{"id":"W2303687823","doi":"10.1039/c6cc00814c","title":"A charge-suppressing strategy for probing protein methylation","year":2016,"lang":"en","type":"article","venue":"Chemical Communications","topic":"Cancer-related gene regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Charge (physics); Methylation; Chemistry; Nanotechnology; Materials science; Biophysics; Cell biology; Biology; Physics; Biochemistry; DNA","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005080306,0.0009011011,0.0002336033,0.0003235694,0.000347608,0.00023868,0.0005656836,0.0007984259,0.001390735],"category_scores_gemma":[0.0003709711,0.0002782978,0.0003120679,0.0002398999,0.0002971797,0.0003127264,0.0004347724,0.001242074,0.0005991154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002501648,"about_ca_system_score_gemma":0.000308316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002918649,"about_ca_topic_score_gemma":0.0006002329,"domain_scores_codex":[0.999673,0.00006770372,0.00001727813,0.00008188268,0.00009308,0.00006705248],"domain_scores_gemma":[0.9997774,0.00006150227,0.00004619809,0.00003135401,0.000043323,0.00004010813],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001545343,0.00001314939,0.00003433137,0.00002577795,0.00000459801,0.00002598055,0.00000884023,0.00002714763,0.9985005,0.0001509811,0.00004834445,0.001144809],"study_design_scores_gemma":[0.00001008787,0.0001039616,0.0003907164,0.000002240567,0.000008758306,0.0001801128,0.00000595523,0.0006252165,0.9964033,0.00009552898,0.002166739,0.000007368821],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6770291,0.003516198,0.310956,0.001031208,0.0003206977,0.0004025111,0.0005812506,0.0007077137,0.005455337],"genre_scores_gemma":[0.8455873,0.00283272,0.1409166,0.0009261967,0.00008041945,0.000366398,0.001007826,0.0001033511,0.008179248],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.001390735,"threshold_uncertainty_score":0.004652441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04296377008165357,"score_gpt":0.3127515434417907,"score_spread":0.2697877733601372,"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."}}