Performance evaluation measures for protein complex prediction

Genomics. 2019 Dec;111(6):1483-1492. doi: 10.1016/j.ygeno.2018.10.003. Epub 2018 Oct 10.

Abstract

Protein complexes play a dominant role in cellular organization and function. Prediction of protein complexes from the network of physical interactions between proteins (PPI networks) has thus become one of the important research areas. Recently, many computational approaches have been developed to identify these complexes. Various performance assessment measures have been proposed for evaluating the efficiency of these methods. However, there are many inconsistencies in the definitions and usage of the measures across the literature. To address this issue, we have gathered and presented the most important performance evaluation measures and developed a tool, named CompEvaluator, to critically assess the protein complex prediction methods. The tool and documentation are publicly available at https://sourceforge.net/projects/compevaluator/files/.

Publication types

  • Review

MeSH terms

  • Algorithms*
  • Animals
  • Computational Biology / methods*
  • Evaluation Studies as Topic
  • Humans
  • Models, Theoretical*
  • Protein Binding
  • Protein Interaction Maps*
  • Proteins / chemistry
  • Proteins / metabolism*

Substances

  • Proteins