{"id":"W3082285224","doi":"10.1186/s12920-020-0708-z","title":"A novel neoantigen discovery approach based on chromatin high order conformation","year":2020,"lang":"en","type":"article","venue":"BMC Medical Genomics","topic":"vaccines and immunoinformatics approaches","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Key Research and Development Program of China; National Science and Technology Major Project; National Natural Science Foundation of China","keywords":"Chromatin; Computational biology; Human genetics; Biology; Genetics; Bioinformatics; DNA; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002305262,0.0001822841,0.0001942005,0.0000247117,0.00007037453,0.00004916566,0.0003225073,0.000206248,0.0000531679],"category_scores_gemma":[0.000472201,0.0001510334,0.00008767792,0.0001043991,0.00004491392,0.00001161406,0.0001297947,0.0001398999,0.0000450849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000163987,"about_ca_system_score_gemma":0.0004733354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009239263,"about_ca_topic_score_gemma":0.000002709247,"domain_scores_codex":[0.998834,0.00002461516,0.000393891,0.0002266295,0.0002912092,0.0002296294],"domain_scores_gemma":[0.9993126,0.00002379972,0.000127629,0.0002877779,0.00005666492,0.0001915758],"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":[0.003281029,0.002870033,0.002321785,0.004112623,0.0007647525,0.000009260374,0.003301599,0.1625338,0.7154552,0.009977453,0.05419038,0.04118209],"study_design_scores_gemma":[0.00352304,0.0005906589,0.001395462,0.00003334404,0.00003196601,0.00001683773,0.0005261138,0.9415588,0.02135965,0.00001410823,0.03044901,0.0005010086],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3486005,0.00009310684,0.64754,0.0006395471,0.0001015013,0.000302696,0.00004221445,0.00002246421,0.002657974],"genre_scores_gemma":[0.9326413,0.00009826387,0.05648313,0.008598004,0.0005091141,0.00003401965,0.001493545,0.00003708096,0.0001055096],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.779025,"threshold_uncertainty_score":0.6158963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.019677037241054,"score_gpt":0.2209377987763951,"score_spread":0.2012607615353411,"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."}}