{"id":"W3029644428","doi":"10.26508/lsa.202000725","title":"STAG1 vulnerabilities for exploiting cohesin synthetic lethality in STAG2-deficient cancers","year":2020,"lang":"en","type":"article","venue":"Life Science Alliance","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Novartis Pharma; Innovative Medicines Initiative; Austrian Science Fund; Ministero dello Sviluppo Economico; Genome Canada; Fundação de Amparo à Pesquisa do Estado de São Paulo; Ontario Ministry of Economic Development and Innovation; Wellcome Trust; Österreichische Forschungsförderungsgesellschaft; European Federation of Pharmaceutical Industries and Associations; Merck KGaA; European Commission; Pfizer","keywords":"Synthetic lethality; Cohesin; Establishment of sister chromatid cohesion; Chromosome segregation; Mutant; Cell biology; Biology; Chromatid; Genetic screen; Genetics; Chromosome; Gene","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005815242,0.000132639,0.0001529914,0.00001949215,0.0001614808,0.00006685963,0.0004635048,0.00005406471,0.000008122948],"category_scores_gemma":[0.0007361919,0.0001352792,0.00005296572,0.0002361968,0.000392287,0.00001157261,0.0001235176,0.00008218261,0.00000339469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009299493,"about_ca_system_score_gemma":0.0005837593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006716441,"about_ca_topic_score_gemma":0.00009110467,"domain_scores_codex":[0.9984931,0.00002907668,0.0002633766,0.0005821597,0.0002084297,0.0004238753],"domain_scores_gemma":[0.9993286,0.00002921076,0.00009777147,0.0002811324,0.00009538684,0.0001678833],"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":[0.0001038747,0.0000599858,0.01091757,0.0002056623,0.00001135959,0.000002182463,0.001719811,0.03340918,0.9495535,0.001964807,0.0003985925,0.001653442],"study_design_scores_gemma":[0.002924439,0.001604735,0.0142521,0.0002434267,0.00003150186,0.000007958383,0.01751372,0.2800415,0.6386238,0.001855956,0.04077901,0.002121934],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934866,0.0003449208,0.003925786,0.001422796,0.000143716,0.0002978438,0.00005934124,0.00001240543,0.0003066181],"genre_scores_gemma":[0.9945841,0.00008203519,0.003635837,0.001435581,0.00009847885,0.00006437211,0.00001085328,0.00001370944,0.00007496661],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3109297,"threshold_uncertainty_score":0.5516525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02889452044939626,"score_gpt":0.2740946032781756,"score_spread":0.2452000828287794,"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."}}