{"id":"W1594736447","doi":"10.1016/s0076-6879(00)28386-9","title":"[1] High-throughput screening for protein-protein interactions using two-hybrid assay","year":2000,"lang":"en","type":"article","venue":"Methods in enzymology on CD-ROM/Methods in enzymology","topic":"Fungal and yeast genetics research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":114,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"National Center for Research Resources; National Institute of General Medical Sciences; National Institutes of Health; Howard Hughes Medical Institute","keywords":"ORFS; Computational biology; Biology; Yeast; Model organism; Open reading frame; Protein tag; Genetics; Protein–protein interaction; Gene; Recombinant DNA; Peptide sequence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001351843,0.002714174,0.003032844,0.00320881,0.001397889,0.001042724,0.002277,0.001389592,0.004877572],"category_scores_gemma":[0.001155992,0.001110686,0.002128875,0.002338508,0.0006355857,0.0008457776,0.001578576,0.002784265,0.006696628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005999405,"about_ca_system_score_gemma":0.0005098473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001014494,"about_ca_topic_score_gemma":0.002923934,"domain_scores_codex":[0.9973304,0.0008060975,0.000176252,0.0003676926,0.001089721,0.0002298499],"domain_scores_gemma":[0.9992829,0.0003201403,0.00004768973,0.0001399582,0.000142612,0.00006679972],"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":[0.0003276893,0.0002619253,0.000386209,0.0003488208,0.0001012921,0.0001567746,0.00003697483,0.0002428813,0.9865327,0.0004373587,0.002890655,0.008276798],"study_design_scores_gemma":[0.00007836305,0.0003061514,0.002277949,0.00001447931,0.0001778512,0.000484372,0.00001296675,0.002731502,0.9779926,0.0003070789,0.01555195,0.0000648495],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.211524,0.008506069,0.7244381,0.001811539,0.0009558547,0.003349139,0.01550603,0.01629437,0.01761493],"genre_scores_gemma":[0.3170419,0.009251047,0.5254701,0.001420063,0.0005903932,0.006871275,0.09493459,0.001387009,0.04303356],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004877572,"threshold_uncertainty_score":0.01631707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07942404757090137,"score_gpt":0.4582964995673425,"score_spread":0.3788724519964411,"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."}}