@article {46279,
	title = {"EviMass": A literature evidence-based miner for human microbial associations},
	journal = {Frontiers in Genetics},
	volume = {10},
	year = {2019},
	month = {SEP},
	type = {Article},
	abstract = {<p>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.</p>
},
	doi = {10.3389/fgene.2019.00849},
	author = {Srivastava, Divyanshu and Baksi, Krishanu D. and Kuntal, Bhusan K. and Mande, Sharmila S.}
}
@article {46654,
	title = {EviMass: a literature evidence-based miner for human microbial associations (vol 10, 849, 2019)},
	journal = {Frontiers in Genetics},
	volume = {11},
	year = {2020},
	month = {NOV },
	pages = {614051},
	type = {Correction},
	keywords = {Human Disease, literature mining, microbial association, Microbiome, Web server},
	doi = {10.3389/fgene.2020.614051},
	author = {Srivastava, Divyanshu and Baksi, Krishanu D. and Kuntal, Bhusan K. and Mande, Sharmila S.}
}
