Accurately modeling biased random walks on weighted networks using node2vec.

Abstract excerpt

MOTIVATION: Accurately representing biological networks in a low-dimensional space, also known as network embedding, is a critical step in network-based machine learning and is carried out widely using node2vec, an unsupervised method based on biased random walks. However, while many networks, including functional gene interaction networks, are dense, weighted graphs, node2vec is fundamentally limited in its...

Topics

Share this publication in a Topic to start or enrich a Post.

• Share to Epistasis, Genetic
• Share to Gene Regulatory Networks
• Share to Machine Learning