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Your search keyword '"Elisabetta Zachara"' showing total 2 results
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2 results on '"Elisabetta Zachara"'

1. Prediction and visualization data for the interpretation of sarcomeric and non-sarcomeric DNA variants found in patients with hypertrophic cardiomyopathy

Author

Irene Bottillo, Daniela D’Angelantonio, Viviana Caputo, Alessandro Paiardini, Martina Lipari, Carmelilia De Bernardo, Silvia Majore, Marco Castori, Elisabetta Zachara, Federica Re, and Paola Grammatico

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Science (General), Q1-390
Abstract

Genomic technologies are redefining the understanding of genotype–phenotype relationships and over the past decade, many bioinformatics algorithms have been developed to predict functional consequences of single nucleotide variants. This article presents the data from a comprehensive computational workflow adopted to assess the biomedical impact of the DNA variants resulting from the experimental study “Molecular analysis of sarcomeric and non-sarcomeric genes in patients with hypertrophic cardiomyopathy” (Bottillo et al., 2016) [1]. Several different independently methods were employed to predict the functional consequences of alleles that result in amino acid substitutions, to study the effect of some DNA variants over the splicing process and to investigate the impact of a sequence variant with respect to the evolutionary conservation.

Published
2016
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2. Prediction and visualization data for the interpretation of sarcomeric and non-sarcomeric DNA variants found in patients with hypertrophic cardiomyopathy

Author

Federica Re, Carmelilia De Bernardo, Viviana Caputo, Irene Bottillo, Martina Lipari, Marco Castori, Paola Grammatico, Daniela D'Angelantonio, Alessandro Paiardini, Elisabetta Zachara, and Silvia Majore

Subjects
0301 basic medicine, Genetics, Multidisciplinary, Hypertrophic cardiomyopathy, Dna variants, Biology, medicine.disease, lcsh:Computer applications to medicine. Medical informatics, Conserved sequence, 3304, 03 medical and health sciences, 030104 developmental biology, RNA splicing, medicine, lcsh:R858-859.7, In patient, Allele, lcsh:Science (General), Gene, Data Article, Sequence (medicine), lcsh:Q1-390
Abstract

Genomic technologies are redefining the understanding of genotype–phenotype relationships and over the past decade, many bioinformatics algorithms have been developed to predict functional consequences of single nucleotide variants. This article presents the data from a comprehensive computational workflow adopted to assess the biomedical impact of the DNA variants resulting from the experimental study “Molecular analysis of sarcomeric and non-sarcomeric genes in patients with hypertrophic cardiomyopathy” (Bottillo et al., 2016) [1]. Several different independently methods were employed to predict the functional consequences of alleles that result in amino acid substitutions, to study the effect of some DNA variants over the splicing process and to investigate the impact of a sequence variant with respect to the evolutionary conservation.

Full Text
View/download PDF

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