SNPs for disease prognosis

SNPs, protein structure, and disease.

Inherited disease susceptibility in humans is most commonly associated with single nucleotide polymorphisms (SNPs). The mechanisms by which this occurs are still poorly understood. We have analyzed the effect of a set of disease-causing missense mutations arising from SNPs, and a set of newly determined SNPs from the general population. Results of in vitro mutagenesis studies, together with the...

HAPGEN2: simulation of multiple disease SNPs

MOTIVATION Performing experiments with simulated data is an inexpensive approach to evaluating competing experimental designs and analysis methods in genome-wide association studies. Simulation based on resampling known haplotypes is fast and efficient and can produce samples with patterns of linkage disequilibrium (LD), which mimic those in real data. However, the inability of current methods ...

Introduction to SNPs: discovery of markers for disease.

F-SNP: computationally predicted functional SNPs for disease association studies

The Functional Single Nucleotide Polymorphism (F-SNP) database integrates information obtained from 16 bioinformatics tools and databases about the functional effects of SNPs. These effects are predicted and indicated at the splicing, transcriptional, translational and post-translational level. As such, the database helps identify and focus on SNPs with potential deleterious effect to human hea...

Extracting new patterns for cardiovascular disease prognosis

Cardiovascular diseases constitute one of the main causes of mortality in the world, and machine learning has become a powerful tool for analysing medical data in the last few years. In this paper we present an interdisciplinary work based on an ambulatory blood pressure study and the development of a new classification algorithm named REMED. We focused on the discovery of new patterns for abno...