TY - JOUR
T1 - Industrial methodology for process verification in research (IMPROVER)
T2 - Toward systems biology verification
AU - Meyer, Pablo
AU - Hoeng, Julia
AU - Rice, J. Jeremy
AU - Norel, Raquel
AU - Sprengel, Jörg
AU - Stolle, Katrin
AU - Bonk, Thomas
AU - Corthesy, Stephanie
AU - Royyuru, Ajay
AU - Peitsch, Manuel C.
AU - Stolovitzky, Gustavo
N1 - Funding Information:
Funding: IBM and PMI authors performed this work under a joint research collaboration funded by PMI.
PY - 2012/5
Y1 - 2012/5
N2 - Motivation: Analyses and algorithmic predictions based on high-throughput data are essential for the success of systems biology in academic and industrial settings. Organizations, such as companies and academic consortia, conduct large multi-year scientific studies that entail the collection and analysis of thousands of individual experiments, often over many physical sites and with internal and outsourced components. To extract maximum value, the interested parties need to verify the accuracy and reproducibility of data and methods before the initiation of such large multi-year studies. However, systematic and well-established verification procedures do not exist for automated collection and analysis workflows in systems biology which could lead to inaccurate conclusions. Results: We present here, a review of the current state of systems biology verification and a detailed methodology to address its shortcomings. This methodology named 'Industrial Methodology for Process Verification in Research' or IMPROVER, consists on evaluating a research program by dividing a workflow into smaller building blocks that are individually verified. The verification of each building block can be done internally by members of the research program or externally by 'crowd-sourcing' to an interested community. www.sbvimprover.com. Implementation: This methodology could become the preferred choice to verify systems biology research workflows that are becoming increasingly complex and sophisticated in industrial and academic settings.
AB - Motivation: Analyses and algorithmic predictions based on high-throughput data are essential for the success of systems biology in academic and industrial settings. Organizations, such as companies and academic consortia, conduct large multi-year scientific studies that entail the collection and analysis of thousands of individual experiments, often over many physical sites and with internal and outsourced components. To extract maximum value, the interested parties need to verify the accuracy and reproducibility of data and methods before the initiation of such large multi-year studies. However, systematic and well-established verification procedures do not exist for automated collection and analysis workflows in systems biology which could lead to inaccurate conclusions. Results: We present here, a review of the current state of systems biology verification and a detailed methodology to address its shortcomings. This methodology named 'Industrial Methodology for Process Verification in Research' or IMPROVER, consists on evaluating a research program by dividing a workflow into smaller building blocks that are individually verified. The verification of each building block can be done internally by members of the research program or externally by 'crowd-sourcing' to an interested community. www.sbvimprover.com. Implementation: This methodology could become the preferred choice to verify systems biology research workflows that are becoming increasingly complex and sophisticated in industrial and academic settings.
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U2 - 10.1093/bioinformatics/bts116
DO - 10.1093/bioinformatics/bts116
M3 - Review article
C2 - 22423044
AN - SCOPUS:84860475570
SN - 1367-4803
VL - 28
SP - 1193
EP - 1201
JO - Bioinformatics
JF - Bioinformatics
IS - 9
M1 - bts116
ER -