Network community detection with higher-order features has become a hot research topic
recently since higher-order features that are captured at the level of small network …

Performing network-based analysis on medical and biological data makes a wide variety of
machine learning tools available. Clustering, which can be used for classification, presents …

Background Many algorithms require doing a large number of betweenness centrality
calculations quickly, and accommodating this need is an active open research area. There …

Reliable identification of Inflammatory biomarkers from metagenomics data is a promising
direction for develo** non-invasive, cost-effective, and rapid clinical tests for early …

With the growing ubiquity of data in network form, clustering in the context of a network,
represented as a graph, has become increasingly important. Clustering is a very useful data …

This paper presents a network science approach to investigate a health information dataset,
the Sexual Acquisition and Transmission of HIV Cooperative Agreement Program …

This paper examines a schema for graph-theoretic clustering using node-based resilience
measures. Node-based resilience measures optimize an objective based on a critical set of …

The human population displays wide variety in demographic history, ancestry, content of
DNA derived from hominins or ancient populations, adaptation, traits, copy number variation …

Powdery mildew is the most economically important disease of cultivated grapevines
worldwide. In the agricultural community, there is a great need for better understanding of …

Many algorithms require doing a large number of betweenness centrality calculations
quickly, and accommodating this need is an active open research area. Two of the most …