Biological networks are powerful resources for the discovery of genes and genetic modules
that drive disease. Fundamental to network analysis is the concept that genes underlying the …

Disease–gene association through genome-wide association study (GWAS) is an arduous
task for researchers. Investigating single nucleotide polymorphisms that correlate with …

Motivation Traditional drug discovery and development are often time-consuming and high
risk. Repurposing/repositioning of approved drugs offers a relatively low-cost and high …

Motivation It has been shown that microRNAs (miRNAs) play key roles in variety of
biological processes associated with human diseases. In Consideration of the cost and …

The emergence of large-scale genomic, chemical and pharmacological data provides new
opportunities for drug discovery and repositioning. In this work, we develop a computational …

INTRODUCTION A disease is rarely a straightforward consequence of an abnormality in a
single gene, but rather reflects the interplay of multiple molecular processes. The …

Motivation: Most existing methods for predicting causal disease genes rely on specific type
of evidence, and are therefore limited in terms of applicability. More often than not, the type …

Discovering disease-gene association is a fundamental and critical biomedical task, which
assists biologists and physicians to discover pathogenic mechanism of syndromes. With …

Identification of disease-associated circular RNAs (circRNAs) is of critical importance,
especially with the dramatic increase in the amount of circRNAs. However, the availability of …

Deciphering the gene disease association is an important goal in biomedical research. In
this paper, we use a novel relevance measure, called HeteSim, to prioritize candidate …