{"id":"W2940275179","doi":"10.2174/1574893614666190410155603","title":"Computational Approaches for Transcriptome Assembly Based on Sequencing Technologies","year":2019,"lang":"en","type":"article","venue":"Current Bioinformatics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Ministry of Education of the People's Republic of China; Hunan Provincial Science and Technology Department; National Natural Science Foundation of China","keywords":"Transcriptome; De novo transcriptome assembly; Computational biology; Sequence assembly; DNA sequencing; Computer science; Genome; Hybrid genome assembly; Biology; Reference genome; Gene; Genetics; Gene expression","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":[0.002077697,0.001631898,0.001595712,0.001900737,0.001419082,0.002487661,0.002399562,0.001326132,0.004057535],"category_scores_gemma":[0.003668408,0.001375705,0.003088014,0.00256982,0.0007477707,0.002073019,0.001529048,0.002199434,0.001959301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00116639,"about_ca_system_score_gemma":0.0019138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003686431,"about_ca_topic_score_gemma":0.003813081,"domain_scores_codex":[0.9990487,0.0003790357,0.00008613371,0.0001978288,0.0002204249,0.00006796584],"domain_scores_gemma":[0.9984875,0.001004627,0.0001050021,0.0001573723,0.0001950643,0.00005037957],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001500643,0.00009487529,0.001568697,0.001075694,0.000350194,0.0003904918,0.0002147159,0.8251711,0.01619797,0.05830598,0.004348845,0.09213141],"study_design_scores_gemma":[0.00001416457,0.00001686299,0.0002424567,0.00003792093,0.0000373849,0.00006224809,0.0000406854,0.96262,0.002846354,0.02759333,0.006463056,0.00002564474],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.003819222,0.0005240424,0.9917573,0.0001486848,0.00008977741,0.00006339151,0.0003902132,0.001438486,0.001768745],"genre_scores_gemma":[0.04881714,0.00173765,0.9437367,0.0001814017,0.0001007538,0.0006068288,0.002573078,0.0009023444,0.00134409],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.004057535,"threshold_uncertainty_score":0.01357377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04642059490391494,"score_gpt":0.2598677564614635,"score_spread":0.2134471615575486,"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."}}