What is he best known for?
The fields of study he is best known for:
Michael Boehnke mostly deals with Genetics, Genome-wide association study, Genetic association, Single-nucleotide polymorphism and Internal medicine.
His studies deal with areas such as Body mass index and Glucose homeostasis as well as Genetics.
His Genome-wide association study research includes themes of Quantitative trait locus, Genetic architecture, Allele, Imputation and Type 2 diabetes.
He has researched Genetic association in several fields, including Bioinformatics, Blood pressure, Heritability, Computational biology and Genetic testing.
His Single-nucleotide polymorphism research incorporates elements of Human genome, Genetic variation and Copy-number variation.
His Internal medicine research integrates issues from Endocrinology and Cardiology.
His most cited work include:
- Analysis of protein-coding genetic variation in 60,706 humans (6694 citations)
- Finding the missing heritability of complex diseases. (6217 citations)
- The International HapMap Project (5051 citations)
What are the main themes of his work throughout his whole career to date?
Genetics, Genome-wide association study, Genetic association, Locus and Type 2 diabetes are his primary areas of study.
His study in Genetics focuses on Genetic linkage, Gene, Single-nucleotide polymorphism, Allele and Quantitative trait locus.
His studies in Genome-wide association study integrate themes in fields like Bioinformatics, Genetic variation, Expression quantitative trait loci, Computational biology and Genetic architecture.
His Computational biology research is multidisciplinary, incorporating perspectives in Meta-analysis and Genome.
His study in Genetic association is interdisciplinary in nature, drawing from both Imputation, Exome sequencing and Linkage disequilibrium.
His Type 2 diabetes research is multidisciplinary, relying on both Internal medicine, Insulin and Insulin resistance.
He most often published in these fields:
- Genetics (61.96%)
- Genome-wide association study (36.23%)
- Genetic association (21.74%)
What were the highlights of his more recent work (between 2018-2021)?
- Genome-wide association study (36.23%)
- Genetics (61.96%)
- Genetic association (21.74%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Genome-wide association study, Genetics, Genetic association, Gene and Computational biology.
His research in Genome-wide association study intersects with topics in Bipolar disorder, Meta-analysis, Disease, Locus and Genetic variation.
His Genetics and Expression quantitative trait loci, Exome sequencing, Quantitative trait locus, Genotype and Mendelian randomization investigations all form part of his Genetics research activities.
The concepts of his Genetic association study are interwoven with issues in Phenotype, Biobank and Haplotype.
His Gene research includes elements of Pulse pressure and Coding.
The various areas that Michael Boehnke examines in his Computational biology study include Type I and type II errors, Genome, Whole genome sequencing, Association test and Genetic architecture.
Between 2018 and 2021, his most popular works were:
- Genome-wide association study identifies 30 loci associated with bipolar disorder (518 citations)
- Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use (385 citations)
- Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program (143 citations)
In his most recent research, the most cited papers focused on:
Michael Boehnke spends much of his time researching Genetics, Genome-wide association study, Genetic association, Gene and Computational biology.
His research links Blood lipids with Genetics.
Michael Boehnke interconnects Schizophrenia, Meta-analysis, Quantitative trait locus, Expression quantitative trait loci and Heritability in the investigation of issues within Genome-wide association study.
Single-nucleotide polymorphism and Genotype is closely connected to Exome in his research, which is encompassed under the umbrella topic of Heritability.
His Computational biology research incorporates themes from Genome, Reference genome and Data visualization.
His study looks at the relationship between Genome and topics such as Genetic architecture, which overlap with Genetic variation.
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