Graph representation learning in biomedicine and healthcare
Networks—or graphs—are universal descriptors of systems of interacting elements. In
biomedicine and healthcare, they can represent, for example, molecular interactions …
biomedicine and healthcare, they can represent, for example, molecular interactions …
Network pharmacology: curing causal mechanisms instead of treating symptoms
For complex diseases, most drugs are highly ineffective, and the success rate of drug
discovery is in constant decline. While low quality, reproducibility issues, and translational …
discovery is in constant decline. While low quality, reproducibility issues, and translational …
Building a knowledge graph to enable precision medicine
Developing personalized diagnostic strategies and targeted treatments requires a deep
understanding of disease biology and the ability to dissect the relationship between …
understanding of disease biology and the ability to dissect the relationship between …
COVID-19 and cardiovascular disease: from bench to bedside
A pandemic of historic impact, coronavirus disease 2019 (COVID-19) has potential
consequences on the cardiovascular health of millions of people who survive infection …
consequences on the cardiovascular health of millions of people who survive infection …
Network-based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2
Human coronaviruses (HCoVs), including severe acute respiratory syndrome coronavirus
(SARS-CoV) and 2019 novel coronavirus (2019-nCoV, also known as SARS-CoV-2), lead …
(SARS-CoV) and 2019 novel coronavirus (2019-nCoV, also known as SARS-CoV-2), lead …
Artificial intelligence in cancer target identification and drug discovery
Artificial intelligence is an advanced method to identify novel anticancer targets and discover
novel drugs from biology networks because the networks can effectively preserve and …
novel drugs from biology networks because the networks can effectively preserve and …
[HTML][HTML] Dual proteome-scale networks reveal cell-specific remodeling of the human interactome
Thousands of interactions assemble proteins into modules that impart spatial and functional
organization to the cellular proteome. Through affinity-purification mass spectrometry, we …
organization to the cellular proteome. Through affinity-purification mass spectrometry, we …
Network-based machine learning approach to predict immunotherapy response in cancer patients
Immune checkpoint inhibitors (ICIs) have substantially improved the survival of cancer
patients over the past several years. However, only a minority of patients respond to ICI …
patients over the past several years. However, only a minority of patients respond to ICI …
Diffusion improves graph learning
J Gasteiger, S Weißenberger… - Advances in neural …, 2019 - proceedings.neurips.cc
Graph convolution is the core of most Graph Neural Networks (GNNs) and usually
approximated by message passing between direct (one-hop) neighbors. In this work, we …
approximated by message passing between direct (one-hop) neighbors. In this work, we …
Network medicine framework for identifying drug-repurposing opportunities for COVID-19
D Morselli Gysi, Í Do Valle, M Zitnik… - Proceedings of the …, 2021 - National Acad Sciences
The COVID-19 pandemic has highlighted the need to quickly and reliably prioritize clinically
approved compounds for their potential effectiveness for severe acute respiratory syndrome …
approved compounds for their potential effectiveness for severe acute respiratory syndrome …