What is he best known for?
The fields of study he is best known for:
- Gene
- Internal medicine
- Genetics
His primary scientific interests are in Genome-wide association study, Genetics, Single-nucleotide polymorphism, Internal medicine and Genetic association.
The various areas that Sekar Kathiresan examines in his Genome-wide association study study include Coronary artery disease, Disease, Allele, Locus and Genetic architecture.
His studies deal with areas such as Cholesterol and Lipoprotein as well as Genetics.
His Single-nucleotide polymorphism research is multidisciplinary, incorporating elements of Quantitative trait locus, Body mass index, Genetic model and Genetic epidemiology.
His work carried out in the field of Internal medicine brings together such families of science as Endocrinology, Genotype and Cardiology.
His research in Genetic association intersects with topics in SNP and Genetic testing.
His most cited work include:
- Analysis of protein-coding genetic variation in 60,706 humans (6694 citations)
- Biological, clinical and population relevance of 95 loci for blood lipids (2804 citations)
- Genome-Wide Association Analysis Identifies Loci for Type 2 Diabetes and Triglyceride Levels (2462 citations)
What are the main themes of his work throughout his whole career to date?
Sekar Kathiresan mostly deals with Genetics, Internal medicine, Genome-wide association study, Single-nucleotide polymorphism and Endocrinology.
His work in Gene, Genetic variation, Locus, Exome and Allele is related to Genetics.
His study explores the link between Internal medicine and topics such as Cardiology that cross with problems in Framingham Risk Score.
His Genome-wide association study research incorporates elements of Bioinformatics, Quantitative trait locus, Genetic architecture, Disease and Genetic association.
His Genetic association study combines topics from a wide range of disciplines, such as Computational biology and Blood pressure.
His Coronary artery disease study combines topics in areas such as Multifunction cardiogram and Case-control study.
He most often published in these fields:
- Genetics (65.07%)
- Internal medicine (50.36%)
- Genome-wide association study (56.62%)
What were the highlights of his more recent work (between 2018-2021)?
- Internal medicine (50.36%)
- Genome-wide association study (56.62%)
- Disease (18.63%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Internal medicine, Genome-wide association study, Disease, Bioinformatics and Genetics.
His research integrates issues of Polygenic risk score, Endocrinology and Cardiology in his study of Internal medicine.
His Genome-wide association study research is multidisciplinary, incorporating perspectives in Genetic architecture, Genetic association and Genomics.
His Disease research includes themes of Endogamy, Consanguinity, Biobank and Founder effect.
His studies in Bioinformatics integrate themes in fields like Diabetes mellitus, Venous thromboembolism, Liver function and Fatty liver.
Sekar Kathiresan combines topics linked to Familial hypercholesterolemia with his work on Genetics.
Between 2018 and 2021, his most popular works were:
- Polygenic Prediction of Weight and Obesity Trajectories from Birth to Adulthood (202 citations)
- A structural variation reference for medical and population genetics (125 citations)
- A brief history of human disease genetics. (99 citations)
In his most recent research, the most cited papers focused on:
- Gene
- Internal medicine
- Genetics
His scientific interests lie mostly in Genome-wide association study, Genetics, Internal medicine, Genetic variation and Bioinformatics.
His Genome-wide association study study incorporates themes from Dna variants, Cardiomyopathy, Heart failure, Cause of death and Gene Discovery.
The various areas that Sekar Kathiresan examines in his Genetics study include Coronary artery disease and Familial hypercholesterolemia.
Sekar Kathiresan usually deals with Internal medicine and limits it to topics linked to Endocrinology and TM6SF2 and Liver disease.
His biological study spans a wide range of topics, including Computational biology, Case-control study and Human genetics.
His research investigates the connection between Bioinformatics and topics such as Disease that intersect with issues in Uterine cancer, Family history and Odds ratio.
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