Human Intrigue: Meta-analysis approaches for big questions with big data while shaking up the peer review process

Pac Symp Biocomput. 2022:27:156-162.

Abstract

Scientific innovation has long been heralded the collaborative effort of many people, groups, and studies to drive forward research. However, the traditional peer review process relies on reviewers acting in a silo to critically judge research. As research becomes more cross-disciplinary, finding reviewers with appropriate expertise to provide feedback on an entire paper is increasingly difficult. We sought to pilot a crowd peer review process that allowed reviewers to interact with one another in the spirit of collaborative science. We focused this session on manuscripts using meta-analysis, to fully embrace the importance of collaborative and open scientific research in the field of biocomputing. Our pilot study found that researchers enjoy a more collaborative peer review process and felt that the process led to higher quality feedback for submitting authors than traditional review offers.

Publication types

  • Meta-Analysis

MeSH terms

  • Big Data*
  • Computational Biology
  • Humans
  • Peer Review, Research*
  • Pilot Projects