The majority of common diseases are influenced by multiple genetic and environmental factors such as Cancer. Even though uncovering the main causes of disease is deemed difficult due to the complexity of gene-gene and gene-environment interactions, major research efforts aim at identifying disease risk factors, especially genetic ones. Over the past decade, disease association studies have been...

Genome-wide association studies (GWAS) have been successful in facilitating the understanding of genetic architecture behind human diseases, but this approach faces many challenges. To identify disease-related loci with modest to weak effect size, GWAS requires very large sample sizes, which can be computational burdensome. In addition, the interpretation of discovered associations remains diff...

The rapid progress of genomic technologies has been providing new opportunities to address the need of maturity-onset diabetes of the young (MODY) molecular diagnosis. However, whether a new mutation causes MODY can be questionable. A number of in silico methods have been developed to predict functional effects of rare human mutations. The purpose of this study is to compare the performance of ...

Phenylketonuria (PKU) is the most common autosomal recessive disorder of amino acid metabolism. Thedisease is caused mainly by mutations in the phenylalanine hydroxylase (PAH) gene, encoding phenylalaninehydroxylase (PAH) enzyme. The PAH enzyme deficiency results in the elevation of phenylalanine inthe blood, which may cause severe irreversible mental retardation in the affect...

introduction: autosomal dominant polycystic kidney disease (adpkd) is one of the most common genetic kidney disorders with the incidence of 1 in 1,000 births. adpkd is genetically heterogeneous with two genes identified: pkd1 (16p13.3, 46 exons) and pkd2 (4q21, 15 exons). eighty five percent of the patients with adpkd have at least one mutation in the pkd1 gene. genetic studies have demonstrate...

In recent years, much research has focused on using machine learning (ML) for disease prediction based gene expression (GE) data. However, many diseases have received considerable attention, whereas some, including Alzheimer’s (AD), not, perhaps due to data shortage. The present work is intended fill this gap by introducing a symmetric framework predict AD from GE data, with the aim produce mos...

Machine Learning (ML) is an emerging technology and a discipline to study how use the machine simulate human learning activities. It focuses on of data algorithms imitate way that humans learn, gradually improving its accuracy. Prediction in ML involves using trained model make predictions forecasts, about new unseen based patterns learned from past data. On contrary healthcare plays important ...

BACKGROUND The ability to identify obese individuals who will successfully lose weight in response to dietary intervention will revolutionize disease management. Therefore, we asked whether it is possible to identify subjects who will lose weight during dietary intervention using only a single gene expression snapshot. METHODOLOGY/PRINCIPAL FINDINGS The present study involved 54 female subjec...