{"id":"W1486212524","doi":"10.1111/j.1747-0285.2010.01044.x","title":"Optimization of Antibacterial Peptides by Genetic Algorithms and Cheminformatics","year":2010,"lang":"en","type":"article","venue":"Chemical Biology & Drug Design","topic":"Antimicrobial Peptides and Activities","field":"Immunology and Microbiology","cited_by":96,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver General Hospital; University of British Columbia","funders":"Canadian Institutes of Health Research; British Columbia Centre for Disease Control; Canada Research Chairs; Foundation for the National Institutes of Health","keywords":"Cheminformatics; Antibacterial peptide; Computational biology; Computer science; Algorithm; Chemistry; Bioinformatics; Biology; Antibacterial activity; Genetics; Bacteria","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":[0.001087083,0.00102799,0.0007981376,0.001005013,0.000321413,0.0007807301,0.0006832653,0.0008357267,0.001080855],"category_scores_gemma":[0.002251709,0.0004535844,0.000634441,0.0006465868,0.0006169095,0.0005665713,0.0004210299,0.0006914074,0.0002454214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007688198,"about_ca_system_score_gemma":0.001037228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001788459,"about_ca_topic_score_gemma":0.002300773,"domain_scores_codex":[0.9996075,0.0001869196,0.00002236374,0.00005448347,0.00009851606,0.00003020063],"domain_scores_gemma":[0.999424,0.0004026384,0.00006359997,0.00002452059,0.0000695136,0.00001585528],"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":[0.00007516206,0.0001192433,0.001045567,0.00009815029,0.00005918743,0.00005514266,0.00003125634,0.9315417,0.00662343,0.004696386,0.00033128,0.05532346],"study_design_scores_gemma":[0.00003291131,0.0000844444,0.00016303,0.0000125553,0.00001726011,0.0000236598,0.00001647997,0.9932341,0.002754666,0.002788364,0.0008654124,0.000007116023],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2306031,0.001436316,0.7567604,0.0005471612,0.0000806049,0.0002812456,0.0001036478,0.001078477,0.009109031],"genre_scores_gemma":[0.4345207,0.0009221509,0.5620235,0.0002562754,0.00003919973,0.0004461761,0.0001840552,0.0001152571,0.001492707],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001788459,"threshold_uncertainty_score":0.005749106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007076495132156544,"score_gpt":0.2091201774527507,"score_spread":0.2020436823205941,"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."}}