{"id":"W2807000436","doi":"10.1038/s41598-018-19669-4","title":"Computer-aided Discovery of Peptides that Specifically Attack Bacterial Biofilms","year":2018,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Antimicrobial Peptides and Activities","field":"Immunology and Microbiology","cited_by":113,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; National Institute of Allergy and Infectious Diseases; Canadian Institutes of Health Research; Killam Trusts","keywords":"In silico; Quantitative structure–activity relationship; Biofilm; Peptide; In vivo; In vitro; Computational biology; Combinatorial chemistry; Chemistry; Bacteria; Virtual screening; Antibiotics; Staphylococcus aureus; Microbiology; Biology; Biochemistry; Pharmacophore; Stereochemistry; Genetics","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":[0.0005218745,0.0006487787,0.000828884,0.000401756,0.0001459662,0.0008061336,0.0004353678,0.0006254725,0.00101163],"category_scores_gemma":[0.0007371524,0.0002965203,0.0006661406,0.0003672412,0.0001637897,0.0002906692,0.0002993248,0.0004836876,0.0002177059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004451995,"about_ca_system_score_gemma":0.0006372802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001764521,"about_ca_topic_score_gemma":0.002020429,"domain_scores_codex":[0.9998794,0.0000341143,0.000006440304,0.00002914169,0.00003262805,0.00001824698],"domain_scores_gemma":[0.9997713,0.0001584411,0.00003035319,0.000007269568,0.00002275831,0.000009857041],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002843883,0.0002326075,0.003159942,0.0002450935,0.00009072466,0.0001472567,0.0000384395,0.9038718,0.05270796,0.001494568,0.0004985066,0.0372287],"study_design_scores_gemma":[0.00002023218,0.0001322572,0.0002686889,0.00000352857,0.00001462172,0.00001548951,0.000008700476,0.9931355,0.005847976,0.0002853953,0.0002632306,0.000004411668],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8354877,0.002165843,0.1556571,0.0003793316,0.00004248063,0.0001909978,0.001095372,0.001221445,0.003759703],"genre_scores_gemma":[0.9007224,0.0009362202,0.09590229,0.0001141877,0.00001223187,0.0002249834,0.0009950771,0.00004621608,0.001046356],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001764521,"threshold_uncertainty_score":0.003508508,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02596110926316537,"score_gpt":0.2438984656342459,"score_spread":0.2179373563710805,"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."}}