scispace - formally typeset
A

Anna C. Need

Researcher at Imperial College London

Publications -  92
Citations -  11954

Anna C. Need is an academic researcher from Imperial College London. The author has contributed to research in topics: Genome-wide association study & Medicine. The author has an hindex of 43, co-authored 73 publications receiving 10623 citations. Previous affiliations of Anna C. Need include Queen Mary University of London & University College London.

Papers
More filters
Posted ContentDOI

Large-Scale cognitive GWAS Meta-analysis Reveals Tissue-Specific Neural Expression and Potential Nootopic Drug Targets

Max Lam, +65 more
- 16 Aug 2017 - 
TL;DR: The largest genome-wide association studies (GWAS) of cognitive ability to date are presented, and signal is enhanced by combining results with a large-scale GWAS of educational attainment.
Posted ContentDOI

Ninety-nine independent genetic loci influencing general cognitive function include genes associated with brain health and structure (N = 280,360)

Gail Davies, +221 more
- 17 Aug 2017 - 
TL;DR: Cognitive and genetic data from the CHARGE and COGENT consortia, and UK Biobank were combined to find 9,714 genome-wide significant SNPs, with significant genetic overlap between general cognitive function and information processing speed, as well as many health variables including longevity.
Journal ArticleDOI

Publisher Correction: Extensive identification of genes involved in congenital and structural heart disorders and cardiomyopathy

Nadine Spielmann, +246 more
TL;DR: In this paper , the authors used in vivo electrocardiography, transthoracic echocardiography and microcomputed tomography imaging to screen 3,894 single-gene-null mouse lines for structural and functional cardiac abnormalities, identifying 705 lines with cardiac arrhythmia, myocardial hypertrophy and ventricular dilation.

SVA: software for annotating and visualizing sequenced human

TL;DR: Sequence Variant Analyzer (SVA) as mentioned in this paper is a software tool that assigns a predicted biological function to variants identified in next-generation sequencing studies and provides a browser to visualize the variants in their genomic contexts.