ArticleFrontiers in microbiology2018
FLIM-MAP: Gene Context Based Identification of Functional Modules in Bacterial Metabolic Pathways.
Article in Frontiers in microbiology, 2018. 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 7 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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Who cites it
7 citing papers in PubMed.
- The aminotransferase Aat initiates 3-phenyllactic acid biosynthesis inFrontiers in microbiology · 2023Article
- A systems level approach to study metabolic networks in prokaryotes with the aromatic amino acid biosynthesis pathway.Frontiers in genetics · 2022Article
- Specific inhibition of Streptococcus bovis by endolysin LyJH307 supplementation shifts the rumen microbiota and metabolic pathways related to carbohydrate metabolism.Journal of animal science and biotechnology · 2021Article
- NetConfer: a web application for comparative analysis of multiple biological networks.BMC biology · 2020Article
- Visual exploration of microbiome data.Journal of biosciences · 2019Review
- Web-gLV: A Web Based Platform for Lotka-Volterra Based Modeling and Simulation of Microbial Populations.Frontiers in microbiology · 2019Article
- iVikodak-A Platform and Standard Workflow for Inferring, Analyzing, Comparing, and Visualizing the Functional Potential of Microbial Communities.Frontiers in microbiology · 2018Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Prediction of functional potential of bacteria can only be ascertained by the accurate annotation of its metabolic pathways. Homology based methods decipher metabolic gene content but ignore the fact that homologs of same protein can function in different pathways. Therefore, mere presence of all constituent genes in an organism is not sufficient to indicate a pathway. Contextual occurrence of genes belonging to a pathway on the bacterial genome can hence be exploited for an accurate estimation of functional potential of a bacterium. In this communication, we present a novel annotation resource to accurately identify pathway presence by using gene context. Our tool FLIM-MAP (Functionally Important Modules in bacterial Metabolic Pathways) predicts biologically relevant functional units called 'GCMs' (Gene Context based Modules) from a given metabolic reaction network. We benchmark the accuracy of our tool on amino acids and carbohydrate metabolism pathways.
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Registered trials
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