Alistair S. Dunham
A5077383030- SARS-CoV-2 and COVID-19 Research
- Machine Learning in Bioinformatics
- Bioinformatics and Genomic Networks
- Genomics and Phylogenetic Studies
- Protein Structure and Dynamics
- Computational Drug Discovery Methods
- interferon and immune responses
- Genomics and Rare Diseases
- Evolution and Genetic Dynamics
- Fungal and yeast genetics research
- Microbial Metabolic Engineering and Bioproduction
- RNA and protein synthesis mechanisms
- Enzyme Structure and Function
- Genetic diversity and population structure
- vaccines and immunoinformatics approaches
- Fermentation and Sensory Analysis
- Mosquito-borne diseases and control
- Biomedical Text Mining and Ontologies
- SARS-CoV-2 detection and testing
- Molecular Biology Techniques and Applications
- CRISPR and Genetic Engineering
- Chromosomal and Genetic Variations
- COVID-19 epidemiological studies
- COVID-19 Clinical Research Studies
- Plant Gene Expression Analysis
Wellcome Sanger Institute
2019-2024
European Bioinformatics Institute
2018-2023
Saffron Walden Museum
2022
Utrecht University
2021
University of Washington
2021
Stockholm University
2021
University of Kansas
2021
ETH Zurich
2021
Science for Life Laboratory
2021
Wellcome Trust
2018-2019
The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a grave threat to public health and the global economy. SARS-CoV-2 closely related more lethal but less transmissible coronaviruses SARS-CoV-1 Middle East (MERS-CoV). Here, we have carried out comparative viral-human protein-protein interaction viral protein localization analyses for all three viruses. Subsequent functional genetic screening identified host factors that functionally impinge on...
Most proteins fold into 3D structures that determine how they function and orchestrate the biological processes of cell. Recent developments in computational methods for protein structure predictions have reached accuracy experimentally determined models. Although this has been independently verified, implementation these across structural-biology applications remains to be tested. Here, we evaluate use AlphaFold2 (AF2) study characteristic structural elements; impact missense variants;...
Abstract Cellular functions are governed by molecular machines that assemble through protein-protein interactions. Their atomic details critical to studying their mechanisms. However, fewer than 5% of hundreds thousands human protein interactions have been structurally characterized. Here we test the potential and limitations recent progress in deep-learning methods using AlphaFold2 predict structures for 65,484 We show experiments can orthogonally confirm higher-confidence models. identify...
Abstract Most proteins fold into 3D structures that determine how they function and orchestrate the biological processes of cell. Recent developments in computational methods have led to protein structure predictions reached accuracy experimentally determined models. While this has been independently verified, implementation these across structural biology applications remains be tested. Here, we evaluate use AlphaFold 2 (AF2) study characteristic elements; impact missense variants; ligand...
Structural variants contribute substantially to genetic diversity and are important evolutionarily medically, but they still understudied. Here we present a comprehensive analysis of structural variation in the Human Genome Diversity panel, high-coverage dataset 911 samples from 54 diverse worldwide populations. We identify, total, 126,018 variants, 78% which were not identified previous global sequencing projects. Some reach high frequency private continental groups or even individual...
Understanding coding mutations is important for many applications in biology and medicine but the vast mutation space makes comprehensive experimental characterisation impossible. Current predictors are often computationally intensive difficult to scale, including recent deep learning models. We introduce Sequence UNET, a highly scalable architecture that classifies predicts variant frequency from sequence alone using multi-scale representations fully convolutional compression/expansion...
Article9 December 2019Open Access Transparent process The impact of the genetic background on gene deletion phenotypes in Saccharomyces cerevisiae Marco Galardini orcid.org/0000-0003-2018-8242 European Molecular Biology Laboratory, Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK Search for more papers by this author Bede P Busby orcid.org/0000-0003-3410-9998 Unit, Heidelberg, Germany Cristina Vieitez Alistair S Dunham Athanasios Typas Corresponding Author...
Abstract All cellular functions are governed by complex molecular machines that assemble through protein-protein interactions. Their atomic details critical to the study of their mechanisms but fewer than 5% hundreds thousands human interactions have been structurally characterized. Here, we test potential and limitations recent progress in deep-learning methods using AlphaFold2 predict structures for 65,484 We show higher confidence models enriched supported affinity or structure-based can...
ABSTRACT A series of SARS-CoV-2 variants concern (VOCs) have evolved in humans during the COVID-19 pandemic—Alpha, Beta, Gamma, Delta, and Omicron. Here, we used global proteomic genomic analyses infection to understand molecular responses driving VOC evolution. We discovered VOC-specific differences viral RNA protein expression levels, including for N, Orf6, Orf9b, pinpointed several mutations responsible. An analysis host response comprehensive interrogation altered virus-host...
Abstract A broad range of approaches have considered the challenge inferring selection from time-resolved genome sequence data. Models describing deterministic changes in allele or haplotype frequency been highlighted as providing accurate and computationally...
More transmissible SARS-CoV-2 variants of concern (VOCs) emerged during the COVID-19 pandemic. Here, we used global proteomic and genomic approaches to study host responses driving VOC evolution. We discovered VOCs evolved convergent strategies remodel response by modulating viral RNA protein levels, altering nucleocapsid phosphorylation, rewiring virus-host protein-protein interactions. Integrative systems analysis revealed that although Alpha, Beta, Gamma, Delta ultimately converged in...
Abstract Amino acids fulfil a diverse range of roles in proteins, each utilising its chemical properties different ways contexts to create required functions. For example, cysteines form disulphide or hydrogen bonds circumstances and charged amino do not always make use their charge. The repertoire acid functions the frequency at which they occur proteins remains understudied. Measuring large numbers mutational consequences, can elucidate role an plays, was prohibitively time consuming until...
Abstract Loss-of-function (LoF) mutations associated with disease don’t manifest equally in different individuals, a phenomenon known as incomplete penetrance. The impact of the genetic background on penetrance remains poorly characterized. Here, we systematically assessed changes gene deletion phenotypes for 3,786 knockouts four Saccharomyces cerevisiae strains and 38 conditions. We observed 16% to 42% changing between pairs small fraction conserved all strains. Conditions causing higher WT...
Abstract The COVID19 pandemic is a global crisis severely impacting many people across the world. An important part of response monitoring viral variants and determining impact they have on properties, such as infectivity, disease severity interactions with drugs vaccines. In this work we generate make available computational variant effect predictions for all possible single amino-acid substitutions to SARS-CoV-2 in order complement facilitate experiments expert analysis. resulting dataset...
Abstract All cellular functions are governed by complex molecular machines that assemble through protein-protein interactions. Their atomic details critical to the study of their mechanisms but fewer than 5% hundreds thousands human interactions have been structurally characterized. Here, we test potential and limitations recent progress in deep-learning methods using AlphaFold2 predict structures for 65,484 We show higher confidence models enriched supported affinity or structure based can...
Abstract Understanding the consequences of protein coding mutations is important for many applications in biology and medicine. The vast number possible across species makes comprehensive experimental characterisation impossible, even with recent high-throughput techniques, which means computationally predicting variation essential analyses. Previous variant effect prediction (VEP) tools, generally based on evolutionary conservation structure, are often intensive, making them difficult to...
Population-scale resources of genetic, molecular, and cellular information form the basis for understanding human genomes, charting heritable disease, tracing effects mutations. Pooled perturbation assays applied to models, probing effect many perturbations coupled with an scRNA-seq readout (Perturb-seq), are especially potent references interpreting disease-linked mutations or gene expression changes. However, utility existing maps has been limited by comprehensiveness possible, relevance...
Abstract Structural variants contribute substantially to genetic diversity and are important evolutionarily medically, yet still understudied. Here, we present a comprehensive analysis of deletions, duplications, insertions, inversions non-reference unique insertions in the Human Genome Diversity Project (HGDP-CEPH) panel, high-coverage dataset 911 samples from 54 diverse worldwide populations. We identify total 126,018 structural (25,588 <100 bp size), which 78% novel. Some reach high...
ABSTRACT A common challenge arising from the observation of an evolutionary system over time is to infer magnitude selection acting upon a specific genetic variant, or variants, within population. The inference may be confounded by effects drift in system, leading development procedures account for these effects. However, recent work has suggested that deterministic models evolution effective capturing even under complex demography, suggesting more general application approaches inference....