Literature DB >> 23630176

BioBlend: automating pipeline analyses within Galaxy and CloudMan.

Clare Sloggett1, Nuwan Goonasekera, Enis Afgan.   

Abstract

UNLABELLED: We present BioBlend, a unified API in a high-level language (python) that wraps the functionality of Galaxy and CloudMan APIs. BioBlend makes it easy for bioinformaticians to automate end-to-end large data analysis, from scratch, in a way that is highly accessible to collaborators, by allowing them to both provide the required infrastructure and automate complex analyses over large datasets within the familiar Galaxy environment.
AVAILABILITY AND IMPLEMENTATION: http://bioblend.readthedocs.org/. Automated installation of BioBlend is available via PyPI (e.g. pip install bioblend). Alternatively, the source code is available from the GitHub repository (https://github.com/afgane/bioblend) under the MIT open source license. The library has been tested and is working on Linux, Macintosh and Windows-based systems.

Entities:  

Mesh:

Year:  2013        PMID: 23630176      PMCID: PMC4288140          DOI: 10.1093/bioinformatics/btt199

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


  3 in total

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Journal:  Nat Rev Genet       Date:  2012-09       Impact factor: 53.242

2.  Galaxy CloudMan: delivering cloud compute clusters.

Authors:  Enis Afgan; Dannon Baker; Nate Coraor; Brad Chapman; Anton Nekrutenko; James Taylor
Journal:  BMC Bioinformatics       Date:  2010-12-21       Impact factor: 3.169

3.  Harnessing cloud computing with Galaxy Cloud.

Authors:  Enis Afgan; Dannon Baker; Nate Coraor; Hiroki Goto; Ian M Paul; Kateryna D Makova; Anton Nekrutenko; James Taylor
Journal:  Nat Biotechnol       Date:  2011-11-08       Impact factor: 54.908

  3 in total
  28 in total

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Authors:  Han Hu; Kshitij Khatri; Joseph Zaia
Journal:  Mass Spectrom Rev       Date:  2016-01-04       Impact factor: 10.946

Review 2.  Cloud computing for genomic data analysis and collaboration.

Authors:  Ben Langmead; Abhinav Nellore
Journal:  Nat Rev Genet       Date:  2018-01-30       Impact factor: 53.242

3.  BioMAJ2Galaxy: automatic update of reference data in Galaxy using BioMAJ.

Authors:  Anthony Bretaudeau; Cyril Monjeaud; Yvan Le Bras; Fabrice Legeai; Olivier Collin
Journal:  Gigascience       Date:  2015-05-09       Impact factor: 6.524

Review 4.  Trends in IT Innovation to Build a Next Generation Bioinformatics Solution to Manage and Analyse Biological Big Data Produced by NGS Technologies.

Authors:  Alexandre G de Brevern; Jean-Philippe Meyniel; Cécile Fairhead; Cécile Neuvéglise; Alain Malpertuy
Journal:  Biomed Res Int       Date:  2015-06-01       Impact factor: 3.411

5.  Implementation of Cloud based next generation sequencing data analysis in a clinical laboratory.

Authors:  Getiria Onsongo; Jesse Erdmann; Michael D Spears; John Chilton; Kenneth B Beckman; Adam Hauge; Sophia Yohe; Matthew Schomaker; Matthew Bower; Kevin A T Silverstein; Bharat Thyagarajan
Journal:  BMC Res Notes       Date:  2014-05-23

6.  BioBlend.objects: metacomputing with Galaxy.

Authors:  Simone Leo; Luca Pireddu; Gianmauro Cuccuru; Luca Lianas; Nicola Soranzo; Enis Afgan; Gianluigi Zanetti
Journal:  Bioinformatics       Date:  2014-06-12       Impact factor: 6.937

7.  Open pipelines for integrated tumor genome profiles reveal differences between pancreatic cancer tumors and cell lines.

Authors:  Jeremy Goecks; Bassel F El-Rayes; Shishir K Maithel; H Jean Khoury; James Taylor; Michael R Rossi
Journal:  Cancer Med       Date:  2015-01-04       Impact factor: 4.452

8.  Galaxy Portal: interacting with the galaxy platform through mobile devices.

Authors:  Claus Børnich; Ivar Grytten; Eivind Hovig; Jonas Paulsen; Martin Čech; Geir Kjetil Sandve
Journal:  Bioinformatics       Date:  2016-01-27       Impact factor: 6.937

9.  Reproducible features of small RNAs in C. elegans reveal NU RNAs and provide insights into 22G RNAs and 26G RNAs.

Authors:  Andrew L Blumenfeld; Antony M Jose
Journal:  RNA       Date:  2015-12-08       Impact factor: 4.942

10.  Towards agile large-scale predictive modelling in drug discovery with flow-based programming design principles.

Authors:  Samuel Lampa; Jonathan Alvarsson; Ola Spjuth
Journal:  J Cheminform       Date:  2016-11-24       Impact factor: 5.514

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