RT Journal
A1 Hoon, Shawn
A1 Ratnapu, Kiran Kumar
A1 Chia, Jer-ming
A1 Kumarasamy, Balamurugan
A1 Juguang, Xiao
A1 Clamp, Michele
A1 Stabenau, Arne
A1 Potter, Simon
A1 Clarke, Laura
A1 Stupka, Elia
T1 Biopipe: A Flexible Framework for Protocol-Based Bioinformatics Analysis
JF Genome Research 
JO Genome Research 
YR 2003 
FD August 01 
VO 13 
IS 8 
SP 1904 
OP 1915 
DO 10.1101/gr.1363103 
UL http://genome.cshlp.org/content/13/8/1904.abstract 
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.