Network-based anomaly detection algorithm reveals proteins with major roles in human tissues
Dima Kagan,
Juman Jubran,
Esti Yeger-Lotem
et al.
Abstract:BackgroundAnomaly detection in graphs is critical in various domains, notably in medicine and biology, where anomalies often encapsulate pivotal information. Here, we focused on network analysis of molecular interactions between proteins, which is commonly used to study and infer the impact of proteins on health and disease. In such a network, an anomalous protein might indicate its impact on the organism’s health.ResultsWe propose Weighted Graph Anomalous Node Detection (WGAND), a novel machine learning-based… Show more
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