Submission + - 10 Easy Rules to Curb Over-optimistic Reporting in Computational Biology (plos.org)
Causes of this problem are diverse, numerous, and interrelated. The effects of 'fishing for significance' strategies or selective/incomplete reporting are exacerbated by design issues or publication bias. Research and guidelines on how to reduce overoptimistic reporting in the context of computational research, including computational biology as an important special case, however, are surprisingly scarce. Many methodological articles published in computational literature report the superior performance of new methods , too often in general terms and—directly or indirectly—implying that the presented positive results are generalizable to other settings.
Such overoptimistic reporting confuses readers, makes literature less credible and more difficult to interpret, and might even ultimately lead to a waste of resources in some cases.
Here are ten simple rules to address the problem of overoptimistic reporting.