{"id":"W7117358448","doi":"10.1016/j.xpro.2025.104303","title":"Protocol for dissecting the aggregation-prone protein interactome with optogenetic-induced aggregation and biotin labeling proximity assay","year":2025,"lang":"en","type":"article","venue":"STAR Protocols","topic":"Biotin and Related Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"PROTEO; Université du Québec à Montréal; Université Laval","funders":"Science and Engineering Research Council; Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec; Canadian Institutes of Health Research; Parkinson Society Canada; Institute of Neurosciences, Mental Health and Addiction; Université Laval","keywords":"Biotinylation; Interactome; Biotin; Protein–protein interaction; Proteomics; Protein methods; Plasma protein binding; Protocol (science); Immunoprecipitation","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001181108,0.001501766,0.001177534,0.001515974,0.001523488,0.0007994435,0.001275984,0.001036447,0.01475596],"category_scores_gemma":[0.0009237745,0.001161098,0.001028032,0.001091951,0.0006694095,0.0005603419,0.001191935,0.002986091,0.01473567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007023136,"about_ca_system_score_gemma":0.001177053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009534581,"about_ca_topic_score_gemma":0.002239341,"domain_scores_codex":[0.9984422,0.0002356854,0.0001959966,0.0004003634,0.0004930916,0.0002325682],"domain_scores_gemma":[0.9993035,0.0001752347,0.00007096718,0.0001963035,0.0001705271,0.00008354207],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002128261,0.0001162729,0.0002545265,0.0005645076,0.00003906641,0.0003494553,0.0001715676,0.0004168372,0.9762095,0.00262925,0.007546493,0.01148961],"study_design_scores_gemma":[0.0001364915,0.0003456202,0.002046765,0.000153234,0.00008167959,0.0009671294,0.00007806255,0.003552506,0.7538282,0.001664324,0.2370254,0.0001205334],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"protocol","genre_scores_codex":[0.04198452,0.004010395,0.8957444,0.0008917689,0.001081045,0.01050275,0.01580574,0.01006214,0.0199172],"genre_scores_gemma":[0.08113462,0.006573805,0.7837138,0.001268401,0.0001935521,0.05135969,0.04263428,0.001856307,0.03126559],"genre_candidate":"protocol","genre_consensus":null,"teacher_disagreement_score":0.01475596,"threshold_uncertainty_score":0.04936361,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02454981152629732,"score_gpt":0.3421638062252526,"score_spread":0.3176139946989552,"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."}}