Affiliation:
1. Center for Computational Biology, College of Biological Sciences and Technology Beijing Forestry University Beijing China
2. Beijing Yanqi Lake Institute of Mathematical Sciences and Applications Beijing China
3. Yau Mathematical Sciences Center Tsinghua University Beijing China
Abstract
Abstract
Network models have been used as a tool to characterize internal workings of complex systems. The amount of topological and functional information extracted from a network depend on the method of network inference and the type of network data.
An interdisciplinary computational model has been proposed to reconstruct informative, dynamic, omnidirectional and personalized networks (idopNetwork) from any data domains including static data.
We implement idopNetwork as an R‐based cartographic tool to characterize spatially varying interspecies interaction networks using the abundance data of multiple species from different geographical locations. This tool provides a unified framework for integrating power curve fitting based on allometrical scaling law, functional clustering, LASSO‐based variable selection, quasi‐dynamic ordinary differential equation solving, species abundance decomposition and network visualization. It coalesces all species from different spaces into location‐specific networks.
We demonstrate the utility of this tool by analysing different organs that are spatially interconnected via microbiomes within the host using two datasets from the gut microbiota and plant microbiota. Given that biodiversity and organization vary biogeographically at different scales, idopNetwork will find its widespread application to modelling and estimating interspecific interactions with differing functions across space.
Funder
Beijing Forestry University
Subject
Ecological Modeling,Ecology, Evolution, Behavior and Systematics