Filter By:

Journal Check one or more journals to show results from those journals only.

Choose more journals

Article type Check one or more article types to show results from those article types only.
Subject Check one or more subjects to show results from those subjects only.
Date Choose a date option to show results from those dates only.

Custom date range

Clear all filters
Sort by:
Showing 1–50 of 496 results
Advanced filters: Author: Andrew Warren Clear advanced filters
  • An analysis of 24,202 critical cases of COVID-19 identifies potentially druggable targets in inflammatory signalling (JAK1), monocyte–macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).

    • Erola Pairo-Castineira
    • Konrad Rawlik
    • J. Kenneth Baillie
    ResearchOpen Access
    Nature
    Volume: 617, P: 764-768
  • High and medium-entropy alloys have shown excellent mechanical performance, yet the role of short-range order (SRO) on these properties has been unclear. Here, the authors demonstrate that the reduction of SRO by deformation leads to rejuvenation, explaining their remarkable damage tolerance.

    • Yang Yang
    • Sheng Yin
    • Andrew M. Minor
    ResearchOpen Access
    Nature Communications
    Volume: 15, P: 1-9
  • The 4D Nucleome Project demonstrates the use of genomic assays and computational methods to measure genome folding and then predict genomic structure from DNA sequence, facilitating the discovery of potential effects of genetic variants, including variants associated with disease, on genome structure and function.

    • Job Dekker
    • Betul Akgol Oksuz
    • Feng Yue
    ResearchOpen Access
    Nature
    Volume: 649, P: 759-776
  • Pulmonary type 2 inflammation is associated with type 2 innate lymphoid cells. Here the authors use the Collaborative Cross mouse panel to show that ILC2 abundance during type 2 lung inflammation is different across the panel and identify free-fatty acid receptor 3 (Ffar3) as a gene responsible and show cytokine and ILC2 functional changes.

    • Mark Rusznak
    • Shinji Toki
    • R. Stokes Peebles Jr
    ResearchOpen Access
    Nature Communications
    Volume: 17, P: 1-23
  • A global network of researchers was formed to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity; this paper reports 13 genome-wide significant loci and potentially actionable mechanisms in response to infection.

    • Mari E. K. Niemi
    • Juha Karjalainen
    • Chloe Donohue
    ResearchOpen Access
    Nature
    Volume: 600, P: 472-477
  • The flagship paper of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium describes the generation of the integrative analyses of 2,658 cancer whole genomes and their matching normal tissues across 38 tumour types, the structures for international data sharing and standardized analyses, and the main scientific findings from across the consortium studies.

    • Lauri A. Aaltonen
    • Federico Abascal
    • Christian von Mering
    ResearchOpen Access
    Nature
    Volume: 578, P: 82-93
  • A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants.

    • Loïc Yengo
    • Sailaja Vedantam
    • Joel N. Hirschhorn
    ResearchOpen Access
    Nature
    Volume: 610, P: 704-712
  • Patricia Munroe, Christopher Newton-Cheh, Andrew Morris and colleagues perform association studies in over 340,000 individuals of European ancestry and identify 66 loci, of which 17 are novel, involved in blood pressure regulation. The risk SNPs are enriched for cis-regulatory elements, particularly in vascular endothelial cells.

    • Georg B Ehret
    • Teresa Ferreira
    • Patricia B Munroe
    Research
    Nature Genetics
    Volume: 48, P: 1171-1184
  • There’s an emerging body of evidence to show how biological sex impacts cancer incidence, treatment and underlying biology. Here, using a large pan-cancer dataset, the authors further highlight how sex differences shape the cancer genome.

    • Constance H. Li
    • Stephenie D. Prokopec
    • Christian von Mering
    ResearchOpen Access
    Nature Communications
    Volume: 11, P: 1-24
  • Analyses of 2,658 whole genomes across 38 types of cancer identify the contribution of non-coding point mutations and structural variants to driving cancer.

    • Esther Rheinbay
    • Morten Muhlig Nielsen
    • Christian von Mering
    ResearchOpen Access
    Nature
    Volume: 578, P: 102-111
  • In somatic cells the mechanisms maintaining the chromosome ends are normally inactivated; however, cancer cells can re-activate these pathways to support continuous growth. Here, the authors characterize the telomeric landscapes across tumour types and identify genomic alterations associated with different telomere maintenance mechanisms.

    • Lina Sieverling
    • Chen Hong
    • Christian von Mering
    ResearchOpen Access
    Nature Communications
    Volume: 11, P: 1-13
  • With the generation of large pan-cancer whole-exome and whole-genome sequencing projects, a question remains about how comparable these datasets are. Here, using The Cancer Genome Atlas samples analysed as part of the Pan-Cancer Analysis of Whole Genomes project, the authors explore the concordance of mutations called by whole exome sequencing and whole genome sequencing techniques.

    • Matthew H. Bailey
    • William U. Meyerson
    • Christian von Mering
    ResearchOpen Access
    Nature Communications
    Volume: 11, P: 1-27
  • Whole-genome sequencing data from more than 2,500 cancers of 38 tumour types reveal 16 signatures that can be used to classify somatic structural variants, highlighting the diversity of genomic rearrangements in cancer.

    • Yilong Li
    • Nicola D. Roberts
    • Christian von Mering
    ResearchOpen Access
    Nature
    Volume: 578, P: 112-121
  • Some cancer patients first present with metastases where the location of the primary is unidentified; these are difficult to treat. In this study, using machine learning, the authors develop a method to determine the tissue of origin of a cancer based on whole sequencing data.

    • Wei Jiao
    • Gurnit Atwal
    • Christian von Mering
    ResearchOpen Access
    Nature Communications
    Volume: 11, P: 1-12
  • In this study the authors consider the structural variants (SVs) present within cancer cases of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. They report hundreds of genes, including known cancer-associated genes for which the nearby presence of a SV breakpoint is associated with altered expression.

    • Yiqun Zhang
    • Fengju Chen
    • Christian von Mering
    ResearchOpen Access
    Nature Communications
    Volume: 11, P: 1-14
  • Mendelian randomization (MR) identifies causal relationships from observational data but has increased error rates when the genetic variants used as instruments come from a single region, a typical scenario when assessing molecular traits like protein or metabolite levels as risk factors. Here the authors introduce a single-region pleiotropy-robust MR method, validating the method on three ground truth sources, showing its capability to identify disease-causing molecular traits.

    • Adriaan van der Graaf
    • Robert Warmerdam
    • Zoltán Kutalik
    ResearchOpen Access
    Nature Communications
    Volume: 16, P: 1-19
  • A genome-wide association meta-analysis study of blood lipid levels in roughly 1.6 million individuals demonstrates the gain of power attained when diverse ancestries are included to improve fine-mapping and polygenic score generation, with gains in locus discovery related to sample size.

    • Sarah E. Graham
    • Shoa L. Clarke
    • Cristen J. Willer
    Research
    Nature
    Volume: 600, P: 675-679
  • Whole-genome sequencing, transcriptome-wide association and fine-mapping analyses in over 7,000 individuals with critical COVID-19 are used to identify 16 independent variants that are associated with severe illness in COVID-19.

    • Athanasios Kousathanas
    • Erola Pairo-Castineira
    • J. Kenneth Baillie
    ResearchOpen Access
    Nature
    Volume: 607, P: 97-103
  • Experimental demonstration of quantum speedup that scales with the system size is the goal of near-term quantum computing. Here, the authors demonstrate such scaling advantage for a D-Wave quantum annealer over analogous classical algorithms in simulations of frustrated quantum magnets.

    • Andrew D. King
    • Jack Raymond
    • Mohammad H. Amin
    ResearchOpen Access
    Nature Communications
    Volume: 12, P: 1-6
  • Understanding deregulation of biological pathways in cancer can provide insight into disease etiology and potential therapies. Here, as part of the PanCancer Analysis of Whole Genomes (PCAWG) consortium, the authors present pathway and network analysis of 2583 whole cancer genomes from 27 tumour types.

    • Matthew A. Reyna
    • David Haan
    • Christian von Mering
    ResearchOpen Access
    Nature Communications
    Volume: 11, P: 1-17
  • Integrative analyses of transcriptome and whole-genome sequencing data for 1,188 tumours across 27 types of cancer are used to provide a comprehensive catalogue of RNA-level alterations in cancer.

    • Claudia Calabrese
    • Natalie R. Davidson
    • Christian von Mering
    ResearchOpen Access
    Nature
    Volume: 578, P: 129-136
  • Viral pathogen load in cancer genomes is estimated through analysis of sequencing data from 2,656 tumors across 35 cancer types using multiple pathogen-detection pipelines, identifying viruses in 382 genomic and 68 transcriptome datasets.

    • Marc Zapatka
    • Ivan Borozan
    • Christian von Mering
    ResearchOpen Access
    Nature Genetics
    Volume: 52, P: 320-330
  • Analysis of cancer genome sequencing data has enabled the discovery of driver mutations. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium the authors present DriverPower, a software package that identifies coding and non-coding driver mutations within cancer whole genomes via consideration of mutational burden and functional impact evidence.

    • Shimin Shuai
    • Federico Abascal
    • Christian von Mering
    ResearchOpen Access
    Nature Communications
    Volume: 11, P: 1-12
  • Hexacoordinate silicon is seen often in molecular compounds, but very rarely in crystalline silicate materials. Now, reversible Si–O chemistry has been used to assemble octahedral dianionic SiO6 building units and anthracene derivatives into crystalline microporous silicate organic frameworks that share characteristics of both covalent organic frameworks and inorganic zeolites.

    • Jérôme Roeser
    • Dragica Prill
    • Arne Thomas
    Research
    Nature Chemistry
    Volume: 9, P: 977-982
  • Whole-genome sequencing data for 2,778 cancer samples from 2,658 unique donors across 38 cancer types is used to reconstruct the evolutionary history of cancer, revealing that driver mutations can precede diagnosis by several years to decades.

    • Moritz Gerstung
    • Clemency Jolly
    • Christian von Mering
    ResearchOpen Access
    Nature
    Volume: 578, P: 122-128
  • The authors present SVclone, a computational method for inferring the cancer cell fraction of structural variants from whole-genome sequencing data.

    • Marek Cmero
    • Ke Yuan
    • Christian von Mering
    ResearchOpen Access
    Nature Communications
    Volume: 11, P: 1-15
  • Many tumours exhibit hypoxia (low oxygen) and hypoxic tumours often respond poorly to therapy. Here, the authors quantify hypoxia in 1188 tumours from 27 cancer types, showing elevated hypoxia links to increased mutational load, directing evolutionary trajectories.

    • Vinayak Bhandari
    • Constance H. Li
    • Christian von Mering
    ResearchOpen Access
    Nature Communications
    Volume: 11, P: 1-10
  • Multi-omics datasets pose major challenges to data interpretation and hypothesis generation owing to their high-dimensional molecular profiles. Here, the authors develop ActivePathways method, which uses data fusion techniques for integrative pathway analysis of multi-omics data and candidate gene discovery.

    • Marta Paczkowska
    • Jonathan Barenboim
    • Christian von Mering
    ResearchOpen Access
    Nature Communications
    Volume: 11, P: 1-16