{"doi":"10.1093/bioinformatics/btab722","title":"MoNET: an R package for multi-omic network analysis","abstract":"MOTIVATION: The increasing availability of multi-omic data has enabled the discovery of disease biomarkers in different scales. 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. RESULTS: 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. AVAILABILITY AND IMPLEMENTATION: The MoNET package is freely available on https://github.com/JW-Yan/MONET. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.","journal":"Bioinformatics","year":2021,"id":207016,"datarank":0.39339432432519444,"base_score":1.791759469228055,"endowment":1.791759469228055,"self_citation_contribution":0.26876392038420827,"citation_network_contribution":0.12463040394098618,"self_endowment_contribution":0.26876392038420827,"citer_contribution":0.12463040394098618,"corpus_percentile":53.631933163146904,"corpus_rank":5995,"citation_count":5,"citer_count":5,"citers_with_citation_signal":5,"citers_with_endowment":5,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.7832,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":415257,"name":"Feng Chen","orcid":"0000-0002-9054-943X","position":1,"is_corresponding":false},{"id":381450,"name":"Hong Liang","orcid":"0000-0002-2590-7210","position":2,"is_corresponding":false},{"id":53154,"name":"Jingwen Yan","orcid":"0000-0001-9066-4908","position":3,"is_corresponding":false},{"id":291561,"name":"Jin Li","orcid":"0000-0001-7024-3591","position":0,"is_corresponding":true}],"reference_count":23,"raw_metadata":null,"created_at":"2026-07-18T23:51:45.688025Z","pmid":"34694378","pmcid":"PMC10060724","fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}