{"doi":"10.3389/fgene.2019.00535","title":"Inferring Interaction Networks From Multi-Omics Data","abstract":"A major goal in systems biology is a comprehensive description of the entirety of all complex interactions between different types of biomolecules-also referred to as the interactome-and how these interactions give rise to higher, cellular and organism level functions or diseases. Numerous efforts have been undertaken to define such interactomes experimentally, for example yeast-two-hybrid based protein-protein interaction networks or ChIP-seq based protein-DNA interactions for individual proteins. To complement these direct measurements, genome-scale quantitative multi-omics data (transcriptomics, proteomics, metabolomics, etc.) enable researchers to predict novel functional interactions between molecular species. Moreover, these data allow to distinguish relevant functional from non-functional interactions in specific biological contexts. However, integration of multi-omics data is not straight forward due to their heterogeneity. Numerous methods for the inference of interaction networks from homogeneous functional data exist, but with the advent of large-scale paired multi-omics data a new class of methods for inferring comprehensive networks across different molecular species began to emerge. Here we review state-of-the-art techniques for inferring the topology of interaction networks from functional multi-omics data, encompassing graphical models with multiple node types and quantitative-trait-loci (QTL) based approaches. In addition, we will discuss Bayesian aspects of network inference, which allow for leveraging already established biological information such as known protein-protein or protein-DNA interactions, to guide the inference process.","journal":"Frontiers in Genetics","year":2019,"id":6336,"datarank":3.8688658731663277,"base_score":5.0238805208462765,"endowment":5.0238805208462765,"self_citation_contribution":0.7535820781269416,"citation_network_contribution":3.115283795039386,"self_endowment_contribution":0.7535820781269416,"citer_contribution":3.115283795039386,"corpus_percentile":null,"corpus_rank":null,"citation_count":151,"citer_count":141,"citers_with_citation_signal":116,"citers_with_endowment":116,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.4418,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2019-06-12","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":42,"name":"Fabian Joachim Theis","orcid":"0000-0002-2419-1943","position":1,"is_corresponding":false},{"id":3349,"name":"Matthias Heinig","orcid":"0000-0002-5612-1720","position":2,"is_corresponding":false},{"id":54373,"name":"Johann S. Hawe","orcid":"0000-0003-3890-303X","position":0,"is_corresponding":true}],"reference_count":102,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-03-01T18:20:47.508186Z","pmid":null,"pmcid":null,"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":[]}