{"id":"W2803639923","doi":"10.1093/bioinformatics/bty385","title":"MRMAssayDB: an integrated resource for validated targeted proteomics assays","year":2018,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Jewish General Hospital; Genome British Columbia; University of Victoria","funders":"Fondation De Famille Alvin Segal; Leids Universitair Medisch Centrum; Genome British Columbia; McGill University; University of Victoria; Jewish General Hospital; Leading Edge Endowment Fund; Genome Canada","keywords":"Proteomics; UniProt; KEGG; Computational biology; Quantitative proteomics; Computer science; Resource (disambiguation); Bioinformatics; Biology; Gene ontology; Gene; Biochemistry; Gene expression","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":[0.006809882,0.004840292,0.003746687,0.00863683,0.001379047,0.00737698,0.006961405,0.002363089,0.03764477],"category_scores_gemma":[0.00967742,0.002453079,0.001889273,0.006273909,0.0007808871,0.005349681,0.006350324,0.002853298,0.05652726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001698378,"about_ca_system_score_gemma":0.00341385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002708402,"about_ca_topic_score_gemma":0.002027057,"domain_scores_codex":[0.9952955,0.0007150902,0.0007867744,0.001013201,0.001900671,0.0002888049],"domain_scores_gemma":[0.9927288,0.002064043,0.001263359,0.001657294,0.001670944,0.0006155706],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00400626,0.0004656806,0.006252246,0.007849227,0.0009913337,0.001291135,0.000416485,0.003757533,0.0631244,0.01124608,0.767262,0.1333375],"study_design_scores_gemma":[0.00094232,0.0003149092,0.007892588,0.001161824,0.0004452432,0.001866362,0.0001863014,0.03337289,0.1228641,0.01840807,0.8119812,0.0005641363],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.006750618,0.005653352,0.171661,0.001084736,0.0003925866,0.0008099969,0.3316087,0.4647644,0.0172747],"genre_scores_gemma":[0.02671397,0.003948185,0.1998823,0.001623316,0.0002899045,0.001685964,0.7186434,0.03902832,0.008184673],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.03764477,"threshold_uncertainty_score":0.1259343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02124059773980129,"score_gpt":0.2857756677972513,"score_spread":0.26453507005745,"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."}}