TY - JOUR
T1 - Biopipe
T2 - A flexible framework for protocol-based bioinformatics analysis
AU - Hoon, Shawn
AU - Ratnapu, Kiran Kumar
AU - Chia, Jer Ming
AU - Kumarasamy, Balamurugan
AU - Juguang, Xiao
AU - Clamp, Michele
AU - Stabenau, Arne
AU - Potter, Simon
AU - Clarke, Laura
AU - Stupka, Elia
PY - 2003/8/1
Y1 - 2003/8/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=0043026713&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0043026713&partnerID=8YFLogxK
M3 - Article
C2 - 12869579
AN - SCOPUS:0043026713
VL - 13
SP - 1904
EP - 1915
JO - Genome Research
JF - Genome Research
SN - 1088-9051
IS - 8
ER -