{"id":"W4394959853","doi":"10.1101/2024.04.17.589858","title":"Genome-Wide CRISPR-Cas9 Screening Identifies a Synergy between Hypomethylating Agents and SUMOylation Blockade in MDS/AML","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Cancer Council NSW; National Health and Medical Research Council; Medical Research Council; National Imaging Facility; Translational Cancer Research Network; University of Toronto; Anthony Rothe Memorial Trust; Peter MacCallum Cancer Centre; University of New South Wales; Cancer Institute NSW; Analytical Center for the Government of the Russian Federation; Fred Hutchinson Cancer Research Center; Australian Cancer Research Foundation; Australian Government","keywords":"CRISPR; SUMO protein; Blockade; Computational biology; Hypomethylating agent; Azacitidine; Genome; Biology; Genetics; Gene; DNA methylation","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001705222,0.0002938008,0.0002850672,0.0002838761,0.0001032054,0.0002537426,0.0001979223,0.0002195773,0.001899428],"category_scores_gemma":[0.00007549099,0.0001085598,0.0001925206,0.0001073866,0.0001436018,0.00007163803,0.0001780085,0.000279481,0.0003381393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002546405,"about_ca_system_score_gemma":0.0001573614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007809321,"about_ca_topic_score_gemma":0.001556947,"domain_scores_codex":[0.999881,0.00001348136,0.00001523096,0.00003161948,0.00004080999,0.00001778615],"domain_scores_gemma":[0.9999588,0.000008151136,0.00001317862,0.000004745936,0.000004312455,0.00001086971],"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":[0.00008358732,0.00001939034,0.0002714992,0.00002047388,0.000006579606,0.00002731614,0.000002808078,0.0001934021,0.9974419,0.00005000818,0.00005413674,0.001828988],"study_design_scores_gemma":[0.00001209972,0.0001719898,0.00252663,0.000002574305,0.00001462487,0.0001428485,0.000007105547,0.001643093,0.9938719,0.00002121612,0.001582825,0.000003105513],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9886275,0.000870617,0.00642811,0.0001159048,0.00002358126,0.00006438951,0.001731535,0.0003126109,0.001825738],"genre_scores_gemma":[0.9909547,0.00041451,0.005075091,0.00004155061,0.00000403685,0.00002747787,0.000940552,0.0000248764,0.002517312],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001899428,"threshold_uncertainty_score":0.006354213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01879665461863034,"score_gpt":0.2520075459065229,"score_spread":0.2332108912878926,"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."}}