Scalable functional assays for the interpretation of human genetic variation

D Tabet, V Parikh, P Mali, FP Roth… - Annual Review of …, 2022 - annualreviews.org
Scalable sequence–function studies have enabled the systematic analysis and cataloging of
hundreds of thousands of coding and noncoding genetic variants in the human genome …

Multiplexed assays of variant effects contribute to a growing genotype–phenotype atlas

J Weile, FP Roth - Human genetics, 2018 - Springer
Given the constantly improving cost and speed of genome sequencing, it is reasonable to
expect that personal genomes will soon be known for many millions of humans. This stands …

Language models enable zero-shot prediction of the effects of mutations on protein function

J Meier, R Rao, R Verkuil, J Liu… - Advances in neural …, 2021 - proceedings.neurips.cc
Modeling the effect of sequence variation on function is a fundamental problem for
understanding and designing proteins. Since evolution encodes information about function …

Proteingym: Large-scale benchmarks for protein fitness prediction and design

P Notin, A Kollasch, D Ritter… - Advances in …, 2024 - proceedings.neurips.cc
Predicting the effects of mutations in proteins is critical to many applications, from
understanding genetic disease to designing novel proteins to address our most pressing …

Deep generative models of genetic variation capture the effects of mutations

AJ Riesselman, JB Ingraham, DS Marks - Nature methods, 2018 - nature.com
The functions of proteins and RNAs are defined by the collective interactions of many
residues, and yet most statistical models of biological sequences consider sites nearly …

MaveDB: an open-source platform to distribute and interpret data from multiplexed assays of variant effect

D Esposito, J Weile, J Shendure, LM Starita… - Genome biology, 2019 - Springer
Multiplex assays of variant effect (MAVEs), such as deep mutational scans and massively
parallel reporter assays, test thousands of sequence variants in a single experiment. Despite …

Protein language-model embeddings for fast, accurate, and alignment-free protein structure prediction

K Weissenow, M Heinzinger, B Rost - Structure, 2022 - cell.com
Advanced protein structure prediction requires evolutionary information from multiple
sequence alignments (MSAs) from evolutionary couplings that are not always available …

Inferring protein 3D structure from deep mutation scans

NJ Rollins, KP Brock, FJ Poelwijk, MA Stiffler… - Nature …, 2019 - nature.com
We describe an experimental method of three-dimensional (3D) structure determination that
exploits the increasing ease of high-throughput mutational scans. Inspired by the success of …

Scientific utopia III: Crowdsourcing science

EL Uhlmann, CR Ebersole… - Perspectives on …, 2019 - journals.sagepub.com
Most scientific research is conducted by small teams of investigators who together formulate
hypotheses, collect data, conduct analyses, and report novel findings. These teams operate …

A statistical framework for analyzing deep mutational scanning data

AF Rubin, H Gelman, N Lucas, SM Bajjalieh… - Genome biology, 2017 - Springer
Deep mutational scanning is a widely used method for multiplex measurement of functional
consequences of protein variants. We developed a new deep mutational scanning statistical …