Abstract Semi-supervised clustering (SSC), a technique integrating semi-supervised
learning and clustering analysis, incorporates the given prior information (eg, class labels …

Network Medicine applies network science approaches to investigate disease
pathogenesis. Many different analytical methods have been used to infer relevant molecular …

Background Protein interactions are crucial components of all cellular processes. Recently,
high-throughput methods have been developed to obtain a global description of the …

Community structure is one of the most important properties of complex networks and is a
foundational concept in exploring and understanding networks. In real world, topology …

Alternative techniques and tools for analyzing biomolecular networks With the recent rapid
advances in molecular biology, high-throughput experimental methods have resulted in …

Discovering a community structure is fundamental for uncovering the links between structure
and function in complex networks. In this paper, we discuss an equivalence of the objective …

The increasing availability of large-scale protein-protein interaction data has made it
possible to understand the basic components and organization of cell machinery from the …

Community detection is a critical issue in the field of complex networks. Nonnegative matrix
factorization (NMF) has been one of the hot research topics in community detection. In the …

With the increasingly accumulated data from high‐throughput technologies, study on
biomolecular networks has become one of key focuses in systems biology and …

Large-scale experiments and data integration have provided the opportunity to
systematically analyze and comprehensively understand the topology of biological networks …