{"doi":"10.1093/bioinformatics/bti492","title":"Inferring protein–protein interactions through high-throughput interaction data from diverse organisms","abstract":"<jats:title>Abstract</jats:title><jats:p>Motivation: Identifying protein–protein interactions is critical for understanding cellular processes. Because protein domains represent binding modules and are responsible for the interactions between proteins, computational approaches have been proposed to predict protein interactions at the domain level. The fact that protein domains are likely evolutionarily conserved allows us to pool information from data across multiple organisms for the inference of domain–domain and protein–protein interaction probabilities.</jats:p><jats:p>Results: We use a likelihood approach to estimating domain–domain interaction probabilities by integrating large-scale protein interaction data from three organisms, Saccharomyces cerevisiae, Caenorhabditis elegans and Drosophila melanogaster. The estimated domain–domain interaction probabilities are then used to predict protein–protein interactions in S.cerevisiae. Based on a thorough comparison of sensitivity and specificity, Gene Ontology term enrichment and gene expression profiles, we have demonstrated that it may be far more informative to predict protein–protein interactions from diverse organisms than from a single organism.</jats:p><jats:p>Availability: The program for computing the protein–protein interaction probabilities and supplementary material are available at http://bioinformatics.med.yale.edu/interaction</jats:p><jats:p>Contact:  hongyu.zhao@yale.edu</jats:p>","journal":"Bioinformatics","year":2005,"id":655873,"datarank":0.6814942173405006,"base_score":4.543294782270004,"endowment":4.543294782270004,"self_citation_contribution":0.6814942173405006,"citation_network_contribution":0.0,"self_endowment_contribution":0.6814942173405006,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":93,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":373623,"name":"Nianjun Liu","orcid":"0000-0002-2565-8154","position":1,"is_corresponding":false},{"id":921659,"name":"Hongyu Zhao","orcid":"0000-0001-6398-0876","position":2,"is_corresponding":false},{"id":381057,"name":"Yin Liu","orcid":"0000-0001-6349-056X","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Inferring protein–protein interactions through high-throughput interaction data from diverse organisms","abstract":"<jats:title>Abstract</jats:title><jats:p>Motivation: Identifying protein–protein interactions is critical for understanding cellular processes. Because protein domains represent binding modules and are responsible for the interactions between proteins, computational approaches have been proposed to predict protein interactions at the domain level. The fact that protein domains are likely evolutionarily conserved allows us to pool information from data across multiple organisms for the inference of domain–domain and protein–protein interaction probabilities.</jats:p><jats:p>Results: We use a likelihood approach to estimating domain–domain interaction probabilities by integrating large-scale protein interaction data from three organisms, Saccharomyces cerevisiae, Caenorhabditis elegans and Drosophila melanogaster. The estimated domain–domain interaction probabilities are then used to predict protein–protein interactions in S.cerevisiae. Based on a thorough comparison of sensitivity and specificity, Gene Ontology term enrichment and gene expression profiles, we have demonstrated that it may be far more informative to predict protein–protein interactions from diverse organisms than from a single organism.</jats:p><jats:p>Availability: The program for computing the protein–protein interaction probabilities and supplementary material are available at http://bioinformatics.med.yale.edu/interaction</jats:p><jats:p>Contact:  hongyu.zhao@yale.edu</jats:p>","is_dataset_classified":null,"base_score":4.543294782270004,"endowment":4.543294782270004,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"15905281","pmcid":null,"openalex_id":"https://openalex.org/W2095910716","authors":[],"funders":[],"total_grants":0,"fwci":5.149,"citation_percentile":0.96297779,"influential_citations":0,"citation_trend":[{"year":2012,"count":6},{"year":2013,"count":2},{"year":2014,"count":2},{"year":2015,"count":1},{"year":2016,"count":4},{"year":2017,"count":2},{"year":2018,"count":3},{"year":2024,"count":1}],"oa_status":"bronze","license":null,"oa_locations":[{"url":"https://academic.oup.com/bioinformatics/article-pdf/21/15/3279/50340670/bioinformatics_21_15_3279.pdf","host_type":"journal"},{"url":"https://academic.oup.com/bioinformatics/article-pdf/21/15/3279/50340670/bioinformatics_21_15_3279.pdf","host_type":"publisher"},{"url":"https://doi.org/10.1093/bioinformatics/bti492","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/15905281","host_type":"repository"},{"url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.105.7463","host_type":""}],"fields_of_study":["Bioinformatics and Genomic Networks","Biomedical Text Mining and Ontologies","Protein Structure and Dynamics","Binding Sites","Biodiversity","Caenorhabditis elegans Proteins","Computer Simulation","Drosophila Proteins","Models, Biological","Models, Chemical","Protein Binding","Protein Interaction Mapping","Saccharomyces cerevisiae Proteins","Sequence Analysis, Protein","Signal Transduction","Species Specificity"],"mesh_terms":["Binding Sites","Computer Simulation","Models, Biological","Models, Chemical","Protein Binding","Species Specificity","Signal Transduction","Sequence Analysis, Protein","Protein Interaction Mapping","Saccharomyces cerevisiae Proteins","Drosophila Proteins","Caenorhabditis elegans Proteins","Biodiversity"],"keywords":["Protein–protein interaction","Domain (mathematical analysis)","Drosophila melanogaster","Caenorhabditis elegans","Protein domain","Model organism","Computational biology","Saccharomyces cerevisiae","Inference","Biology","Organism","Computer science","Gene","Genetics","Artificial intelligence","Mathematics"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-11T19:12:00.298505Z","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":[]}