{"id":"W2131813051","doi":"10.1093/bioinformatics/btu762","title":"EPGA: <i>de novo</i> assembly using the distributions of reads and insert size","year":2014,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genome Rearrangement Algorithms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Contig; Sequence assembly; Hybrid genome assembly; De Bruijn graph; Computer science; Sequence (biology); Insert (composites); Genome; De Bruijn sequence; Graph; Extension (predicate logic); Reference genome; Algorithm; Computational biology; Biology; Theoretical computer science; Genetics; Mathematics; Combinatorics","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":[0.001597001,0.002322746,0.001019116,0.002181105,0.0009747374,0.001487558,0.001532956,0.001122784,0.002697368],"category_scores_gemma":[0.005390555,0.0007989994,0.001190805,0.001808441,0.0009048019,0.001736802,0.001425003,0.001325318,0.001518225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009644153,"about_ca_system_score_gemma":0.001569914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004320345,"about_ca_topic_score_gemma":0.004548238,"domain_scores_codex":[0.9988421,0.000270171,0.00007412604,0.0004310877,0.0002958048,0.00008675589],"domain_scores_gemma":[0.997201,0.001287433,0.0004760147,0.0004549729,0.000495447,0.00008518219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006576119,0.0002762919,0.01967786,0.0008840068,0.0003655418,0.000468098,0.0004560461,0.2277194,0.07156665,0.01072578,0.0141639,0.6530389],"study_design_scores_gemma":[0.00008398943,0.0002983193,0.005944372,0.00006933045,0.0001272967,0.0005725258,0.0001545692,0.9140632,0.0510115,0.01675961,0.01084992,0.00006531466],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02227961,0.0003073113,0.9642116,0.0001246677,0.00003364349,0.0002176704,0.0005231526,0.01122033,0.001082084],"genre_scores_gemma":[0.09948464,0.0002751208,0.8943799,0.0001327462,0.00002367692,0.0002645084,0.002799868,0.001100167,0.001539403],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004320345,"threshold_uncertainty_score":0.009023607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01103939165250195,"score_gpt":0.2415699575942003,"score_spread":0.2305305659416983,"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."}}