Personalized diagnosis by cached solutions with hypertension as a study model
Genet. mol. res. (Online)
;
5(4): 856-867, 2006. tab, ilus, graf
Article
in English
| LILACS
| ID: lil-482072
ABSTRACT
Statistical modeling of links between genetic profiles with environmental and clinical data to aid in medical diagnosis is a challenge. Here, we present a computational approach for rapidly selecting important clinical data to assist in medical decisions based on personalized genetic profiles. What could take hours or days of computing is available on-the-fly, making this strategy feasible to implement as a routine without demanding great computing power. The key to rapidly obtaining an optimal/nearly optimal mathematical function that can evaluate the [quot ]disease stage[quot ] by combining information of genetic profiles with personal clinical data is done by querying a precomputed solution database. The database is previously generated by a new hybrid feature selection method that makes use of support vector machines, recursive feature elimination and random sub-space search. Here, to evaluate the method, data from polymorphisms in the renin-angiotensin-aldosterone system genes together with clinical data were obtained from patients with hypertension and control subjects. The disease [quot ]risk[quot ] was determined by classifying the patients' data with a support vector machine model based on the optimized feature; then measuring the Euclidean distance to the hyperplane decision function. Our results showed the association of renin-angiotensin-aldosterone system gene haplotypes with hypertension. The association of polymorphism patterns with different ethnic groups was also tracked by the feature selection process. A demonstration of this method is also available online on the project's web site.
Full text:
Available
Index:
LILACS (Americas)
Main subject:
Polymorphism, Genetic
/
Renin-Angiotensin System
/
Pattern Recognition, Automated
/
Diagnosis, Computer-Assisted
/
Genetic Predisposition to Disease
/
Hypertension
Type of study:
Diagnostic study
/
Observational study
/
Prognostic study
/
Risk factors
Limits:
Female
/
Humans
/
Male
Language:
English
Journal:
Genet. mol. res. (Online)
Journal subject:
Molecular Biology
/
Genetics
Year:
2006
Type:
Article
Affiliation country:
Brazil
Institution/Affiliation country:
Fiocruz/BR
/
Instituto Nacional de Cardiologia/BR
/
Instituto Oswaldo Cruz/BR
/
UFRJ/BR
/
Universidade Federal de Juiz de For a/BR
/
Universidade Federal do Rio de Janeiro/BR
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