Background Many existing bioinformatics predictors are based on machine learning
technology. When applying these predictors in practical studies, their predictive …

Genome-wide association studies (GWASs) have become the focus of the statistical analysis
of complex traits in humans, successfully shedding light on several aspects of genetic …

Epistasis, commonly defined as the interaction between multiple genes, is an important
genetic component underlying phenotypic variation. Many statistical methods have been …

Background Identifying epistasis or epistatic interactions, which refer to nonlinear interaction
effects of single nucleotide polymorphisms (SNPs), is essential to understand disease …

Abstract “Omics” refers to high-throughput analyses of genes, proteins, or metabolites in a
biological system, and is increasingly used for ophthalmic research. These system-based …

Backgroud Taking the advan tage of high-throughput single nucleotide polymorphism (SNP)
genotyping technology, large genome-wide association studies (GWASs) have been …

BACKGROUND More than a century ago, Alexander G. Bell first observed the photoacoustic
effect. He found that absorption of electromagnetic waveforms, such as radio frequency (rf) …

Background Epistasis is recognized fundamentally important for understanding the
mechanism of disease-causing genetic variation. Though many novel methods for detecting …

Genome-wide interaction-based association (GWIBA) analysis has the potential to identify
novel susceptibility loci. These interaction effects could be missed with the prevailing …

Motivation Two-locus model is a typical significant disease model to be identified in genome-
wide association study (GWAS). Due to intensive computational burden and diversity of …