Name
Title | ||
|---|---|---|
Statistical classifiers for diagnosing disease from immune repertoires: a case study using multiple sclerosis. |
Abstract | ||
|---|---|---|
Our method is the first to apply statistical learning to immune repertoires to aid disease diagnosis, learning repertoire-level labels from the set of individual immune repertoire sequences. This method produced a repertoire-based statistical classifier for diagnosing RRMS that provides a high degree of diagnostic capability, rivaling the accuracy of diagnosis by a clinical expert. Additionally, this method points to a diagnostic biochemical motif in the antibodies of RRMS patients, which may offer insight into the disease process. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1186/s12859-017-1814-6 | BMC Bioinformatics |
Keywords | Field | DocType |
Antibody,CDR3,Immune repertoire,Machine learning,Multiple sclerosis,Statistical classifier | Deep sequencing,Disease,Biology,Repertoire,Multiple sclerosis,Immune system,Bioinformatics,Genetics,DNA microarray,Antibody,Autoimmune disease | Journal |
Volume | Issue | ISSN |
18 | 1 | 1471-2105 |
Citations | PageRank | References |
1 | 0.35 | 2 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jared Ostmeyer | 1 | 1 | 0.35 |
| Scott Christley | 2 | 293 | 26.68 |
| William Rounds | 3 | 2 | 1.12 |
| Inimary T. Toby | 4 | 2 | 1.46 |
| Benjamin M. Greenberg | 5 | 1 | 0.35 |
| Nancy Monson | 6 | 2 | 1.12 |
| Lindsay G. Cowell | 7 | 153 | 15.43 |