addition to classification, it also produces information about the features that are most important for discriminating different populations of small non-coding RNAs.

::DEVELOPER

Wang Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • libgsl
  • bigWigToBedGraph (a UCSC kent utility)
  • bedtools
  • samtools
  • RNAfold
  • ruby
  • R package

:: DOWNLOAD

 CoRAL

:: MORE INFORMATION

Citation

Leung,Y.Y., Ryvkin,P., Ungar,L., Gregory,B.D., and Wang, L.-S. (2013)
CoRAL: Predicting non-coding RNAs from small RNA-sequencing.
Nucl. Acids Res. (2013) doi: 10.1093/nar/gkt426

GPCR-GIA – Predicting GPCR Classification

GPCR-GIA

:: DESCRIPTION

The current GPCR-GIA is a 2-layer predictor: the 1st layer prediction engine is for identifying a query protein sequence as GPCR on non-GPCR

::DEVELOPER

Xiao Lab

:: SCREENSHOTS

n/a

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Protein Eng Des Sel. 2009 Nov;22(11):699-705. doi: 10.1093/protein/gzp057. Epub 2009 Sep 22.
GPCR-GIA: a web-server for identifying G-protein coupled receptors and their families with grey incidence analysis.
Lin WZ1, Xiao X, Chou KC.

GPCR-CA – Predicting GPCR Classification

GPCR-CA

:: DESCRIPTION

The GPCR-CA (G-protein-coupled receptor – Cellular Automaton) is a 2-layer predictor: the 1st layer prediction engine is for identifying a query protein sequence as GPCR on non-GPCR; if it is a GPCR protein, the process will be automatically continued with the 2nd-layer prediction engine to further identify its type among the following six main functional classes: (1) rhodopsin-like, (2) secretin-like, (3) metabotrophic/glutamate/pheromone, (4) fungal pheromone, (5) cAMP receptor, and (6) Frizzled/Smoothemed family

::DEVELOPER

Xiao Lab

:: SCREENSHOTS

n/a

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

GPCR-CA: A cellular automaton image approach for predicting G-protein-coupled receptor functional classes.
Xiao X, Wang P, Chou KC.
J Comput Chem. 2009 Jul 15;30(9):1414-23. doi: 10.1002/jcc.21163.