Confero 0.1 – Integrated Contrast and Gene Set Platform

Confero 0.1

:: DESCRIPTION

Confero is a contrast data and gene set platform for downstream analysis and biological interpretation of omics data.

::DEVELOPER

Confero team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / MacOsX
  • Java
  • Perl
  • MySQL Server

:: DOWNLOAD

 Confero

:: MORE INFORMATION

Citaton

BMC Genomics. 2013 Jul 29;14:514. doi: 10.1186/1471-2164-14-514.
Confero: an integrated contrast data and gene set platform for computational analysis and biological interpretation of omics data.
Hermida L1, Poussin C, Stadler MB, Gubian S, Sewer A, Gaidatzis D, Hotz HR, Martin F, Belcastro V, Cano S, Peitsch MC, Hoeng J.

CMF – Contrast Motif Finder

CMF

:: DESCRIPTION

CMF (Contrast Motif Finder) Contrast motif finder that finds motifs with differential enrichment between two datasets.CMF aims to take advantage of multiple high quality binding datasets to identify subtle regulatory signals, such as context-dependent motifs, within bound sequences. It is specifically designed to discriminate between two sets of bound sequences and takes into account false positive sites when updating PWMs and other model parameters.

::DEVELOPER

Qing Zhou

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • C Compiler

:: DOWNLOAD

 CMF

:: MORE INFORMATION

CONTRAST 1.0 – Multiple Sequence de novo Gene Predictor

CONTRAST 1.0

:: DESCRIPTION

CONTRAST predicts protein-coding genes from a multiple genomic alignment using a combination of discriminative machine learning techniques. A two-stage approach is used, in which output from local classifiers is combined with a global model of gene structure. CONTRAST is trained using a novel procedure designed to maximize expected coding region boundary detection accuracy.

::DEVELOPER

Chuong Do (chuongdo@cs.stanford.edu)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 CONTRAST

:: MORE INFORMATION

Citation

Gross SS, Do CB, Sirota M, Batzoglou S.
CONTRAST: A Discriminative, Phylogeny-free Approach to Multiple Informant De Novo Gene Prediction.
Genome Biology, submitted.