Literature DB >> 21278189

Conveyor: a workflow engine for bioinformatic analyses.

Burkhard Linke1, Robert Giegerich, Alexander Goesmann.   

Abstract

MOTIVATION: The rapidly increasing amounts of data available from new high-throughput methods have made data processing without automated pipelines infeasible. As was pointed out in several publications, integration of data and analytic resources into workflow systems provides a solution to this problem, simplifying the task of data analysis. Various applications for defining and running workflows in the field of bioinformatics have been proposed and published, e.g. Galaxy, Mobyle, Taverna, Pegasus or Kepler. One of the main aims of such workflow systems is to enable scientists to focus on analysing their datasets instead of taking care for data management, job management or monitoring the execution of computational tasks. The currently available workflow systems achieve this goal, but fundamentally differ in their way of executing workflows.
RESULTS: We have developed the Conveyor software library, a multitiered generic workflow engine for composition, execution and monitoring of complex workflows. It features an open, extensible system architecture and concurrent program execution to exploit resources available on modern multicore CPU hardware. It offers the ability to build complex workflows with branches, loops and other control structures. Two example use cases illustrate the application of the versatile Conveyor engine to common bioinformatics problems. AVAILABILITY: The Conveyor application including client and server are available at http://conveyor.cebitec.uni-bielefeld.de.

Mesh:

Year:  2011        PMID: 21278189     DOI: 10.1093/bioinformatics/btr040

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


  13 in total

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Authors:  Scott Christley; Gary An
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2.  Proteorhodopsin light-enhanced growth linked to vitamin-B1 acquisition in marine Flavobacteria.

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3.  Bioinformatic pipelines in Python with Leaf.

Authors:  Francesco Napolitano; Renato Mariani-Costantini; Roberto Tagliaferri
Journal:  BMC Bioinformatics       Date:  2013-06-21       Impact factor: 3.169

4.  Bacterial community shift in treated periodontitis patients revealed by ion torrent 16S rRNA gene amplicon sequencing.

Authors:  Sebastian Jünemann; Karola Prior; Rafael Szczepanowski; Inga Harks; Benjamin Ehmke; Alexander Goesmann; Jens Stoye; Dag Harmsen
Journal:  PLoS One       Date:  2012-08-01       Impact factor: 3.240

5.  Tavaxy: integrating Taverna and Galaxy workflows with cloud computing support.

Authors:  Mohamed Abouelhoda; Shadi Alaa Issa; Moustafa Ghanem
Journal:  BMC Bioinformatics       Date:  2012-05-04       Impact factor: 3.169

6.  High-Performance Integrated Virtual Environment (HIVE) Tools and Applications for Big Data Analysis.

Authors:  Vahan Simonyan; Raja Mazumder
Journal:  Genes (Basel)       Date:  2014-09-30       Impact factor: 4.096

7.  Comparative genomics of host adaptive traits in Xanthomonas translucens pv. graminis.

Authors:  Lena Hersemann; Daniel Wibberg; Jochen Blom; Alexander Goesmann; Franco Widmer; Frank-Jörg Vorhölter; Roland Kölliker
Journal:  BMC Genomics       Date:  2017-01-05       Impact factor: 3.969

8.  Streaming support for data intensive cloud-based sequence analysis.

Authors:  Shadi A Issa; Romeo Kienzler; Mohamed El-Kalioby; Peter J Tonellato; Dennis Wall; Rémy Bruggmann; Mohamed Abouelhoda
Journal:  Biomed Res Int       Date:  2013-04-24       Impact factor: 3.411

9.  Personalized cloud-based bioinformatics services for research and education: use cases and the elasticHPC package.

Authors:  Mohamed El-Kalioby; Mohamed Abouelhoda; Jan Krüger; Robert Giegerich; Alexander Sczyrba; Dennis P Wall; Peter Tonellato
Journal:  BMC Bioinformatics       Date:  2012-12-13       Impact factor: 3.169

10.  Experiences with workflows for automating data-intensive bioinformatics.

Authors:  Ola Spjuth; Erik Bongcam-Rudloff; Guillermo Carrasco Hernández; Lukas Forer; Mario Giovacchini; Roman Valls Guimera; Aleksi Kallio; Eija Korpelainen; Maciej M Kańduła; Milko Krachunov; David P Kreil; Ognyan Kulev; Paweł P Łabaj; Samuel Lampa; Luca Pireddu; Sebastian Schönherr; Alexey Siretskiy; Dimitar Vassilev
Journal:  Biol Direct       Date:  2015-08-19       Impact factor: 4.540

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