2009
DOI: 10.1371/journal.pone.0007492
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Accounting for Redundancy when Integrating Gene Interaction Databases

Abstract: During the last years gene interaction networks are increasingly being used for the assessment and interpretation of biological measurements. Knowledge of the interaction partners of an unknown protein allows scientists to understand the complex relationships between genetic products, helps to reveal unknown biological functions and pathways, and get a more detailed picture of an organism's complexity. Being able to measure all protein interactions under all relevant conditions is virtually impossible. Hence, … Show more

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Cited by 5 publications
(4 citation statements)
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“…refs. (25) and (26)] and, importantly, that the integrated interaction map present in ConsensusPathDB has not saturated yet. This underlines the importance of further interaction data integration.…”
Section: Database Content Updatementioning
confidence: 99%
“…refs. (25) and (26)] and, importantly, that the integrated interaction map present in ConsensusPathDB has not saturated yet. This underlines the importance of further interaction data integration.…”
Section: Database Content Updatementioning
confidence: 99%
“…To the best of our knowledge, methods including information on the interactions among gene sets within the single collections have not yet appeared in the literature. Moreover, database redundancy and disagreement are not limited to collections of gene sets, e.g., [18,19]. The impact of the choice of databases has been tackled for specific applications on cancer development in Mubeen et al [20].…”
Section: Related Workmentioning
confidence: 99%
“…In order to integrate prior knowledge of measured interactions we combined the Random Forests scores with experimental lines of evidence using Bayesian integration (implemented in R) as described previously (29). This approach also accounts for correlation between individual lines of evidence.…”
Section: Interaction Predictionmentioning
confidence: 99%