{"id":"W2324898097","doi":"10.3389/fpls.2016.00481","title":"RNA-seq Transcriptome Analysis of Panax japonicus, and Its Comparison with Other Panax Species to Identify Potential Genes Involved in the Saponins Biosynthesis","year":2016,"lang":"en","type":"article","venue":"Frontiers in Plant Science","topic":"Ginseng Biological Effects and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":87,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute of Genetics; Ministry of Education, Culture, Sports, Science and Technology; Japan Society for the Promotion of Science; Chiba University; National University of Singapore; Research Organization of Information and Systems","keywords":"Transcriptome; Panax notoginseng; Biology; De novo transcriptome assembly; Araliaceae; Gene; KEGG; Ginseng; Sequence assembly; RNA-Seq; Genetics; Gene expression","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001644098,0.0004042051,0.0004118444,0.0004767526,0.0004628773,0.0003188426,0.0001297696,0.0001669079,0.0006603213],"category_scores_gemma":[0.0001420709,0.0001491425,0.0004631247,0.0006842405,0.0001458986,0.0001995024,0.0002176355,0.0003187687,0.0001965416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001894596,"about_ca_system_score_gemma":0.0003351501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002193765,"about_ca_topic_score_gemma":0.002992576,"domain_scores_codex":[0.9998679,0.000008173716,0.00001038784,0.00006426784,0.0000319548,0.00001726059],"domain_scores_gemma":[0.9999255,0.00001874394,0.00001577516,0.000004958624,0.00002265207,0.00001239554],"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":[0.0001631323,0.00001776421,0.001877996,0.0001968319,0.00001467811,0.0001002354,0.0001004897,0.0002301286,0.9938781,0.0000573627,0.0001546141,0.003208744],"study_design_scores_gemma":[0.0000808552,0.0009026189,0.5626073,0.000100999,0.0003608925,0.001544063,0.0007990833,0.01379418,0.3935978,0.0003874179,0.02574659,0.00007801968],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.971349,0.001811009,0.007508784,0.0001291231,0.00005664314,0.000129823,0.01631085,0.0002291402,0.002475663],"genre_scores_gemma":[0.924952,0.001996282,0.02233885,0.0003886874,0.00005449015,0.0004928592,0.04444714,0.000181679,0.005148059],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002193765,"threshold_uncertainty_score":0.004361987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01761188954420578,"score_gpt":0.263228352450375,"score_spread":0.2456164629061692,"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."}}