{"id":"W4320857030","doi":"10.1007/7651_2022_465","title":"Inferring Gene Regulatory Networks and Predicting the Effect of Gene Perturbations via IQCELL","year":2023,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; University of British Columbia","funders":"","keywords":"Gene regulatory network; Computational biology; Gene; Boolean network; Computer science; Data mining; Biology; Boolean function; Theoretical computer science; Genetics; Gene expression; Algorithm","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002452012,0.0002191074,0.0003489066,0.0001599711,0.0001010692,0.000009219862,0.0002662881,0.0003151807,0.000004431964],"category_scores_gemma":[0.0003356274,0.0001704509,0.0001593742,0.0005322938,0.0002537965,0.000002210573,0.0002935443,0.0001771539,9.230022e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001477214,"about_ca_system_score_gemma":0.00002257406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002121651,"about_ca_topic_score_gemma":0.00001140006,"domain_scores_codex":[0.9969187,0.001765959,0.0003872324,0.0004787633,0.00008151551,0.0003678456],"domain_scores_gemma":[0.9988719,0.0002431879,0.0001557152,0.0006225618,0.00004563548,0.00006096594],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002037141,0.000005578424,0.03995802,0.00001079649,0.0001138272,0.000003680969,0.00002949217,0.03005297,0.9166481,0.00003297248,0.00002157328,0.01310258],"study_design_scores_gemma":[0.0004116237,0.0002568948,0.01763321,0.00001146075,0.0001036494,0.00002270262,0.00001734484,0.05166444,0.9289275,0.0002649539,0.0004894469,0.0001967246],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5774139,0.003006823,0.4191878,0.00004324274,0.0001095933,0.000174899,0.000002348474,0.00001605779,0.00004532416],"genre_scores_gemma":[0.9313262,0.0002910253,0.06781069,0.00008811893,0.0001710091,0.00007620698,0.000116662,0.00004213968,0.00007795003],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3539124,"threshold_uncertainty_score":0.6950787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009112959948269148,"score_gpt":0.3147128918060493,"score_spread":0.3055999318577801,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}