{"id":"W4385612013","doi":"10.1101/2023.08.03.551914","title":"Revealing Shared Proteins and Pathways in Cardiovascular and Cognitive Diseases Using Protein Interaction Network Analysis","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Montreal Heart Institute","funders":"Agencia Estatal de Investigación; Instituto de Salud Carlos III; European Research Area Network on Cardiovascular Diseases; Ministerio de Ciencia e Innovación; Türkiye Bilimsel ve Teknolojik Araştırma Kurumu","keywords":"Oxidative stress; Computational biology; Signal transduction; Phenotype; Biology; Cognition; Neuroscience; Bioinformatics; Disease; Glycation; Medicine; Receptor; Gene; Cell biology; Genetics; Pathology","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":[0.0004557197,0.0007320661,0.0004629967,0.003820325,0.0004789143,0.0007753825,0.0003140266,0.0003581792,0.002620297],"category_scores_gemma":[0.000898431,0.0001812065,0.001202893,0.002381894,0.0002280726,0.000350394,0.0006020729,0.0003643284,0.0003779425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000549773,"about_ca_system_score_gemma":0.000669988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004459882,"about_ca_topic_score_gemma":0.003924663,"domain_scores_codex":[0.9997069,0.00009204751,0.00001603864,0.0001051157,0.00004267999,0.00003718598],"domain_scores_gemma":[0.9996426,0.0001845684,0.00007582696,0.00002244007,0.00003612481,0.00003841753],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003017633,0.0007405065,0.3855728,0.004834639,0.005377708,0.002415601,0.0004893324,0.2404535,0.1814855,0.01487263,0.01878786,0.1419524],"study_design_scores_gemma":[0.00008295661,0.0002159407,0.2434948,0.0001282793,0.001042441,0.0008114803,0.0003173111,0.7006812,0.01545447,0.02442203,0.01326888,0.00008023196],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8593553,0.005629064,0.09203308,0.001252712,0.0001083593,0.0001515304,0.03560322,0.002466383,0.003400435],"genre_scores_gemma":[0.9415489,0.001515121,0.03732853,0.0001020722,0.00003620265,0.000121172,0.01844391,0.00007748789,0.0008265583],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004459882,"threshold_uncertainty_score":0.00886786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01763585644767331,"score_gpt":0.2229854706350194,"score_spread":0.2053496141873461,"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."}}