Advances in Computational Methods for Genetic Diseases
1University of Naples Parthenope, Napoli, Italy
2University of Oxford, Oxford, UK
3University of Naples Federico II, Napoli, Italy
4University of Naples, Napoli, Italy
Advances in Computational Methods for Genetic Diseases
Description
Genetic diseases are widely studied for the relevant impact on the human health. In the last years, a large amount of experimental data has been available. The identification of new strategies for elaborating such experimental data is becoming more and more necessary since the large amount of information can sometimes represent a real obstacle for the effective identification of relevant findings. The aim of the special issue is to review the recent advances about the research on computational methods concerning with genetic diseases.
Potential topics include, but are not limited to:
- Computational and mathematical methods for the following:
- Evaluating the pathogenicity of novel genetic variants
- The evaluation of protein folding and/or protein-protein interactions in presence of genetic variants
- Analysis of experimental data from next generation sequencing
- Searching for variant/mutation databases for massive data analysis
- Analysis of “omics” data
- Analysis of complex diseases, namely, multifactorial and polygenic, for example, diabetes, hypertension and dyslipidemia
- Variant analysis from Genome Wide Association studies
- Analysis of common genetic variants (i.e., SNPs, HLA genotypes, microsatellites)
- Analysis of quantitative trait loci
- The integration of genetic and nongenetic factors for prediction of disease predisposition
- The identification of potential gene regulatory elements (i.e., binding of transcription factors, and miRNAs)
- Analysis of gene expression data
- Analysis of biological models of genetic diseases