[HTML][HTML] A guide for the diagnosis of rare and undiagnosed disease: beyond the exome

S Marwaha, JW Knowles, EA Ashley - Genome medicine, 2022 - Springer
Rare diseases affect 30 million people in the USA and more than 300–400 million
worldwide, often causing chronic illness, disability, and premature death. Traditional …

Decoding disease: from genomes to networks to phenotypes

AK Wong, RSG Sealfon, CL Theesfeld… - Nature Reviews …, 2021 - nature.com
Interpreting the effects of genetic variants is key to understanding individual susceptibility to
disease and designing personalized therapeutic approaches. Modern experimental …

Disease variant prediction with deep generative models of evolutionary data

J Frazer, P Notin, M Dias, A Gomez, JK Min, K Brock… - Nature, 2021 - nature.com
Quantifying the pathogenicity of protein variants in human disease-related genes would
have a marked effect on clinical decisions, yet the overwhelming majority (over 98%) of …

[HTML][HTML] Genome-wide prediction of disease variant effects with a deep protein language model

N Brandes, G Goldman, CH Wang, CJ Ye, V Ntranos - Nature Genetics, 2023 - nature.com
Predicting the effects of coding variants is a major challenge. While recent deep-learning
models have improved variant effect prediction accuracy, they cannot analyze all coding …

[HTML][HTML] An Atlas of Variant Effects to understand the genome at nucleotide resolution

DM Fowler, DJ Adams, AL Gloyn, WC Hahn, DS Marks… - Genome Biology, 2023 - Springer
Sequencing has revealed hundreds of millions of human genetic variants, and continued
efforts will only add to this variant avalanche. Insufficient information exists to interpret the …

Deep-learning-enabled protein–protein interaction analysis for prediction of SARS-CoV-2 infectivity and variant evolution

G Wang, X Liu, K Wang, Y Gao, G Li… - Nature Medicine, 2023 - nature.com
Host–pathogen interactions and pathogen evolution are underpinned by protein–protein
interactions between viral and host proteins. An understanding of how viral variants affect …

[PDF][PDF] Improved pathogenicity prediction for rare human missense variants

Y Wu, H Liu, R Li, S Sun, J Weile, FP Roth - The American Journal of …, 2021 - cell.com
The success of personalized genomic medicine depends on our ability to assess the
pathogenicity of rare human variants, including the important class of missense variation …

[PDF][PDF] Predicting and interpreting large-scale mutagenesis data using analyses of protein stability and conservation

MH Høie, M Cagiada, AHB Frederiksen, A Stein… - Cell reports, 2022 - cell.com
Understanding and predicting the functional consequences of single amino acid changes is
central in many areas of protein science. Here, we collect and analyze experimental …

[HTML][HTML] Embeddings from protein language models predict conservation and variant effects

C Marquet, M Heinzinger, T Olenyi, C Dallago… - Human genetics, 2022 - Springer
The emergence of SARS-CoV-2 variants stressed the demand for tools allowing to interpret
the effect of single amino acid variants (SAVs) on protein function. While Deep Mutational …

Neural networks to learn protein sequence–function relationships from deep mutational scanning data

S Gelman, SA Fahlberg… - Proceedings of the …, 2021 - National Acad Sciences
The mapping from protein sequence to function is highly complex, making it challenging to
predict how sequence changes will affect a protein's behavior and properties. We present a …