New application of intelligent agents in sporadic amyotrophic lateral sclerosis identifies unexpected specific genetic background |
| |
| Authors: | Silvana Penco Massimo Buscema Maria Cristina Patrosso Alessandro Marocchi Enzo Grossi |
| |
| Institution: | (1) Medical Genetics, Clinical Chemistry and Clinical Pathology Laboratory, Niguarda Ca' Granda Hospital P.za Ospedale Maggiore 3, 20100 Milan, Italy;(2) Semeion Research Center Via Sersale 117, 00128 Rome, Italy;(3) Bracco SpA Medical Department Via E. Folli 50, , 20134 Milan, Italy |
| |
| Abstract: | Background Few genetic factors predisposing to the sporadic form of amyotrophic lateral sclerosis (ALS) have been identified, but the
pathology itself seems to be a true multifactorial disease in which complex interactions between environmental and genetic
susceptibility factors take place. The purpose of this study was to approach genetic data with an innovative statistical method
such as artificial neural networks to identify a possible genetic background predisposing to the disease. A DNA multiarray
panel was applied to genotype more than 60 polymorphisms within 35 genes selected from pathways of lipid and homocysteine
metabolism, regulation of blood pressure, coagulation, inflammation, cellular adhesion and matrix integrity, in 54 sporadic
ALS patients and 208 controls. Advanced intelligent systems based on novel coupling of artificial neural networks and evolutionary
algorithms have been applied. The results obtained have been compared with those derived from the use of standard neural networks
and classical statistical analysis |
| |
| Keywords: | |
| 本文献已被 SpringerLink 等数据库收录！ |
|
