Sustained software development, not number of citations or journal choice, is indicative of accurate bioinformatic software.

ABSTRACT:

Background

Computational biology provides software tools for testing and making inferences about biological data. In the face of increasing volumes of data, heuristic methods that trade software speed for accuracy may be employed. We have studied these trade-offs using the results of a large number of independent software benchmarks, and evaluated whether external factors, including speed, author reputation, journal impact, recency and developer efforts, are indicative of accurate software.

Results

We find that software speed, author reputation, journal impact, number of citations and age are unreliable predictors of software accuracy. This is unfortunate because these are frequently cited reasons for selecting software tools. However, GitHub-derived statistics and high vers

SUBMITTER: Gardner PP 

PROVIDER: S-EPMC8851831 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature