Researchers from Ben-Gurion University of the Negev have developed a machine-learning system to detect abnormal activity in protein networks inside the human body. The system, called weighted graph anomalous node detection (WGAND), uses an algorithm that uncovers suspicious behavior in social networks to identify anomalous behavior in protein networks. The researchers were able to identify proteins associated with brain disorders and heart conditions, as well as those involved in critical biological processes. WGAND outperformed existing methods in terms of accuracy and precision and is open source, allowing researchers worldwide to utilize and build upon it.