BoNB 1.2 – Biomarker Selection and Classification from Genome-wide SNP data

BoNB 1.2

:: DESCRIPTION

BoNB (Bag of Naïve Bayes), an algorithm for genetic biomarker selection and subjects classification from the simultaneous analysis of genome-wide SNP data. BoNB is based on the Naïve Bayes classification framework, enriched by three main features: bootstrap aggregating of an ensemble of Naïve Bayes classifiers, a novel strategy for ranking and selecting the attributes used by each classifier in the ensemble and a permutation-based procedure for selecting significant biomarkers, based on their marginal utility in the classification process. BoNB is tested on the Wellcome Trust Case-Control study on Type 1 Diabetes and its performance is compared with the ones of both a standard Naïve Bayes algorithm and HyperLASSO, a penalized logistic regression algorithm from the state-of-the-art in simultaneous genome-wide data analysis.

::DEVELOPER

SYSTEMS BIOLOGY AND BIOINFORMATICS GROUP

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • C++ Compiler

:: DOWNLOAD

 BoNB

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2012;13 Suppl 14:S2. doi: 10.1186/1471-2105-13-S14-S2. Epub 2012 Sep 7.
Bag of Naïve Bayes: biomarker selection and classification from genome-wide SNP data.
Sambo F, Trifoglio E, Di Camillo B, Toffolo GM, Cobelli C.

Biomarker – Biomarker Selection using Logit-Laplacian-net

Biomarker

:: DESCRIPTION

Biomarker uses graph Laplacian regularized logistic regression to integrate biological networks into disease classification and pathway association problems

:: DEVELOPER

Liu Lab, Baylor College of Medicine

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / windows/ MacOsX
  • Matlab

:: DOWNLOAD

 Biomarker

:: MORE INFORMATION

Citation

BMC Genomics. 2013;14 Suppl 8:S7. doi: 10.1186/1471-2164-14-S8-S7. Epub 2013 Dec 9.
Molecular pathway identification using biological network-regularized logistic models.
Zhang W, Wan YW, Allen GI, Pang K, Anderson ML, Liu Z.

lodGWAS 1.0-7 – Genome-Wide Association Analysis of a Biomarker Accounting for Limit of Detection

lodGWAS 1.0-7

:: DESCRIPTION

lodGWAS is a software package for genome-wide association anal-ysis of biomarkers with a limit of detection.

::DEVELOPER

Ahmad Vaez, Ilja M. Nolte<i.m.nolte at umcg.nl>, Peter J. van der Most

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • R

:: DOWNLOAD

 lodGWAS

:: MORE INFORMATION

Citation

lodGWAS: a software package for genome-wide association anal-ysis of biomarkers with a limit of detection.
Vaez A, van der Most PJ, Prins BP, Snieder H, van den Heuvel E, Alizadeh BZ, Nolte IM.
Bioinformatics. 2016 Jan 22. pii: btw021

PAA 1.26.0 – Biomarker Discovery with Protein Microarrays

PAA 1.26.0

:: DESCRIPTION

The R/Bioconductor package PAA (Protein Array Analyzer) facilitates a flexible analysis of protein microarrays for biomarker discovery (esp., ProtoArrays).

::DEVELOPER

Medizinisches Proteom-Center

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / Mac OsX
  • R/ BioConductor

:: DOWNLOAD

 PAA

:: MORE INFORMATION

Citation

PAA: An R/Bioconductor package for biomarker discovery with protein microarrays.
Turewicz M, Ahrens M, May C, Marcus K, Eisenacher M.
Bioinformatics. 2016 Jan 22. pii: btw037

shinyGEO – Identifying Biomarkers in Gene Expression Omnibus datasets

shinyGEO

:: DESCRIPTION

shinyGEO is a web-based application for performing differential expression and survival analysis on Gene Expression Omnibus datasets

::DEVELOPER

Bioinformatics Laboratory at Eastern Connecticut State University.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows
  • R

:: DOWNLOAD

 shinyGEO

:: MORE INFORMATION

Citation

shinyGEO: a web-based application for analyzing Gene Expression Omnibus datasets.
Dumas J, Gargano MA, Dancik GM.
Bioinformatics. 2016 Aug 8. pii: btw519.

BioPlat 2 – Human Cancer Biomarker Discovery

BioPlat 2

:: DESCRIPTION

BioPlat (Biomarkers Platform) is a user-friendly bioinformatic resource, which provides a set of analytic tools and predefined pipelies for the discovery and in silico evaluation of novel prognostic and predictive cancer biomarkers based on integration of different genomics data profiles and re-use of gene expression signature in the context of follow-up data.

::DEVELOPER

BioPlat team

:: SCREENSHOTS

BioPlat

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • Java

:: DOWNLOAD

 BioPlat

:: MORE INFORMATION

Citation

Bioinformatics. 2014 Jun 15;30(12):1782-4. doi: 10.1093/bioinformatics/btu111. Epub 2014 Feb 25.
BioPlat: a software for human cancer biomarker discovery.
Butti MD, Chanfreau H, Martinez D, García D, Lacunza E, Abba MC.

kSolutionVis 1.4 – Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

kSolutionVis 1.4

:: DESCRIPTION

kSolutionVis is a software for selecting multiple biomarker subsets with similarly effective binary classification performances.

::DEVELOPER

Health Informatics Lab (HILab)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ Windows
  • Python

:: DOWNLOAD

kSolutionVis

:: MORE INFORMATION

Citation

J Vis Exp. 2018 Oct 11;(140). doi: 10.3791/57738.
Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances.
Feng X, Wang S, Liu Q, Li H, Liu J, Xu C, Yang W, Shu Y, Zheng W, Yu B, Qi M, Zhou W, Zhou F.

GeneTerrain – Next-generation Panel Biomarker Discovery and Validation software

GeneTerrain

:: DESCRIPTION

GeneTerrain is a next-generation panel biomarker discovery and validation software.

::DEVELOPER

Discovery Informatics and Computing Laboratory@ Indiana University School of Informatics

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows

:: DOWNLOAD

 Please join the mailing group to obtain instructions for downloading a pre-release version of the software.

:: MORE INFORMATION

Citation

You Qian, Shiaofen Fang, and Jake Y. Chen (2008)
GeneTerrain: Visual Exploration of Differential Gene Expression Profiles Organized in Native Biomolecular Interaction Networks
Information Visualization, doi: 10.1057/palgrave.ivs.9500169

BDVAL 1.2 – Biomarker Discovery in High-throughput datasets

BDVAL 1.2

:: DESCRIPTION

BDVAL ( Biomarker Discovery and VALidation ) is an open source project for biomarker discovery in high-throughput datasets.

::DEVELOPER

Campagne Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  •  Java

:: DOWNLOAD

 BDVAL

:: MORE INFORMATION

Citation:

Dorff KC, Chambwe N, Srdanovic M, Campagne F.
BDVal: reproducible large-scale predictive model development and validation in high-throughput datasets.
Bioinformatics. 2010 Oct 1;26(19):2472-3. Epub 2010 Aug 11