ArticleBioinformatics (Oxford, England)2014
NetComm: a network analysis tool based on communicability.
Article in Bioinformatics (Oxford, England), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Network bypasses sustain complexity.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Exome sequencing efficacy and phenotypic expansions involving esophageal atresia/tracheoesophageal fistula plus.American journal of medical genetics. Part A · 2022Article
- AI-Based Computational Methods in Early Drug Discovery and Post Market Drug Assessment: A Survey.IEEE transactions on computational biology and bioinformaticsReview
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
motivationSet-based network similarity metrics are increasingly used to productively analyze genome-wide data. Conventional approaches, such as mean shortest path and clique-based metrics, have been useful but are not well suited to all applications. Computational scientists in other disciplines have developed communicability as a complementary metric. Network communicability considers all paths of all lengths between two network members. Given the success of previous network analyses of protein-protein interactions, we applied the concepts of network communicability to this problem. Here we show that our communicability implementation has advantages over traditional approaches. Overall, analyses suggest network communicability has considerable utility in analysis of large-scale biological networks. AVAILABILITY AND IMPLEMENTATION: We provide our method as an R package for use in both human protein-protein interaction network analyses and analyses of arbitrary networks along with a tutorial at http://www.shawlab.org/NetComm/.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.