{"id":"W4398765605","doi":"10.1101/2024.05.23.594371","title":"Predictive Biophysical Neural Network Modeling of a Compendium of <i>in vivo</i> Transcription Factor DNA Binding Profiles for <i>Escherichia coli</i>","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Diffusion and Search Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"National Institutes of Health; Universidad Nacional Autónoma de México","keywords":"Compendium; Escherichia coli; Transcription factor; Computational biology; DNA; Transcription (linguistics); DNA binding site; Biology; Genetics; Chemistry; Promoter; Gene; Gene expression","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":[0.0004776036,0.0004388033,0.0003940572,0.0004365849,0.0002920592,0.0005462517,0.0006584046,0.0008845583,0.001355203],"category_scores_gemma":[0.001362619,0.0003664479,0.0004772694,0.0004012274,0.0004900843,0.000486624,0.0002285383,0.0007080714,0.0001628132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001571224,"about_ca_system_score_gemma":0.0007194884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0170029,"about_ca_topic_score_gemma":0.01415571,"domain_scores_codex":[0.999923,0.00002323595,0.000002668139,0.00002820471,0.00001070509,0.0000122662],"domain_scores_gemma":[0.9994397,0.0003957329,0.00004285777,0.00002381954,0.00007507991,0.00002278478],"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":[0.00001454297,0.00001351167,0.0005505309,0.000007453546,0.00001031078,0.00001371762,0.000008052575,0.9956638,0.0007623676,0.0004178826,0.0001207632,0.002417086],"study_design_scores_gemma":[7.752261e-7,0.000001410343,0.00007842752,3.751227e-7,6.611556e-7,8.140408e-7,6.892104e-7,0.9996722,0.0001042177,0.000124655,0.00001523048,5.937944e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8888614,0.0003067462,0.1064118,0.0006036122,0.00003980157,0.00003085189,0.0006085913,0.0005732363,0.002563928],"genre_scores_gemma":[0.9820737,0.00008122015,0.015386,0.00006542843,0.000009061666,0.00005930073,0.0005066606,0.00003831475,0.001780459],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0170029,"threshold_uncertainty_score":0.03380787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01430526841136648,"score_gpt":0.2338312202039925,"score_spread":0.219525951792626,"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."}}