The modern science of networks has made significant advancement in the modeling of
complex real-world systems. One of the most important features in these networks is the …

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 …

Technology opportunity analysis using network analysis and link prediction has attracted the
interest of both academia and industry. However, there are several unresolved issues with …

Proteins interact with each other to play critical roles in many biological processes in cells.
Although promising, laboratory experiments usually suffer from the disadvantages of being …

We combine advances in neural language modeling and structurally motivated design to
develop D-SCRIPT, an interpretable and generalizable deep-learning model, which predicts …

The increasing growth of online social networks has drawn researchers' attention to link
prediction and has been adopted in many fields, including computer sciences, information …

The GOSemSim package, an R-based tool within the Bioconductor project, offers several
methods based on information content and graph structure for measuring semantic similarity …

Technology opportunity analysis (TOA) with ideas generation has been recognized an
important activity to remain competitive and lead the industry in the future. However, there …

Molecular interaction networks are powerful resources for molecular discovery. They are
increasingly used with machine learning methods to predict biologically meaningful …

Link prediction is a paradigmatic problem in network science, which aims at estimating the
existence likelihoods of nonobserved links, based on known topology. After a brief …