{"doi":"10.1016/j.xpro.2024.103457","title":"Protocol for using Multiomics2Targets to identify targets and driver kinases for cancer cohorts profiled with multi-omics assays","abstract":"The availability of multi-omics data applied to profile cancer cohorts is rapidly increasing. Here, we present a protocol for Multiomics2Targets, a computational pipeline that can identify driver cell signaling pathways, protein kinases, and cell-surface targets for immunotherapy. We describe steps for preparing the data, uploading files, and tuning parameters. We then detail procedures for running the workflow, visualizing the results, and exporting and sharing reports containing the analysis. For complete details on the use and execution of this protocol, please refer to Deng et al. 1 • A comprehensive workflow to analyze data from cancer patient cohorts • Workflow to analyze transcriptomics, proteomics, and phosphoproteomics • Results are produced in a research-paper-like report that can be shared Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics. The availability of multi-omics data applied to profile cancer cohorts is rapidly increasing. Here, we present a protocol for Multiomics2Targets, a computational pipeline that can identify driver cell signaling pathways, protein kinases, and cell-surface targets for immunotherapy. We describe steps for preparing the data, uploading files, and tuning parameters. We then detail procedures for running the workflow, visualizing the results, and exporting and sharing reports containing the analysis.","journal":"STAR Protocols","year":2024,"id":506378,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.8366,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":951391,"name":"Eden Z. Deng","orcid":"0000-0002-8717-4606","position":1,"is_corresponding":false},{"id":2540,"name":"Daniel J. B. Clarke","orcid":"0000-0003-3471-7416","position":2,"is_corresponding":false},{"id":1201757,"name":"Ido Diamant","orcid":null,"position":3,"is_corresponding":false},{"id":32696,"name":"Adam C. Resnick","orcid":"0000-0003-0436-4189","position":4,"is_corresponding":false},{"id":108218,"name":"Weiping Ma","orcid":"0000-0003-3786-7460","position":5,"is_corresponding":false},{"id":108227,"name":"Pei Wang","orcid":"0000-0002-6890-6453","position":6,"is_corresponding":false},{"id":60353,"name":"Avi Ma’ayan","orcid":"0000-0002-6904-1017","position":7,"is_corresponding":false},{"id":997119,"name":"Giacomo B. Marino","orcid":"0009-0005-9727-559X","position":0,"is_corresponding":true}],"reference_count":30,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T02:10:54.646711Z","pmid":"39565691","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":[]}