ArticleBMC genomics2007
Investigation of factors affecting prediction of protein-protein interaction networks by phylogenetic profiling.
Article in BMC genomics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Towards a Dynamic Interaction Network of Life to unify and expand the evolutionary theory.BMC biology · 2018Review
- Co-Inheritance Analysis within the Domains of Life Substantially Improves Network Inference by Phylogenetic Profiling.PloS one · 2015Article
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- Article
- A systematic study of genome context methods: calibration, normalization and combination.BMC bioinformatics · 2010Article
- Comparing transcription rate and mRNA abundance as parameters for biochemical pathway and network analysis.PloS one · 2010Article
- Detecting Coevolution of Functionally Related Proteins for Automated Protein Annotation.Proceedings. IEEE International Symposium on Bioinformatics and Bioengineering · 2010Article
- Stratification of co-evolving genomic groups using ranked phylogenetic profiles.BMC bioinformatics · 2009Article
- Biomedical discovery acceleration, with applications to craniofacial development.PLoS computational biology · 2009Article
- Prediction of evolutionarily conserved interologs in Mus musculus.BMC genomics · 2008Article
- Predicting protein linkages in bacteria: which method is best depends on task.BMC bioinformatics · 2008Article
- The topology of the bacterial co-conserved protein network and its implications for predicting protein function.BMC genomics · 2008Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
backgroundThe use of computational methods for predicting protein interaction networks will continue to grow with the number of fully sequenced genomes available. The Co-Conservation method, also known as the Phylogenetic profiles method, is a well-established computational tool for predicting functional relationships between proteins.
resultsHere, we examined how various aspects of this method affect the accuracy and topology of protein interaction networks. We have shown that the choice of reference genome influences the number of predictions involving proteins of previously unknown function, the accuracy of predicted interactions, and the topology of predicted interaction networks. We show that while such results are relatively insensitive to the E-value threshold used in defining homologs, predicted interactions are influenced by the similarity metric that is employed. We show that differences in predicted protein interactions are biologically meaningful, where judicious selection of reference genomes, or use of a new scoring scheme that explicitly considers reference genome relatedness, produces known protein interactions as well as predicted protein interactions involving coordinated biological processes that are not accessible using currently available databases.
conclusionThese studies should prove valuable for future studies seeking to further improve phylogenetic profiling methodologies as well for efforts to efficiently employ such methods to develop new biological insights.
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