title: Predicting microbial interactions through computational approaches.
abstract: Microorganisms play a vital role in various ecosystems and characterizing interactions between them is an essential step towards understanding the organization and function of microbial communities. Computational prediction has recently become a widely used approach to investigate microbial interactions. We provide a thorough review of emerging computational methods organized by the type of data they employ. We highlight three major challenges in inferring interactions using metagenomic survey data and discuss the underlying assumptions and mathematics of interaction inference algorithms. In addition, we review interaction prediction methods relying on metabolic pathways, which are increasingly used to reveal mechanisms of interactions. Furthermore, we also emphasize the importance of mining the scientific literature for microbial interactions - a largely overlooked data source for experimentally validated interactions.
authors.affiliation: Genome Institute of Singapore, Singapore 138672, Singapore; Department of Computer Science, National University of Singapore, Singapore 117417, Singapore.
authors.forename: Chenhao
authors.initials: C
authors.lastname: Li
authors.affiliation: Genome Institute of Singapore, Singapore 138672, Singapore; Computational Biology program, National University of Singapore, Singapore, 117543, Singapore.
authors.forename: Kun Ming Kenneth
authors.initials: KM
authors.lastname: Lim
authors.affiliation: Genome Institute of Singapore, Singapore 138672, Singapore.
authors.forename: Kern Rei
authors.initials: KR
authors.lastname: Chng
authors.affiliation: Genome Institute of Singapore, Singapore 138672, Singapore; Department of Computer Science, National University of Singapore, Singapore 117417, Singapore. Electronic address: nagarajann@gis.a-star.edu.sg.
authors.forename: Niranjan
authors.initials: N
authors.lastname: Nagarajan
mesh_terms: D003198:Computer Simulation; D057225:Data Mining / Q000379:methods; D056186:Metagenomics / Q000379:methods*; D056265:Microbial Interactions
keywords: Metagenomics; Microbial interactions; Reverse ecology; Text mining