“EviMass”: A Literature Evidence-Based Miner for Human Microbial Associations

• Main Authors: Divyanshu Srivastava, Krishanu D. Baksi, Bhusan K. Kuntal, Sharmila S. Mande
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2019-09-01
• Series: Frontiers in Genetics
• Subjects: microbiome; literature mining; human disease; web server; microbial association
• Online Access: https://www.frontiersin.org/article/10.3389/fgene.2019.00849/full

The importance of understanding microbe–microbe as well as microbe–disease associations is one of the key thrust areas in human microbiome research. High-throughput metagenomic and transcriptomic projects have fueled discovery of a number of new microbial associations. Consequently, a plethora of information is being added routinely to biomedical literature, thereby contributing toward enhancing our knowledge on microbial associations. In this communication, we present a tool called “EviMass” (Evidence based mining of human Microbial Associations), which can assist biologists to validate their predicted hypotheses from new microbiome studies. Users can interactively query the processed back-end database for microbe–microbe and disease–microbe associations. The EviMass tool can also be used to upload microbial association networks generated from a human “disease–control” microbiome study and validate the associations from biomedical literature. Additionally, a list of differentially abundant microbes for the corresponding disease can be queried in the tool for reported evidences. The results are presented as graphical plots, tabulated summary, and other evidence statistics. EviMass is a comprehensive platform and is expected to enable microbiome researchers not only in mining microbial associations, but also enriching a new research hypothesis. The tool is available free for academic use at https://web.rniapps.net/evimass.