ArticleTheScientificWorldJournal2012
Pathway detection from protein interaction networks and gene expression data using color-coding methods and A∗ search algorithms.
Article in TheScientificWorldJournal, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Integrating protein localization with automated signaling pathway reconstruction.BMC bioinformatics · 2019Article
- Adverse Drug Reaction Predictions Using Stacking Deep Heterogeneous Information Network Embedding Approach.Molecules (Basel, Switzerland) · 2018Article
- An overview of bioinformatics methods for modeling biological pathways in yeast.Briefings in functional genomics · 2016Review
- Predicting Pharmacodynamic Drug-Drug Interactions through Signaling Propagation Interference on Protein-Protein Interaction Networks.PloS one · 2015Article
- Discovery of significant pathways in breast cancer metastasis via module extraction and comparison.IET systems biology · 2014Article
- Gene network biological validity based on gene-gene interaction relevance.TheScientificWorldJournal · 2014Article
- Identifying co-targets to fight drug resistance based on a random walk model.BMC systems biology · 2012Article
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Authors and funding
4 authors.
Funding
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Abstract
With the large availability of protein interaction networks and microarray data supported, to identify the linear paths that have biological significance in search of a potential pathway is a challenge issue. We proposed a color-coding method based on the characteristics of biological network topology and applied heuristic search to speed up color-coding method. In the experiments, we tested our methods by applying to two datasets: yeast and human prostate cancer networks and gene expression data set. The comparisons of our method with other existing methods on known yeast MAPK pathways in terms of precision and recall show that we can find maximum number of the proteins and perform comparably well. On the other hand, our method is more efficient than previous ones and detects the paths of length 10 within 40 seconds using CPU Intel 1.73 GHz and 1 GB main memory running under windows operating system.
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Registered trials
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