{"id":"W2797229131","doi":"10.22215/etd/2016-11283","title":"Realizing the Potential of Protein-Protein Interaction Prediction for Studying Single and Evolutionarily Similar Organisms and Engineering Inhibitory Proteins with InSiPS: The In Silico Protein Synthesizer","year":2016,"lang":"en","type":"dissertation","venue":"","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"In silico; Protein engineering; Protein–protein interaction; Inhibitory postsynaptic potential; Computational biology; Biology; Chemistry; Cell biology; Biochemistry; Neuroscience; Gene","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001300829,0.001244472,0.001030697,0.0005945386,0.0003510739,0.0008525126,0.0009027257,0.0006505418,0.00177978],"category_scores_gemma":[0.001505667,0.0005148844,0.001544531,0.0005009071,0.0004179532,0.00122875,0.0007301035,0.001645651,0.0008648979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005446082,"about_ca_system_score_gemma":0.0005836725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007636735,"about_ca_topic_score_gemma":0.0009481117,"domain_scores_codex":[0.999602,0.0001161459,0.00002268408,0.0001322052,0.0001043093,0.00002277658],"domain_scores_gemma":[0.9992855,0.0003917432,0.00007587625,0.0001151743,0.00008256162,0.00004912998],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001488823,0.000562233,0.01442728,0.001352097,0.001057498,0.0004235145,0.0002413223,0.1200911,0.6398878,0.02485219,0.01008964,0.1855264],"study_design_scores_gemma":[0.0001995189,0.000477377,0.003347761,0.00005067542,0.0005885309,0.0003760143,0.00007709883,0.6549263,0.2998634,0.02454399,0.01547378,0.00007547764],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1911788,0.002160716,0.7827309,0.001794964,0.0001664987,0.0001345534,0.003440221,0.0129257,0.0054676],"genre_scores_gemma":[0.3012646,0.002098544,0.6871061,0.000437643,0.00007764768,0.0001788908,0.005916385,0.001016095,0.001904082],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00177978,"threshold_uncertainty_score":0.006879508,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006138956238456667,"score_gpt":0.1975140057191808,"score_spread":0.1913750494807241,"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."}}