An application of topological graph clustering to protein function prediction
arXiv:1408.5634v1
Originality Synthesis-oriented
AI Analysis
This work addresses protein function prediction for biologists, but it appears incremental as it builds on existing methods with a new application.
The authors tackled protein function prediction for yeast by applying a topological graph clustering method, achieving results comparable to or better than state-of-the-art approaches.
We use a semisupervised learning algorithm based on a topological data analysis approach to assign functional categories to yeast proteins using similarity graphs. This new approach to analyzing biological networks yields results that are as good as or better than state of the art existing approaches.