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== Background ==
One of the biggest challenges in bioinformatics is documenting and sharing [[Scientific workflow system#Scientific workflows|scientific workflows]] in such a way that the computation and its results can be peer-reviewed or reliably reproduced.<ref>{{cite journal|title=Ten Simple Rules for Reproducible Computational Research|first1=Geir Kjetil|last1=Sandve|first2=Anton|last2=Nekrutenko|first3=James|last3=Taylor|first4=Eivind|last4=Hovig|date=24 October 2013|journal=PLOS Computational Biology|volume=9|issue=10|pages=e1003285|doi=10.1371/journal.pcbi.1003285|pmid=24204232|pmc=3812051 |bibcode=2013PLSCB...9E3285S |doi-access=free }}</ref> Bioinformatic [[Pipeline (software)|pipelines]] typically use multiple pieces of software, each of which typically has multiple versions available, multiple input parameters, multiple outputs, and possibly platform-specific configurations. As with experimental parameters in a laboratory protocol, small changes in computational parameters may have a large impact on the scientific validity of the results. The BioCompute Framework provides an [[Object-oriented design|object oriented design]] from which a BCO that contains details of a pipeline and how it was used can be constructed, [[digitally signed]], and shared. The BioCompute concept was originally developed to satisfy FDA regulatory research and review needs for evaluation, validation, and verification of genomics data. However, the Biocompute Framework follows FAIR Data Principles<ref>{{Cite journal|
== Utility ==
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