Abstract
BackgroundPhysical and functional interplays between genes or proteins have important biological meaning for cellular functions. Some efforts have been made to construct weighted gene association meta-networks by integrating multiple biological resources, where the weight indicates the confidence of the interaction. However, it is found that these existing human gene association networks share only quite limited overlapped interactions, suggesting their incompleteness and noise.ResultsHere we proposed a workflow to construct a weighted human gene association network using information of six existing networks, including two weighted specific PPI networks and four gene association meta-networks. We applied link prediction algorithm to predict possible missing links of the networks, cross-validation approach to refine each network and finally integrated the refined networks to get the final integrated network.ConclusionsThe common information among the refined networks increases notably, suggesting their higher reliability. Our final integrated network owns much more links than most of the original networks, meanwhile its links still keep high functional relevance. Being used as background network in a case study of disease gene prediction, the final integrated network presents good performance, implying its reliability and application significance. Our workflow could be insightful for integrating and refining existing gene association data.
Highlights
Physical and functional interplays between genes or proteins have important biological meaning for cellular functions
Based on the idea of reliable-route weighted similarity indices which measures the similarity of a pair of unconnected nodes by the product of weights of local paths connecting them, ð3Þ we proposed weighted reliable local path similarity indices as follows: (4) Reliable-route weighted Common Neighbors (CN) index: (7)Weighted reliable local path CN index: X
The network hsaPPI is constructed from the experimental biochemical cofractionation data in consistence with information from curated public databases and literatures
Summary
Physical and functional interplays between genes or proteins have important biological meaning for cellular functions. Genes and their products usually perform particular cellular task and carry out their biological functions by interacting or communicating with each other [1]. Such interactions can be expressed with molecular networks [2] with different meaning at different levels. Protein-protein interaction (PPI) networks [6, 7] represent the physical interactions These years, high-throughput biological experiments have produced huge number of data concerning interactions between genes and their products, such as gene regulatory, gene co-expression, protein complex, and PPI data, based on which we can build gene association networks. High-throughput experiments usually produce large amount of false-positive and falsenegative data [11]
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