{"id":"W2513487313","doi":"10.1038/srep31730","title":"Complete De Novo Assembly of Monoclonal Antibody Sequences","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":172,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bioinformatics Solutions (Canada); University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; National Key Research and Development Program of China; Scheme for Promotion of Academic and Research Collaboration; Hospital for Sick Children","keywords":"Sequence assembly; Computational biology; Monoclonal antibody; De Bruijn sequence; Genome; Proteomics; Immunoglobulin light chain; De Bruijn graph; Computer science; Biology; Antibody; Graph; Gene; Genetics; Mathematics; Combinatorics; Transcriptome; Theoretical computer science","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":[0.001258089,0.001115173,0.001156499,0.001316095,0.0003766481,0.0009384016,0.000681103,0.0006562649,0.001496507],"category_scores_gemma":[0.002989753,0.0007551436,0.001081554,0.00076294,0.0002396663,0.0008213092,0.000889381,0.0008868056,0.00170557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00043068,"about_ca_system_score_gemma":0.0006332711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008249926,"about_ca_topic_score_gemma":0.001315086,"domain_scores_codex":[0.9992713,0.0001236359,0.00009292795,0.0002310888,0.0002249553,0.00005614187],"domain_scores_gemma":[0.9984164,0.0004893897,0.0002343151,0.0002465793,0.0005282357,0.00008506612],"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":[0.0003297962,0.00006422749,0.001859714,0.0004755872,0.0001265202,0.0003022318,0.0001694662,0.01442211,0.8757753,0.001462407,0.002039077,0.1029735],"study_design_scores_gemma":[0.00005973484,0.0003698486,0.002850215,0.00005918446,0.0001185688,0.0004631284,0.00008411824,0.1994904,0.7692435,0.003248741,0.02395249,0.00006004807],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.195265,0.001463978,0.7892915,0.0001589027,0.0001572561,0.0003046622,0.001771339,0.009694983,0.001892468],"genre_scores_gemma":[0.1925298,0.0007976736,0.7969776,0.0001864414,0.00003537136,0.0002467202,0.006059536,0.001108162,0.002058631],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001496507,"threshold_uncertainty_score":0.006653488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02414833861714541,"score_gpt":0.3142664562418849,"score_spread":0.2901181176247395,"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."}}