{"id":"W2732785974","doi":"10.1101/156679","title":"GrapHi-C: Graph-based visualization of Hi-C Datasets","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Visualization; Genome; Graph drawing; Computer science; Graph; Computational biology; Genomics; ENCODE; Theoretical computer science; Biology; Data mining; Genetics; Gene","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":[0.002370593,0.002079003,0.001422316,0.006018536,0.0009122716,0.002908243,0.002270248,0.001144766,0.0342498],"category_scores_gemma":[0.009201911,0.0006280829,0.001416306,0.004984944,0.0004665377,0.001822708,0.002258133,0.002718776,0.004901522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009313404,"about_ca_system_score_gemma":0.001774983,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006512456,"about_ca_topic_score_gemma":0.007063799,"domain_scores_codex":[0.9989787,0.0002996946,0.0001146257,0.0002309147,0.0002908601,0.00008519767],"domain_scores_gemma":[0.9943069,0.003450374,0.0004431665,0.0006177209,0.0008975846,0.0002842032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002525516,0.0006055172,0.01062689,0.01299133,0.001339925,0.001198418,0.003088569,0.04029383,0.04588905,0.03127115,0.6385515,0.2116184],"study_design_scores_gemma":[0.0009215159,0.0004006065,0.02835288,0.00166791,0.0005027234,0.0008257673,0.001496591,0.3268071,0.05683165,0.09045549,0.490933,0.0008047805],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.02857276,0.001338196,0.2810532,0.001951372,0.0006960159,0.001091416,0.438976,0.2376629,0.008658189],"genre_scores_gemma":[0.1199894,0.001859048,0.5344673,0.0008493226,0.0002256154,0.003948736,0.3083374,0.026475,0.00384821],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.0342498,"threshold_uncertainty_score":0.1145771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01011512326566493,"score_gpt":0.235935481874241,"score_spread":0.225820358608576,"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."}}