ArticleNature communications2013
Counting motifs in the human interactome.
Article in Nature communications, 2013. 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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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.
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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
12 citing papers in PubMed.
- Generating random graphs with prescribed graphlet frequency bounds derived from probabilistic networks.PloS one · 2025Article
- Proper network randomization is key to assessing social balance.Science advances · 2024Article
- The duplication of genomes and genetic networks and its potential for evolutionary adaptation and survival during environmental turmoil.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Structural measures of similarity and complementarity in complex networks.Scientific reports · 2022Article
- Characterizing building blocks of resource constrained biological networks.BMC bioinformatics · 2019Article
- Topological motifs populate complex networks through grouped attachment.Scientific reports · 2018Article
- ProMotE: an efficient algorithm for counting independent motifs in uncertain network topologies.BMC bioinformatics · 2018Article
- Understanding the Mechanisms Behind the Response to Environmental Perturbation in Microbial Mats: A Metagenomic-Network Based Approach.Frontiers in microbiology · 2018Article
- LncFunNet: an integrated computational framework for identification of functional long noncoding RNAs in mouse skeletal muscle cells.Nucleic acids research · 2017Article
- Functional networks inference from rule-based machine learning models.BioData mining · 2016Article
- Bridging topological and functional information in protein interaction networks by short loops profiling.Scientific reports · 2015Article
- Triadic motifs in the dependence networks of virtual societies.Scientific reports · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Small over-represented motifs in biological networks often form essential functional units of biological processes. A natural question is to gauge whether a motif occurs abundantly or rarely in a biological network. Here we develop an accurate method to estimate the occurrences of a motif in the entire network from noisy and incomplete data, and apply it to eukaryotic interactomes and cell-specific transcription factor regulatory networks. The number of triangles in the human interactome is about 194 times that in the Saccharomyces cerevisiae interactome. A strong positive linear correlation exists between the numbers of occurrences of triad and quadriad motifs in human cell-specific transcription factor regulatory networks. Our findings show that the proposed method is general and powerful for counting motifs and can be applied to any network regardless of its topological structure.
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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.