Statistical classifiers for diagnosing disease from immune repertoires: a case study using multiple sclerosis - Ostmeyer, Jared; Christley, Scott; Rounds, William H.; Toby, Inimary; Greenberg, Benjamin M.; Monson, Nancy L.; Cowell, Lindsay G. (BMC bioinformatics, 2017)
Keywords: Algorithms; Amino Acid Sequence; Antibodies; Antibody; Area Under Curve; Autoimmune diseases; B-Lymphocytes - metabolism; Bioinformatics; Biomedical and Life Sciences; Case depth; CDR3; Cerebrospinal fluid; Classifiers; Coding; Codons; Complementarity; Complementarity Determining Regions - chemistry; Complementarity Determining Regions - metabolism; Complementarity-determining region 3; Computational biology; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Datasets; Diagnosis; Diagnostic systems; Feasibility studies; High-Throughput Nucleotide Sequencing; Humans; Immune repertoire; Learning algorithms; Life Sciences; Lymphocytes; Lymphocytes B; Machine learning; Microarrays; Models, Statistical; Molecular diagnostic techniques; Multiple sclerosis; Multiple Sclerosis, Relapsing-Remitting - classification; Multiple Sclerosis, Relapsing-Remitting - diagnosis; Multiple Sclerosis, Relapsing-Remitting - immunology; Nervous System Diseases - classification; Nervous System Diseases - diagnosis; Nervous System Diseases - immunology; Neurological diseases; Ovarian cancer; Patients; Receptors; Research Article; ROC Curve; Sequence analysis (applications); Statistical classifier; Statistical methods; Statistics; T cell receptors; Multiple sclerosis; Antibody; CDR3; Immune repertoire; Statistical classifier; Machine learning