Literature DB >> 22084254

Gene set analysis in the cloud.

Lu Zhang1, Shengchang Gu, Yuan Liu, Bingqiang Wang, Francisco Azuaje.   

Abstract

UNLABELLED: Cloud computing offers low cost and highly flexible opportunities in bioinformatics. Its potential has already been demonstrated in high-throughput sequence data analysis. Pathway-based or gene set analysis of expression data has received relatively less attention. We developed a gene set analysis algorithm for biomarker identification in the cloud. The resulting tool, YunBe, is ready to use on Amazon Web Services. Moreover, here we compare its performance to those obtained with desktop and computing cluster solutions.
AVAILABILITY AND IMPLEMENTATION: YunBe is open-source and freely accessible within the Amazon Elastic MapReduce service at s3n://lrcv-crp-sante/app/yunbe.jar. Source code and user's guidelines can be downloaded from http://tinyurl.com/yunbedownload.

Mesh:

Year:  2011        PMID: 22084254     DOI: 10.1093/bioinformatics/btr630

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  8 in total

1.  cisPath: an R/Bioconductor package for cloud users for visualization and management of functional protein interaction networks.

Authors:  Likun Wang; Luhe Yang; Zuohan Peng; Dan Lu; Yan Jin; Michael McNutt; Yuxin Yin
Journal:  BMC Syst Biol       Date:  2015-01-21

Review 2.  Single-cell Transcriptome Study as Big Data.

Authors:  Pingjian Yu; Wei Lin
Journal:  Genomics Proteomics Bioinformatics       Date:  2016-02-11       Impact factor: 7.691

Review 3.  Translational biomedical informatics in the cloud: present and future.

Authors:  Jiajia Chen; Fuliang Qian; Wenying Yan; Bairong Shen
Journal:  Biomed Res Int       Date:  2013-03-17       Impact factor: 3.411

Review 4.  Bioinformatics clouds for big data manipulation.

Authors:  Lin Dai; Xin Gao; Yan Guo; Jingfa Xiao; Zhang Zhang
Journal:  Biol Direct       Date:  2012-11-28       Impact factor: 4.540

5.  A novel approach for discovering condition-specific correlations of gene expressions within biological pathways by using cloud computing technology.

Authors:  Tzu-Hao Chang; Shih-Lin Wu; Wei-Jen Wang; Jorng-Tzong Horng; Cheng-Wei Chang
Journal:  Biomed Res Int       Date:  2014-01-22       Impact factor: 3.411

Review 6.  Enabling large-scale biomedical analysis in the cloud.

Authors:  Ying-Chih Lin; Chin-Sheng Yu; Yen-Jen Lin
Journal:  Biomed Res Int       Date:  2013-10-31       Impact factor: 3.411

7.  Bioinformatics on the cloud computing platform Azure.

Authors:  Hugh P Shanahan; Anne M Owen; Andrew P Harrison
Journal:  PLoS One       Date:  2014-07-22       Impact factor: 3.240

8.  rapidGSEA: Speeding up gene set enrichment analysis on multi-core CPUs and CUDA-enabled GPUs.

Authors:  Christian Hundt; Andreas Hildebrandt; Bertil Schmidt
Journal:  BMC Bioinformatics       Date:  2016-09-23       Impact factor: 3.169

  8 in total

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