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 …
Graph representation learning in biomedicine
Biomedical networks (or graphs) are universal descriptors for systems of interacting
elements, from molecular interactions and disease co-morbidity to healthcare systems and …
elements, from molecular interactions and disease co-morbidity to healthcare systems and …
Current and future directions in network biology
Network biology, an interdisciplinary field at the intersection of computational and biological
sciences, is critical for deepening understanding of cellular functioning and disease. While …
sciences, is critical for deepening understanding of cellular functioning and disease. While …
AAnet resolves a continuum of spatially-localized cell states to unveil tumor complexity
Identifying functionally important cell states and structure within a heterogeneous tumor
remains a significant biological and computational challenge. Moreover, current clustering …
remains a significant biological and computational challenge. Moreover, current clustering …
[PDF][PDF] Machine learning and large scale cancer omic data: decoding the biological mechanisms underpinning cancer
V Fanfani - 2022 - core.ac.uk
Many of the mechanisms underpinning cancer risk and tumorigenesis are still not fully
understood. However, the next-generation sequencing revolution and the rapid advances in …
understood. However, the next-generation sequencing revolution and the rapid advances in …