25 citations · 29 across the 5 of their papers we have counts for
5 papers
Simplifying complex machine learning by linearly separable network embedding spaces
Alexandros Xenos, Noel-Malod Dognin, Natasa Przulj
Low-dimensional embeddings are a cornerstone in the modelling and analysis of complex networks. However, most existing approaches for mining network embedding spaces rely on comput…
Graphlets correct for the topological information missed by random walks
Sam F. L. Windels, Noel Malod-Dognin, Natasa Przulj
Random walks are widely used for mining networks due to the computational efficiency of computing them. For instance, graph representation learning learns a d-dimensional embedding…
Simplicity within biological complexity
Natasa Przulj, Noel Malod-Dognin
Heterogeneous, interconnected, systems-level, molecular data have become increasingly available and key in precision medicine. We need to utilize them to better stratify patients i…
Drugst.One -- A plug-and-play solution for online systems medicine and network-based drug repurposing
Andreas Maier, Michael Hartung, Mark Abovsky +36
In recent decades, the development of new drugs has become increasingly expensive and inefficient, and the molecular mechanisms of most pharmaceuticals remain poorly understood. In…
Unveiling new disease, pathway, and gene associations via multi-scale neural networks
Thomas Gaudelet, Noel Malod-Dognin, Jon Sanchez-Valle +3
Diseases involve complex processes and modifications to the cellular machinery. The gene expression profile of the affected cells contains characteristic patterns linked to a disea…