Coverage and error models of protein-protein interaction data by directed graph analysis

Genome Biol. 2007;8(9):R186. doi: 10.1186/gb-2007-8-9-r186.

Abstract

Using a directed graph model for bait to prey systems and a multinomial error model, we assessed the error statistics in all published large-scale datasets for Saccharomyces cerevisiae and characterized them by three traits: the set of tested interactions, artifacts that lead to false-positive or false-negative observations, and estimates of the stochastic error rates that affect the data. These traits provide a prerequisite for the estimation of the protein interactome and its modules.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Computational Biology / methods*
  • Computer Graphics
  • Databases, Protein
  • Fungal Proteins
  • Gene Expression Regulation, Fungal
  • Genomics / methods
  • Models, Biological
  • Protein Interaction Mapping*
  • Proteome
  • Proteomics / methods
  • Regression Analysis
  • Reproducibility of Results
  • Saccharomyces cerevisiae / genetics
  • Stochastic Processes

Substances

  • Fungal Proteins
  • Proteome