ArticleBMC bioinformatics2016
CompNet: a GUI based tool for comparison of multiple biological interaction networks.
Article in BMC bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 21 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed, 34 citations in OpenAlex.
- Identifying Differential Network Properties and Driver Microbes in Microbial Association Networks Using CompNet and NetShift.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Article
- The Fungal Gut Microbiome Exhibits Reduced Diversity and Increased Relative Abundance of Ascomycota in Severe COVID-19 Illness and Distinct Interconnected Communities in SARS-CoV-2 Positive Patients.Frontiers in cellular and infection microbiology · 2022Article
- NetCoMi: network construction and comparison for microbiome data in R.Briefings in bioinformatics · 2021Article
- Exploring the Microbiome Analysis and Visualization Landscape.Frontiers in bioinformatics · 2021Review
- Host population size is linked to orchid mycorrhizal fungal communities in roots and soil, which are shaped by microenvironment.Mycorrhiza · 2021Article
- Exploring the Multi-Tissue Crosstalk Relevant to Insulin Resistance Through Network-Based Analysis.Frontiers in endocrinology · 2021Article
- Differential Network Testing Reveals Diverging Dynamics of Organ System Interactions for Survivors and Non-survivors in Intensive Care Medicine.Frontiers in physiology · 2021Article
- NetConfer: a web application for comparative analysis of multiple biological networks.BMC biology · 2020Article
- Construction, comparison and evolution of networks in life sciences and other disciplines.Journal of the Royal Society, Interface · 2020Article
- Whole transcriptomic network analysis using Co-expression Differential Network Analysis (CoDiNA).PloS one · 2020Article
- Time-Varying Gene Network Analysis of Human Prefrontal Cortex Development.Frontiers in genetics · 2020Article
- Investigating host-bacterial interactions among enteric pathogens.BMC genomics · 2019Article
- Correction to: CompNet: a GUI based tool for comparison of multiple biological interaction networks.BMC bioinformatics · 2019Article
- Visual exploration of microbiome data.Journal of biosciences · 2019Review
- Meta-network: optimized species-species network analysis for microbial communities.BMC genomics · 2019Article
- 'NetShift': a methodology for understanding 'driver microbes' from healthy and disease microbiome datasets.The ISME journal · 2019Article
- Understanding the role of interactions between host and Mycobacterium tuberculosis under hypoxic condition: an in silico approach.BMC genomics · 2018Article
- Metabolite-Centric Reporter Pathway and Tripartite Network Analysis ofFrontiers in bioengineering and biotechnology · 2018Article
- Article
Corrections and comments
- Erratum issued
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNetwork visualization and analysis tools aid in better understanding of complex biological systems. Furthermore, to understand the differences in behaviour of system(s) under various environmental conditions (e.g. stress, infection), comparing multiple networks becomes necessary. Such comparisons between multiple networks may help in asserting causation and in identifying key components of the studied biological system(s). Although many available network comparison methods exist, which employ techniques like network alignment and querying to compute pair-wise similarity between selected networks, most of them have limited features with respect to interactive visual comparison of multiple networks.
resultsIn this paper, we present CompNet - a graphical user interface based network comparison tool, which allows visual comparison of multiple networks based on various network metrics. CompNet allows interactive visualization of the union, intersection and/or complement regions of a selected set of networks. Different visualization features (e.g. pie-nodes, edge-pie matrix, etc.) aid in easy identification of the key nodes/interactions and their significance across the compared networks. The tool also allows one to perform network comparisons on the basis of neighbourhood architecture of constituent nodes and community compositions, a feature particularly useful while analyzing biological networks. To demonstrate the utility of CompNet, we have compared a (time-series) human gene-expression dataset, post-infection by two strains of Mycobacterium tuberculosis, overlaid on the human protein-protein interaction network. Using various functionalities of CompNet not only allowed us to comprehend changes in interaction patterns over the course of infection, but also helped in inferring the probable fates of the host cells upon infection by the two strains.
conclusionsCompNet is expected to be a valuable visual data mining tool and is freely available for academic use from http://metagenomics.atc.tcs.com/compnet/ or http://121.241.184.233/compnet/.
Indexed as
Identifiers
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.