Reverse ecology analysis software tools | Population genetics data analysis
Reverse ecology has been developed to study the complex interactions and species composition of microbial communities. Reverse ecology uses genomics to study community ecology with no a priori assumptions about the organisms under consideration. Researchers can use it to infer the ecology of a system directly from genomic information. The reverse ecology framework uses advances in systems biology and genomic metabolic modeling and the system-level analysis of complex biological networks to predict the ecological traits of poorly studied microorganisms, their interactions with other microorganisms, and the ecology of microbial communities. Several studies have applied this approach to investigate the interactions between microorganisms and their surroundings on a large scale.
A web tool for analyzing the topology of metabolic networks and calculating the set of exogenously acquired compounds. NetSeed is based on the seed detection algorithm, that allows for the quantification of an organism's metabolic dependence on its environment and enables the transformation of high-throughput genomic data into large-scale ecological data.
A package for determining host-microbe and microbe-microbe cooperative potential. NetCooperate specifically calculates two previously developed and validated metrics for species interaction: the Biosynthetic Support Score and Metabolic Complementarity Index, which provide insight into host-microbe and microbe-microbe metabolic interactions. NetCooperate determines these interaction indices from metabolic network topology, and can be used for small- or large-scale analyses.
An R package and a Shiny Web application that implements the reverse ecology algorithm for determining microbe–microbe interactions in microbial communities. RevEcoR allows users to obtain large-scale ecological insights into species’ ecology directly from high-throughput metagenomic data. The software has great potential for facilitating the study of microbiomes.
A tool for calculating the competitive potential between pairs of bacterial species. The score describes the effective metabolic overlap (EMO) between two species, derived from analyzing the topology of the corresponding metabolic models. NetCmpt is based on the EMO algorithm, developed and validated in previous studies. It takes as input lists of species-specific enzymatic reactions (EC numbers) and generates a matrix of the potential competition scores between all pairwise combinations.
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