Background: Networks are powerful resources for describing complex systems. Link prediction is an
important issue in network analysis and has important practical application value. Network representation learning
has proven to be useful for network analysis, especially for link prediction tasks.
Objective: To review the application of network representation learning on link prediction in a biological network,
we summarize recent methods for link prediction in a biological network and discuss the application and
significance of network representation learning in link prediction task.
Method & Results: We first introduce the widely used link prediction algorithms, then briefly introduce the development
of network representation learning methods, focusing on a few widely used methods, and their application
in biological network link prediction. Existing studies demonstrate that using network representation learning
to predict links in biological networks can achieve better performance. In the end, some possible future directions
have been discussed.