{"id":"W2155201678","doi":"10.1093/bioinformatics/btt092","title":"EBARDenovo: highly accurate <i>de novo</i> assembly of RNA-Seq with efficient chimera-detection","year":2013,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"De Bruijn graph; Sequence assembly; De Bruijn sequence; Computer science; Computational biology; De novo transcriptome assembly; Amplicon; RNA-Seq; Software; RNA; Chimera (genetics); Biology; Graph; Genetics; Gene; Transcriptome; Theoretical computer science; Mathematics; Programming language; Gene expression; Combinatorics; Polymerase chain reaction","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":[0.005041101,0.002215239,0.001756921,0.001355556,0.001863345,0.002906906,0.00366507,0.001640388,0.008073058],"category_scores_gemma":[0.008544173,0.002066254,0.00173539,0.001060843,0.001020889,0.00182861,0.002505576,0.003866793,0.007027433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001060897,"about_ca_system_score_gemma":0.001859211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003272859,"about_ca_topic_score_gemma":0.004711528,"domain_scores_codex":[0.998021,0.0004287979,0.0001885365,0.0007107356,0.000507863,0.000142961],"domain_scores_gemma":[0.9974733,0.001212184,0.0002904636,0.0005243729,0.0003646144,0.0001349977],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002604752,0.0003361022,0.007755816,0.005259264,0.001101373,0.0009739479,0.001973165,0.06261905,0.4476746,0.03084854,0.1679189,0.2709345],"study_design_scores_gemma":[0.0003117811,0.0002841787,0.00361881,0.0003983366,0.0002257974,0.001085184,0.0001475229,0.3705112,0.3852046,0.01622886,0.2215915,0.0003922863],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01936425,0.001032573,0.864219,0.0002691172,0.0002941084,0.0003474859,0.005009386,0.1048288,0.004635335],"genre_scores_gemma":[0.03919058,0.000422377,0.9240361,0.0002266233,0.0000367037,0.0006999962,0.01018561,0.02163094,0.003571109],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008073058,"threshold_uncertainty_score":0.0270071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007075047158963154,"score_gpt":0.2059673794860584,"score_spread":0.1988923323270953,"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."}}