{"id":"W2112888168","doi":"10.1038/nmeth.1517","title":"De novo assembly and analysis of RNA-seq data","year":2010,"lang":"en","type":"article","venue":"Nature Methods","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1050,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; BC Cancer Agency; Canada's Michael Smith Genome Sciences Centre","funders":"","keywords":"Contig; Sequence assembly; Substring; Pipeline (software); Computational biology; RNA-Seq; Transcriptome; Biology; De novo transcriptome assembly; RNA; Genetics; Gene; Computer science; Genome; Gene expression; Set (abstract data type)","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":[0.003198098,0.001955848,0.001879085,0.002540596,0.002246413,0.002519035,0.001927579,0.0009675781,0.008051694],"category_scores_gemma":[0.009355992,0.001913195,0.002496408,0.002030521,0.0007181324,0.0008275704,0.001626997,0.005289873,0.007702449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001219708,"about_ca_system_score_gemma":0.00347587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003443387,"about_ca_topic_score_gemma":0.01386389,"domain_scores_codex":[0.9980155,0.0002992229,0.0002048345,0.0006816672,0.0006089181,0.000189845],"domain_scores_gemma":[0.9931932,0.002975591,0.0003229502,0.001562747,0.001591115,0.0003543249],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001302863,0.0003285659,0.007545512,0.001958991,0.0006903599,0.0005833668,0.0007678311,0.01358351,0.840354,0.01078136,0.03282645,0.08927722],"study_design_scores_gemma":[0.0002782743,0.0002567857,0.01908909,0.0001914036,0.0004171575,0.0005956857,0.0003350887,0.1714429,0.6307653,0.02473572,0.1515105,0.0003820522],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04617281,0.0005402401,0.8514225,0.0003863817,0.0008839172,0.00122484,0.07092199,0.02451471,0.003932526],"genre_scores_gemma":[0.053114,0.0003575337,0.8494779,0.000412996,0.0001401388,0.002266647,0.08257397,0.007664101,0.003992782],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008051694,"threshold_uncertainty_score":0.02693558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0223015164198906,"score_gpt":0.3865809976313916,"score_spread":0.364279481211501,"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."}}