arXiv:1408.5634
An application of topological graph clustering to protein function prediction
원문 초록
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.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Tri-Learn Graph Fusion Network for Attributed Graph Clustering
Unsupervised Graph Clustering with Deep Structural Entropy
Adaptive Local Clustering over Attributed Graphs
The Shape of Consumer Behavior: A Symbolic and Topological Analysis of Time Series
Imputation-free and Alignment-free: Incomplete Multi-view Clustering Driven by Consensus Semantic Learning
Rhomboid Tiling for Geometric Graph Deep Learning
토론
이 논문과 연결된 포럼 글이 아직 없습니다.