{"id":"W2294475834","doi":"10.1371/journal.pone.0150582","title":"Genome-Wide Investigation Using sRNA-Seq, Degradome-Seq and Transcriptome-Seq Reveals Regulatory Networks of microRNAs and Their Target Genes in Soybean during Soybean mosaic virus Infection","year":2016,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Plant Virus Research Studies","field":"Agricultural and Biological Sciences","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; Western University","funders":"Agriculture and Agri-Food Canada; Natural Sciences and Engineering Research Council of Canada; Iowa State University","keywords":"Biology; Transcriptome; microRNA; RNA-Seq; Gene; Genetics; Computational biology; Genome; Soybean mosaic virus; Gene expression; Small RNA; Gene expression profiling; Regulation of gene expression; Virus; Plant virus; Potyvirus","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000231174,0.0002232341,0.0004237601,0.0003223763,0.0002011123,0.0003308469,0.0001042026,0.0001805105,0.0003585158],"category_scores_gemma":[0.0001222815,0.0001626134,0.0004632001,0.0003152346,0.0001279927,0.0001615892,0.0002143749,0.0002325779,0.0001590441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002115605,"about_ca_system_score_gemma":0.0002522406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001144232,"about_ca_topic_score_gemma":0.002656044,"domain_scores_codex":[0.9998515,0.000009336109,0.00000962615,0.00007106199,0.00003903081,0.00001952281],"domain_scores_gemma":[0.9999185,0.00001650461,0.00002566874,0.000005048549,0.00001869975,0.00001560462],"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":[0.0001164912,0.000008140823,0.004777653,0.00005468991,0.0000184761,0.00003937938,0.0000506003,0.0001464666,0.993141,0.00003136731,0.00004728009,0.001568513],"study_design_scores_gemma":[0.00002857912,0.0003480826,0.6212015,0.00002249501,0.0001683198,0.0005748783,0.0003460893,0.01176587,0.36082,0.0002636713,0.004421031,0.00003952922],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9913614,0.0009306345,0.003890822,0.00003453075,0.000009572397,0.00002219248,0.003119555,0.00006148562,0.0005697623],"genre_scores_gemma":[0.9784894,0.0007570151,0.009639933,0.0001122089,0.000008481434,0.00008194536,0.009427222,0.00004261027,0.001441184],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001144232,"threshold_uncertainty_score":0.002275169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05274436874826455,"score_gpt":0.2165289259094141,"score_spread":0.1637845571611495,"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."}}