{"id":"W2979945966","doi":"10.1109/tcbb.2019.2945761","title":"EPGA-SC : A Framework for<i>de novo</i>Assembly of Single-Cell Sequencing Reads","year":2019,"lang":"en","type":"article","venue":"IEEE/ACM Transactions on Computational Biology and Bioinformatics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Higher Education Discipline Innovation Project; National Natural Science Foundation of China","keywords":"Contig; Sequence assembly; Hybrid genome assembly; Computer science; DNA sequencing; Single cell sequencing; Deep sequencing; Computational biology; Nanopore sequencing; Genome; Algorithm; Biology; Genetics; Exome sequencing; Mutation; Gene","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":[0.003919775,0.003384026,0.002164022,0.002496582,0.001493787,0.002722208,0.003703989,0.002006321,0.003217893],"category_scores_gemma":[0.007422149,0.001846971,0.004026586,0.002089906,0.001329027,0.00193708,0.003535255,0.003876589,0.003188754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001236245,"about_ca_system_score_gemma":0.002805804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006754888,"about_ca_topic_score_gemma":0.008710351,"domain_scores_codex":[0.9977495,0.0005599,0.0002278195,0.0006762541,0.0005723402,0.0002142096],"domain_scores_gemma":[0.9969077,0.001314507,0.000316648,0.0006683292,0.0006133694,0.0001795733],"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":[0.001095104,0.0003275257,0.005966037,0.003071291,0.001179268,0.001705907,0.00148491,0.285524,0.1396549,0.0343269,0.03636481,0.4892993],"study_design_scores_gemma":[0.0001587834,0.0002347191,0.001337357,0.0001539311,0.000122773,0.0004994111,0.0001666428,0.8864897,0.04303462,0.0236693,0.04393302,0.000199788],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00245649,0.0002702952,0.975758,0.00004486344,0.00005613018,0.0001863424,0.0004885764,0.02023176,0.0005076332],"genre_scores_gemma":[0.02114723,0.0002718256,0.9700991,0.0001767007,0.00003708695,0.0005881061,0.003843626,0.00304278,0.0007936768],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006754888,"threshold_uncertainty_score":0.02073002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01982537621100055,"score_gpt":0.2612341450046684,"score_spread":0.2414087687936678,"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."}}