The workflow starts with a gene set created from Example gene set. CTD is applied which diffuses through all nodes in STRING[1] to identify nodes that are "guilty by association" and highly connected to the initial gene set of interest[2][3]. A list of Highly Connected Genes was obtained from the CTD output. A list of Guilty By Association Genes was obtained from the CTD output. 1. Szklarczyk, D. et al. STRING v10: protein–protein interaction networks, integrated over the tree of life. Nucleic Acids Research vol. 43 D447–D452 (2014). doi:10.1093/nar/gku1003 2. Thistlethwaite, L. R. et al. Correction: CTD: An information-theoretic algorithm to interpret sets of metabolomic and transcriptomic perturbations in the context of graphical models. PLOS Computational Biology vol. 17 e1009551 (2021). doi:10.1371/journal.pcbi.1009551 3. Petrosyan, V. et al. Identifying biomarkers of differential chemotherapy response in TNBC patient-derived xenografts with a CTD/WGCNA approach. iScience vol. 26 105799 (2023). doi:10.1016/j.isci.2022.105799