What is he best known for?
The fields of study he is best known for:
- Gene
- Genetics
- Internal medicine
His primary scientific interests are in Genetics, Genome-wide association study, Genetic association, Single-nucleotide polymorphism and Human genome.
The concepts of his Genome-wide association study study are interwoven with issues in Internal medicine, Imputation, Computational biology, Type 2 diabetes and Genetic architecture.
His study in Genetic association is interdisciplinary in nature, drawing from both Body mass index, Genetic heterogeneity and Heritability.
As a part of the same scientific study, Gonçalo R. Abecasis usually deals with the Single-nucleotide polymorphism, concentrating on Case-control study and frequently concerns with Genotype and Macular degeneration.
His Human genome study integrates concerns from other disciplines, such as Genetic variation and Genomics.
His Genetic variation study also includes
- 1000 Genomes Project which is related to area like Exome sequencing, Genomic Structural Variation and Information retrieval,
- Human genetic variation together with Evolutionary biology,
- Deep sequencing, Genome resequencing, Population genomics, Reference genome and Variant Call Format most often made with reference to Exome.
His most cited work include:
- The Sequence Alignment/Map format and SAMtools (29524 citations)
- A global reference for human genetic variation. (7825 citations)
- A Map of Human Genome Variation From Population-Scale Sequencing (6302 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Genetics, Genome-wide association study, Genetic association, Single-nucleotide polymorphism and Gene.
Genetics is represented through his Locus, Genotype, Allele, Quantitative trait locus and Haplotype research.
The various areas that Gonçalo R. Abecasis examines in his Genome-wide association study study include Bioinformatics, Genetic variation, Internal medicine, Imputation and Computational biology.
His Computational biology research is multidisciplinary, relying on both Genome and Genomics.
His research in Genomics tackles topics such as 1000 Genomes Project which are related to areas like Exome sequencing.
His Genetic association research integrates issues from Linkage disequilibrium, Meta-analysis, Genotyping, Exome and Genetic architecture.
He most often published in these fields:
- Genetics (55.77%)
- Genome-wide association study (44.39%)
- Genetic association (25.75%)
What were the highlights of his more recent work (between 2017-2021)?
- Genome-wide association study (44.39%)
- Genetics (55.77%)
- Genetic association (25.75%)
In recent papers he was focusing on the following fields of study:
Gonçalo R. Abecasis spends much of his time researching Genome-wide association study, Genetics, Genetic association, Computational biology and Gene.
The Genome-wide association study study combines topics in areas such as Bioinformatics, Quantitative trait locus, Meta-analysis, Disease and Locus.
His Genetic variation, Genome, Single-nucleotide polymorphism, Medical genetics and Allele study are his primary interests in Genetics.
His study on Genetic association also encompasses disciplines like
- Biobank which is related to area like Sample and Statistics,
- Whole genome sequencing that connect with fields like Indel.
His Computational biology study incorporates themes from Allele frequency, Genomics, Imputation, DNA sequencing and Genetic architecture.
His studies deal with areas such as Biorepository and Medical diagnosis as well as Genomics.
Between 2017 and 2021, his most popular works were:
- Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps. (503 citations)
- Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence (403 citations)
- Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use (385 citations)
In his most recent research, the most cited papers focused on:
- Gene
- Internal medicine
- Genetics
Genome-wide association study, Genetics, Computational biology, Genetic association and Genotype are his primary areas of study.
His Genome-wide association study research is multidisciplinary, incorporating elements of Allele frequency, Medical genetics, Quantitative trait locus, Genetic architecture and Imputation.
His work deals with themes such as Meta-analysis and Cholesterol, which intersect with Genetics.
He interconnects Genome, Data visualization, MEDLINE and Statistical power in the investigation of issues within Computational biology.
He has researched Genetic association in several fields, including Sample, Data mining, Regression and Age of onset.
His Genotype study combines topics from a wide range of disciplines, such as Biobank, Blood lipids, Exome, Behavioural genetics and Neuroscience.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
