{"id":"W2131869007","doi":"10.1016/j.febslet.2005.02.013","title":"Synthetic modular systems – reverse engineering of signal transduction","year":2005,"lang":"en","type":"review","venue":"FEBS Letters","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital","funders":"","keywords":"Synthetic biology; Modular design; Reverse engineering; Computational biology; Systems biology; Signal transduction; Computer science; Protein engineering; Transduction (biophysics); Proteomics; Biological network; Biology; Gene; Cell biology; Genetics; Biochemistry","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":[0.0006858194,0.0009681761,0.001001657,0.001226397,0.0003362266,0.0008722279,0.001250707,0.001008784,0.001725963],"category_scores_gemma":[0.0005007252,0.0004768603,0.0005750906,0.001084462,0.001258511,0.001276455,0.000749774,0.001351255,0.002105154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001093666,"about_ca_system_score_gemma":0.0003845455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00053039,"about_ca_topic_score_gemma":0.0003809611,"domain_scores_codex":[0.9997036,0.00005822838,0.00001987548,0.00007154813,0.0001184739,0.00002830575],"domain_scores_gemma":[0.9998504,0.00006218379,0.00002511707,0.00002267596,0.0000304783,0.000009037835],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001068875,0.000195388,0.0001653224,0.009038238,0.0001297681,0.0006160361,0.0002135697,0.0104788,0.09219332,0.1557017,0.01349937,0.7176615],"study_design_scores_gemma":[0.00006192036,0.0002630495,0.000298711,0.0006308742,0.00006234057,0.00166533,0.00004470828,0.004076153,0.06207719,0.03274713,0.8980127,0.00005993588],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.005690779,0.9300504,0.04314242,0.0009505656,0.0008586302,0.00009018379,0.00008997512,0.0002729386,0.01885417],"genre_scores_gemma":[0.05868437,0.9009945,0.02800719,0.0005901564,0.000390652,0.0002251467,0.0002046175,0.00006013461,0.01084328],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.001725963,"threshold_uncertainty_score":0.007935166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01218252295687504,"score_gpt":0.2303200518609506,"score_spread":0.2181375289040755,"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."}}