ArticleBioinformatics (Oxford, England)2012
A single source k-shortest paths algorithm to infer regulatory pathways in a gene network.
Article in Bioinformatics (Oxford, England), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed.
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- Machine Learning-Assisted Network Inference Approach to Identify a New Class of Genes that Coordinate the Functionality of Cancer Networks.Scientific reports · 2017Article
- Reconstruction and signal propagation analysis of the Syk signaling network in breast cancer cells.PLoS computational biology · 2017Article
- The PathLinker app: Connect the dots in protein interaction networks.F1000Research · 2017Article
- A physarum-inspired prize-collecting steiner tree approach to identify subnetworks for drug repositioning.BMC systems biology · 2016Article
- Protein-fold recognition using an improved single-source K diverse shortest paths algorithm.Proteins · 2016Article
- Providing data science support for systems pharmacology and its implications to drug discovery.Expert opinion on drug discovery · 2016Review
- A new method to improve network topological similarity search: applied to fold recognition.Bioinformatics (Oxford, England) · 2015Article
- Integrating phosphoproteome and transcriptome reveals new determinants of macrophage multinucleation.Molecular & cellular proteomics : MCP · 2015Article
- Predicting functional and regulatory divergence of a drug resistance transporter gene in the human malaria parasite.BMC genomics · 2015Article
- Functional association networks as priors for gene regulatory network inference.Bioinformatics (Oxford, England) · 2014Article
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- Chapter 5: Network biology approach to complex diseases.PLoS computational biology · 2012Article
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2 authors.
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Abstract
motivationInferring the underlying regulatory pathways within a gene interaction network is a fundamental problem in Systems Biology to help understand the complex interactions and the regulation and flow of information within a system-of-interest. Given a weighted gene network and a gene in this network, the goal of an inference algorithm is to identify the potential regulatory pathways passing through this gene.
resultsIn a departure from previous approaches that largely rely on the random walk model, we propose a novel single-source k-shortest paths based algorithm to address this inference problem. An important element of our approach is to explicitly account for and enhance the diversity of paths discovered by our algorithm. The intuition here is that diversity in paths can help enrich different functions and thereby better position one to understand the underlying system-of-interest. Results on the yeast gene network demonstrate the utility of the proposed approach over extant state-of-the-art inference algorithms. Beyond utility, our algorithm achieves a significant speedup over these baselines. AVAILABILITY: All data and codes are freely available upon request.
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