Protein arrays and pattern recognition: new tools to assist in the identification and management of autoimmune disease
| Autor: | C S Hixson, Steven R. Binder, John Glossenger |
|---|---|
| Rok vydání: | 2006 |
| Předmět: |
Immunology
Protein Array Analysis Disease Biology computer.software_genre Autoimmune Diseases Pattern Recognition Automated Antibody Repertoire Antigen medicine Immunology and Allergy Humans Connective Tissue Diseases Autoantibodies Autoimmune disease business.industry Autoantibody Pattern recognition medicine.disease Expert system Identification (information) Pattern recognition (psychology) Artificial intelligence business computer Algorithms |
| Zdroj: | Autoimmunity reviews. 5(4) |
| ISSN: | 1568-9972 |
| Popis: | The occurrence of antibody patterns in connective tissue diseases has been recognized for thirty years, but the generation of multiple antibody results relied on time-consuming immunodiffusion or electrophoretic techniques. Today it is possible to study the antibody repertoire using rapid multi-analyte technologies, generally referred to as protein arrays. These arrays may use planar surfaces similar to DNA arrays, or use microspheres in suspension (“liquid arrays”). Also, many high quality autoantigens are now commercially available, including recombinant antigens. The vast amount of information that can be generated by measuring multiple antibodies for multiple patients has created demand for data processing. Software programs to aid physicians in reviewing multiple inputs as an aid to disease diagnosis and classification have been available for twenty years. Initial work used the “expert systems” approach; more recently pattern recognition has been widely evaluated because of the improvements in software programs and computational speed. The use of antibody data, generated in protein arrays, may assist in establishing diagnosis, in identifying potentially significant antibody patterns in advance of clinical symptoms, and in classifying patients based on expected disease progression. |
| Databáze: | OpenAIRE |
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