Evidence map›Paper›PMID 20498836›Full record

ArticlePloS one2010

Reconstruction and validation of RefRec: a global model for the yeast molecular interaction network.

Tommi Aho, Henrikki Almusa, Jukka Matilainen, Antti Larjo, Pekka Ruusuvuori, Kaisa-Leena Aho, Thomas Wilhelm, Harri Lähdesmäki, Andreas Beyer, Manu Harju and 4 more

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Article in PloS one, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

14 authors.

Tommi AhoDepartment of Signal Processing, Tampere University of Technology, Tampere, Finland. tommi.aho@tut.fi
Henrikki Almusa
Jukka Matilainen
Antti Larjo
Pekka Ruusuvuori
Kaisa-Leena Aho
Thomas Wilhelm
Harri Lähdesmäki
Andreas Beyer
Manu Harju
Sharif Chowdhury
Kalle Leinonen
Christophe Roos
Olli Yli-Harja

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Molecular interaction networks establish all cell biological processes. The networks are under intensive research that is facilitated by new high-throughput measurement techniques for the detection, quantification, and characterization of molecules and their physical interactions. For the common model organism yeast Saccharomyces cerevisiae, public databases store a significant part of the accumulated information and, on the way to better understanding of the cellular processes, there is a need to integrate this information into a consistent reconstruction of the molecular interaction network. This work presents and validates RefRec, the most comprehensive molecular interaction network reconstruction currently available for yeast. The reconstruction integrates protein synthesis pathways, a metabolic network, and a protein-protein interaction network from major biological databases. The core of the reconstruction is based on a reference object approach in which genes, transcripts, and proteins are identified using their primary sequences. This enables their unambiguous identification and non-redundant integration. The obtained total number of different molecular species and their connecting interactions is approximately 67,000. In order to demonstrate the capacity of RefRec for functional predictions, it was used for simulating the gene knockout damage propagation in the molecular interaction network in approximately 590,000 experimentally validated mutant strains. Based on the simulation results, a statistical classifier was subsequently able to correctly predict the viability of most of the strains. The results also showed that the usage of different types of molecular species in the reconstruction is important for accurate phenotype prediction. In general, the findings demonstrate the benefits of global reconstructions of molecular interaction networks. With all the molecular species and their physical interactions explicitly modeled, our reconstruction is able to serve as a valuable resource in additional analyses involving objects from multiple molecular -omes. For that purpose, RefRec is freely available in the Systems Biology Markup Language format.

Indexed as

Models, GeneticSoftwareComputational BiologyGene Knockout TechniquesGene Regulatory NetworksGenes, EssentialMutationPhenotypeReproducibility of ResultsSaccharomyces cerevisiae

Identifiers

PMID20498836
PMCPMC2871048

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.