Bioinformatics workflow management system
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A bioinformatics workflow management system is a specialized form of workflow management system designed specifically to compose and execute a series of computational or data manipulation steps, or a workflow, in a specific domain of science, bioinformatics.
There are currently many different workflow systems. Some have been developed more generally as scientific workflow systems for use by scientists from many different disciplines like astronomy and earth science. All such systems are based on an abstract representation of how a computation proceeds in the form of a directed graph, where each node represents a task to be executed and edges represent either data flow or execution dependencies between different tasks. Each system typically provides visual front-end allowing the user to build and modify complex applications with little or no programming expertise.
Comparisons between workflow systems
With a large number of bioinformatics workflow systems to chose from, it becomes difficult to understand and compare the features of the different workflow systems. There has been little work conducted in evaluating and comparing the systems from a bioinformatician's perspective, especially when it comes to comparing the data types they can deal with, the in-built functionalities that are provided to the user or even their performance or usability. Examples of existing comparisons include
- The paper "Scientific workflow systems-can one size fit all?",[1] which provides a high-level framework for comparing workflow systems based on their control flow and data flow properties. The systems compared include Discovery Net, Taverna, Triana, Kepler as well as Yawl and BPEL.
- The paper "Meta-workflows: pattern-based interoperability between Galaxy and Taverna" [2] which provides a more user-oriented comparison between Taverna and Galaxy in the context of enabling interoperability between both systems.
- The infrastructure paper "Delivering ICT Infrastructure for Biomedical Research" [3] compares two workflow systems, Anduril and Chipster, in terms of infrastructure requirements in a cloud-delivery model.
References
- ^ Curcin, V; Ghanem, M (2008), Scientific workflow systems - can one size fit all?, Biomedical Engineering Conference, 2008. CIBEC 2008, IEEE, doi:10.1109/CIBEC.2008.4786077
- ^ Abouelhoda, M; Ghanem, M; Alaa, S (2010), Meta-workflows: pattern-based interoperability between Galaxy and Taverna, Wands '10 Proceedings of the 1st International Workshop on Workflow Approaches to New Data-centric Science, ACM, doi:10.1145/1833398.1833400
- ^
Nyrönen, TH; Laitinen, J; et al. (2012), Delivering ICT infrastructure for biomedical research, Proceedings of the WICSA/ECSA 2012 Companion Volume (WICSA/ECSA '12), ACM
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External links
- Attention: This template ({{cite doi}}) is deprecated. To cite the publication identified by doi:10.1002/cpe.993, please use {{cite journal}} (if it was published in a bona fide academic journal, otherwise {{cite report}} with
|doi=10.1002/cpe.993instead. This paper reviews some of the above workflow systems - Attention: This template ({{cite doi}}) is deprecated. To cite the publication identified by doi:10.1145/1084805.1084814, please use {{cite journal}} (if it was published in a bona fide academic journal, otherwise {{cite report}} with
|doi=10.1145/1084805.1084814instead. from the ACM SIGMOD Record - Attention: This template ({{cite doi}}) is deprecated. To cite the publication identified by doi:10.1109/CIBEC.2008.4786077, please use {{cite journal}} (if it was published in a bona fide academic journal, otherwise {{cite report}} with
|doi=10.1109/CIBEC.2008.4786077instead. paper in CIBEC'08 comparing multiple workflow systems for bioinformatics applications