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Understanding the functional interaction between multi-omic biomarkers is becoming increasingly important due to its great potential for providing insights of the underlying molecular mechanism.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Leveraging multiple biological network databases, we integrated the relationship between single nucleotide polymorphisms (SNPs), genes\/proteins and metabolites, and developed an R package Multi-omic Network Explorer Tool (MoNET) for multi-omic network analysis. This new tool enables users to not only track down the interaction of SNPs\/genes with metabolome level, but also trace back for the potential risk variants\/regulators given altered genes\/metabolites. MoNET is expected to advance our understanding of the multi-omic findings by unveiling their transomic interactions and is likely to generate new hypotheses for further validation.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>The MoNET package is freely available on https:\/\/github.com\/JW-Yan\/MONET.<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btab722","type":"journal-article","created":{"date-parts":[[2021,10,20]],"date-time":"2021-10-20T01:37:33Z","timestamp":1634693853000},"page":"1165-1167","source":"Crossref","is-referenced-by-count":4,"title":["MoNET: an R package for multi-omic network analysis"],"prefix":"10.1093","volume":"38","author":[{"given":"Jin","family":"Li","sequence":"first","affiliation":[{"name":"College of Intelligent Systems Science and Engineering, Harbin Engineering University , Harbin 150001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Feng","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Intelligent Systems Science and Engineering, Harbin Engineering University , Harbin 150001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hong","family":"Liang","sequence":"additional","affiliation":[{"name":"College of Intelligent Systems Science and Engineering, Harbin Engineering University , Harbin 150001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9066-4908","authenticated-orcid":false,"given":"Jingwen","family":"Yan","sequence":"additional","affiliation":[{"name":"Department of BioHealth Informatics, School of Informatics and Computing, Indiana University\u2013Purdue University Indianapolis , Indianapolis, IN 46202, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2021,10,25]]},"reference":[{"key":"2023033101030324000_","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1186\/s12859-016-1043-4","article-title":"Integration of multi-omics data for prediction of phenotypic traits using random forest","volume":"17","author":"Acharjee","year":"2016","journal-title":"BMC Bioinformatics"},{"key":"2023033101030324000_","doi-asserted-by":"crossref","first-page":"104219","DOI":"10.1016\/j.cellimm.2020.104219","article-title":"Genomic, proteomic, and systems biology approaches in biomarker discovery for multiple sclerosis","volume":"358","author":"Chase Huizar","year":"2020","journal-title":"Cell. 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