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 …
[HTML][HTML] Why digital medicine depends on interoperability
M Lehne, J Sass, A Essenwanger, J Schepers… - NPJ digital …, 2019 - nature.com
Digital data are anticipated to transform medicine. However, most of today's medical data
lack interoperability: hidden in isolated databases, incompatible systems and proprietary …
lack interoperability: hidden in isolated databases, incompatible systems and proprietary …
Graph neural networks: foundation, frontiers and applications
The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …
recent years. Graph neural networks, also known as deep learning on graphs, graph …
Whole-genome sequencing of patients with rare diseases in a national health system
Most patients with rare diseases do not receive a molecular diagnosis and the aetiological
variants and causative genes for more than half such disorders remain to be discovered …
variants and causative genes for more than half such disorders remain to be discovered …
[HTML][HTML] Generalisable long COVID subtypes: findings from the NIH N3C and RECOVER programmes
Background Stratification of patients with post-acute sequelae of SARS-CoV-2 infection
(PASC, or long COVID) would allow precision clinical management strategies. However …
(PASC, or long COVID) would allow precision clinical management strategies. However …
PhenoScore quantifies phenotypic variation for rare genetic diseases by combining facial analysis with other clinical features using a machine-learning framework
AJM Dingemans, M Hinne, KMG Truijen, L Goltstein… - Nature Genetics, 2023 - nature.com
Several molecular and phenotypic algorithms exist that establish genotype–phenotype
correlations, including facial recognition tools. However, no unified framework that …
correlations, including facial recognition tools. However, no unified framework that …
Expansion of the Human Phenotype Ontology (HPO) knowledge base and resources
Abstract The Human Phenotype Ontology (HPO)—a standardized vocabulary of phenotypic
abnormalities associated with 7000+ diseases—is used by thousands of researchers …
abnormalities associated with 7000+ diseases—is used by thousands of researchers …
[HTML][HTML] Massive mining of publicly available RNA-seq data from human and mouse
RNA sequencing (RNA-seq) is the leading technology for genome-wide transcript
quantification. However, publicly available RNA-seq data is currently provided mostly in raw …
quantification. However, publicly available RNA-seq data is currently provided mostly in raw …
Semantic similarity and machine learning with ontologies
Ontologies have long been employed in the life sciences to formally represent and reason
over domain knowledge and they are employed in almost every major biological database …
over domain knowledge and they are employed in almost every major biological database …
The human phenotype ontology in 2021
Abstract The Human Phenotype Ontology (HPO, https://hpo. jax. org) was launched in 2008
to provide a comprehensive logical standard to describe and computationally analyze …
to provide a comprehensive logical standard to describe and computationally analyze …