ArticleBioMed research international2015
mmnet: An R Package for Metagenomics Systems Biology Analysis.
Article in BioMed research international, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Article
- Bacterial Community Composition and Structure in the Littoral of Rila Mountains Glacial Lakes.Life (Basel, Switzerland) · 2025Article
- Response of the gut microbiota during the Clostridioides difficile infection in tree shrews mimics those in humans.BMC microbiology · 2020Article
- The characteristics of gut microbiota and commensal Enterobacteriaceae isolates in tree shrew (Tupaia belangeri).BMC microbiology · 2019Article
- Recent Advances in the Systems Biology of Aging.Antioxidants & redox signaling · 2018Review
- LRLSHMDA: Laplacian Regularized Least Squares for Human Microbe-Disease Association prediction.Scientific reports · 2017Article
- Human microbiome signatures of differential colorectal cancer drug metabolism.NPJ biofilms and microbiomes · 2017Article
- A novel approach for predicting microbe-disease associations by bi-random walk on the heterogeneous network.PloS one · 2017Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The human microbiome plays important roles in human health and disease. Previous microbiome studies focused mainly on single pure species function and overlooked the interactions in the complex communities on system-level. A metagenomic approach introduced recently integrates metagenomic data with community-level metabolic network modeling, but no comprehensive tool was available for such kind of approaches. To facilitate these kinds of studies, we developed an R package, mmnet, to implement community-level metabolic network reconstruction. The package also implements a set of functions for automatic analysis pipeline construction including functional annotation of metagenomic reads, abundance estimation of enzymatic genes, community-level metabolic network reconstruction, and integrated network analysis. The result can be represented in an intuitive way and sent to Cytoscape for further exploration. The package has substantial potentials in metagenomic studies that focus on identifying system-level variations of human microbiome associated with disease.
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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.