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, Genetic association, Single-nucleotide polymorphism and Genetic architecture.
His Genome-wide association study research integrates issues from Internal medicine, Blood pressure, Kidney disease, Bioinformatics and Allele.
His study in Internal medicine is interdisciplinary in nature, drawing from both Diabetes mellitus and Type 2 diabetes.
As part of his studies on Genetics, he frequently links adjacent subjects like Case-control study.
In his research, Body mass index and CDKAL1 is intimately related to Obesity, which falls under the overarching field of Single-nucleotide polymorphism.
Xueling Sim has researched Genetic architecture in several fields, including Imputation and Medical genetics.
His most cited work include:
- Biological, clinical and population relevance of 95 loci for blood lipids (2804 citations)
- Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk (1543 citations)
- Novel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries (799 citations)
What are the main themes of his work throughout his whole career to date?
Genetics, Genome-wide association study, Genetic association, Single-nucleotide polymorphism and Type 2 diabetes are his primary areas of study.
His research integrates issues of Polymorphism, Linkage disequilibrium, Allele frequency, Medical genetics and Internal medicine in his study of Genome-wide association study.
His biological study spans a wide range of topics, including Case-control study and Macular degeneration.
His study explores the link between Genetic association and topics such as Imputation that cross with problems in 1000 Genomes Project and Evolutionary biology.
He combines subjects such as Genotyping, Obesity, Genetic variation and Blood pressure with his study of Single-nucleotide polymorphism.
His Type 2 diabetes research is multidisciplinary, incorporating perspectives in Susceptibility locus and Bioinformatics.
He most often published in these fields:
- Genetics (70.05%)
- Genome-wide association study (68.02%)
- Genetic association (39.09%)
What were the highlights of his more recent work (between 2017-2021)?
- Genetics (70.05%)
- Genome-wide association study (68.02%)
- Type 2 diabetes (21.83%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Genetics, Genome-wide association study, Type 2 diabetes, Internal medicine and Gene.
His research in Genetics tackles topics such as Blood pressure which are related to areas like Meta-analysis and Genome.
Genome-wide association study is a subfield of Single-nucleotide polymorphism that he explores.
His studies in Single-nucleotide polymorphism integrate themes in fields like Refractive error and Candidate gene.
His Type 2 diabetes study integrates concerns from other disciplines, such as Kidney disease and Bioinformatics.
His Medical genetics course of study focuses on Genetic architecture and Polymorphism and Risk factor.
Between 2017 and 2021, his most popular works were:
- Novel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries (799 citations)
- Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps. (503 citations)
- Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity (145 citations)
In his most recent research, the most cited papers focused on:
- Gene
- Internal medicine
- Genetics
Xueling Sim mainly investigates Genome-wide association study, Genetics, Medical genetics, Allele frequency and Allele.
His research on Genome-wide association study concerns the broader Single-nucleotide polymorphism.
Xueling Sim has included themes like Blood lipids, Cholesterol, Blood pressure and Lipid metabolism in his Genetics study.
His work deals with themes such as SNP, Triglyceride and Genotype, which intersect with Blood lipids.
The study incorporates disciplines such as Imputation, Human genetics and Genetic architecture in addition to Medical genetics.
His biological study deals with issues like Expression quantitative trait loci, which deal with fields such as Pedigree chart.
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