Published in

BioMed Central, Genome Biology, 9(8), p. R186

DOI: 10.1186/gb-2007-8-9-r186

Links

Tools

Export citation

Search in Google Scholar

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

Journal article published in 2007 by Tony Chiang, Denise Scholtens, Deepayan Sarkar ORCID, Robert Gentleman, Wolfgang Huber ORCID
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Green circle
Preprint: archiving allowed
Upload
Green circle
Postprint: archiving allowed
Upload
Green circle
Published version: archiving allowed
Upload
Policy details
Data provided by SHERPA/RoMEO

Abstract

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.