{"id":"W2168264491","doi":"10.1038/nbt.1522","title":"Dynamic modularity in protein interaction networks predicts breast cancer outcome","year":2009,"lang":"en","type":"article","venue":"Nature Biotechnology","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":711,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital; Occupational Cancer Research Centre; Canada Research Chairs; University of New Brunswick; University of Toronto","funders":"","keywords":"Interactome; Modularity (biology); Breast cancer; Carcinogenesis; Biology; Computational biology; Phenotype; Cancer; Outcome (game theory); Protein–protein interaction; Bioinformatics; Interaction network; Gene; Genetics","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":[0.00100268,0.00027458,0.0003522263,0.002109307,0.0002758497,0.0006867389,0.0003376836,0.0005114719,0.001323314],"category_scores_gemma":[0.007048003,0.000314912,0.0004631582,0.001115241,0.0004243519,0.0009755191,0.0005769924,0.0005564621,0.0002860119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005337475,"about_ca_system_score_gemma":0.0002483442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001123622,"about_ca_topic_score_gemma":0.001885287,"domain_scores_codex":[0.999622,0.0001211377,0.00002348887,0.0001031011,0.00006283215,0.00006747408],"domain_scores_gemma":[0.9950033,0.002508967,0.001517625,0.0002967801,0.000286176,0.0003871299],"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":[0.0007487364,0.0001267521,0.9413888,0.00005220469,0.0005247968,0.0002165509,0.0001171413,0.01674997,0.01993629,0.002367747,0.0008336746,0.0169374],"study_design_scores_gemma":[0.00003531624,0.000118856,0.8611866,0.0000141862,0.0002170019,0.0007508107,0.00008864228,0.1192485,0.002838607,0.01501928,0.0004586674,0.00002357004],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955263,0.0002416906,0.003218089,0.000214851,0.000006140863,0.000005391708,0.0003042419,0.00003902639,0.0004443716],"genre_scores_gemma":[0.9992913,0.00004784775,0.0003877178,0.00001248795,0.000008451731,0.000003034289,0.0001647873,0.000005431556,0.0000788067],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002109307,"threshold_uncertainty_score":0.005302787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00349498992628686,"score_gpt":0.2516630259113888,"score_spread":0.2481680359851019,"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."}}