{"doi":"10.1109/msp.2008.930647","title":"Reverse engineering gene regulatory networks","abstract":null,"journal":"IEEE Signal Processing Magazine","year":2009,"id":636531,"datarank":0.637274286307404,"base_score":4.248495242049359,"endowment":4.248495242049359,"self_citation_contribution":0.637274286307404,"citation_network_contribution":0.0,"self_endowment_contribution":0.637274286307404,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":69,"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":1652095,"name":"I. Tienda-Luna","orcid":null,"position":1,"is_corresponding":false},{"id":815126,"name":"Yufeng Wang","orcid":"0000-0002-9959-4149","position":2,"is_corresponding":false},{"id":238479,"name":"Yufei Huang","orcid":"0000-0001-6268-5357","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Reverse engineering gene regulatory networks","abstract":"Statistical models for reverse engineering gene regulatory networks are surveyed in this article. To provide readers with a system-level view of the modeling issues in this research, a graphical modeling framework is proposed. This framework serves as the scaffolding on which the review of different models can be systematically assembled. Based on the framework, we review many existing models for many aspects of gene regulation; the pros and cons of each model are discussed. In addition, network inference algorithms are also surveyed under the graphical modeling framework by the categories of point solutions and probabilistic solutions and the connections and differences among the algorithms are provided. This survey has the potential to elucidate the development and future of reverse engineering GRNs and bring statistical signal processing closer to the core of this research.","is_dataset_classified":null,"base_score":4.248495242049359,"endowment":4.248495242049359,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"20046885","pmcid":"PMC2763329","openalex_id":"https://openalex.org/W2153244486","authors":[],"funders":[{"funder_name":"NIAID NIH HHS","grant_id":"R21 AI067543","title":null},{"funder_name":"NCRR NIH HHS","grant_id":"G12 RR013646","title":null},{"funder_name":"NIAID NIH HHS","grant_id":"SC1 AI080579","title":null},{"funder_name":"NIGMS NIH HHS","grant_id":"SC1 GM081068","title":null}],"total_grants":4,"fwci":3.2755,"citation_percentile":0.9287205,"influential_citations":0,"citation_trend":[{"year":2012,"count":15},{"year":2013,"count":13},{"year":2014,"count":5},{"year":2015,"count":2},{"year":2016,"count":3},{"year":2017,"count":4},{"year":2018,"count":2},{"year":2019,"count":2},{"year":2021,"count":2},{"year":2022,"count":3},{"year":2023,"count":2},{"year":2024,"count":1},{"year":2025,"count":1},{"year":2026,"count":3}],"oa_status":"green","license":"https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html","oa_locations":[{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/2763329","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/2763329","host_type":"repository"},{"url":"http://xplorestaging.ieee.org/ielx5/79/4775864/04775882.pdf?arnumber=4775882","host_type":"publisher"},{"url":"https://doi.org/10.1109/msp.2008.930647","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/20046885","host_type":"repository"}],"fields_of_study":["Gene Regulatory Network Analysis","Viral Infectious Diseases and Gene Expression in Insects","Gene expression and cancer classification"],"mesh_terms":[],"keywords":["Graphical model","Reverse engineering","Computer science","Gene regulatory network","Inference","Statistical model","Probabilistic logic","Data science","Statistical inference","Data mining","Machine learning","Theoretical computer science","Artificial intelligence","Gene"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Partnerships for the goals"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-06T17:14:49.976884Z","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":[]}