In the era of big data, transformation of biomedical big data into valuable knowledge has
been one of the most important challenges in bioinformatics. Deep learning has advanced …

In this paper, we provide an introduction to machine learning tasks that address important
problems in genomic medicine. One of the goals of genomic medicine is to determine how …

Epigenomic profiling has enabled large-scale identification of regulatory elements, yet we
still lack a systematic mapping from any sequence or variant to regulatory activities. We …

Knowing the sequence specificities of DNA-and RNA-binding proteins is essential for
developing models of the regulatory processes in biological systems and for identifying …

The majority of common variants associated with common diseases, as well as an unknown
proportion of causal mutations for rare diseases, fall in noncoding regions of the genome …

Abstract Machine learning methods have been widely applied to big data analysis in
genomics and epigenomics research. Although accuracy and efficiency are common goals …

Familial hypercholesterolemia (FH), characterized by isolated elevation of plasmatic low-
density lipoprotein (LDL) cholesterol and premature coronary heart disease (CHD), is …

Familial hypercholesterolemia (FH) is a genetic disorder characterized by elevated low-
density lipoprotein (LDL) cholesterol and premature cardiovascular disease, with a …

As costs of next-generation sequencing decrease, identification of genetic variants has far
outpaced our ability to understand their functional consequences. This lack of understanding …

Background Familial hypercholesterolemia type IIA (FH) is due to mutations in the low-
density lipoprotein receptor (LDLR) resulting in elevated levels of low-density lipoprotein …