Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/129705
Title: Biopipe: A flexible framework for protocol-based bioinformatics analysis
Authors: Hoon, S.
Ratnapu, K.K.
Chia, J.-M. 
Kumarasamy, B.
Juguang, X.
Clamp, M.
Stabenau, A.
Potter, S.
Clarke, L.
Stupka, E.
Issue Date: 1-Aug-2003
Citation: Hoon, S., Ratnapu, K.K., Chia, J.-M., Kumarasamy, B., Juguang, X., Clamp, M., Stabenau, A., Potter, S., Clarke, L., Stupka, E. (2003-08-01). Biopipe: A flexible framework for protocol-based bioinformatics analysis. Genome Research 13 (8) : 1904-1915. ScholarBank@NUS Repository.
Abstract: We identify several challenges facing bioinformatics analysis today. Firstly, to fulfill the promise of comparative studies, bioinformatics analysis will need to accommodate different sources of data residing in a federation of databases that, in turn, come in different formats and modes of accessibility. Secondly, the tsunami of data to be handled will require robust systems that enable bioinformatics analysis to be carried out in a parallel fashion. Thirdly, the ever-evolving state of bioinformatics presents new algorithms and paradigms in conducting analysis. This means that any bioinformatics framework must be flexible and generic enough to accommodate such changes. In addition, we identify the need for introducing an explicit protocol-based approach to bioinformatics analysis that will lend rigorousness to the analysis. This makes it easier for experimentation and replication of results by external parties. Biopipe is designed in an effort to meet these goals. It aims to allow researchers to focus on protocol design. At the same time, it is designed to work over a compute farm and thus provides high-throughput performance. A common exchange format that encapsulates the entire protocol in terms of the analysis modules, parameters, and data versions has been developed to provide a powerful way in which to distribute and reproduce results. This will enable researchers to discuss and interpret the data better as the once implicit assumptions are now explicitly defined within the Biopipe framework.
Source Title: Genome Research
URI: http://scholarbank.nus.edu.sg/handle/10635/129705
ISSN: 10889051
Appears in Collections:Staff Publications

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