What is she best known for?
The fields of study she is best known for:
Maria Martinez spends much of her time researching Genetics, Genome-wide association study, Genetic association, Single-nucleotide polymorphism and Meta-analysis.
Maria Martinez combines subjects such as Disease and Age of onset with her study of Genetics.
Her research on Genome-wide association study frequently links to adjacent areas such as LRRK2.
Her Genetic association research incorporates themes from Genetic heterogeneity and Heritability.
Her primary area of study in Single-nucleotide polymorphism is in the field of Imputation.
Her work in Meta-analysis addresses issues such as Parkinson's disease, which are connected to fields such as Computational biology.
Her most cited work include:
- Analysis of shared heritability in common disorders of the brain (726 citations)
- Analysis of shared heritability in common disorders of the brain (726 citations)
- Imputation of sequence variants for identification of genetic risks for Parkinson's disease: a meta-analysis of genome-wide association studies. (726 citations)
What are the main themes of her work throughout her whole career to date?
Maria Martinez mainly investigates Genetics, Genome-wide association study, Genetic association, Single-nucleotide polymorphism and Locus.
Her Genetics study is mostly concerned with Genetic linkage, Allele, Gene mapping, Candidate gene and Gene.
Maria Martinez interconnects LRRK2, Meta-analysis, Disease, Imputation and Genetic variation in the investigation of issues within Genome-wide association study.
Her Genetic association research includes themes of Quantitative trait locus, Comorbidity and Heritability.
Her Heritability study combines topics in areas such as Missing heritability problem and Genetic architecture.
Her study in Single-nucleotide polymorphism focuses on SNP in particular.
She most often published in these fields:
- Genetics (69.70%)
- Genome-wide association study (40.91%)
- Genetic association (32.58%)
What were the highlights of her more recent work (between 2013-2021)?
- Genome-wide association study (40.91%)
- Genetics (69.70%)
- Genetic association (32.58%)
In recent papers she was focusing on the following fields of study:
Maria Martinez mostly deals with Genome-wide association study, Genetics, Genetic association, Disease and Parkinson's disease.
Her studies in Genome-wide association study integrate themes in fields like Exome, Computational biology, Genetic variation and Candidate gene.
Her work on Single-nucleotide polymorphism, Gene, Genotyping and Molecular genetics as part of general Genetics study is frequently linked to HMG-CoA reductase, bridging the gap between disciplines.
Her work on SNP as part of general Single-nucleotide polymorphism research is often related to Plasma cell differentiation, thus linking different fields of science.
Her Genetic association research incorporates elements of Heritability, Linkage, Quantitative trait locus and Comorbidity.
The Parkinson's disease study which covers Meta-analysis that intersects with Mendelian inheritance.
Between 2013 and 2021, her most popular works were:
- Analysis of shared heritability in common disorders of the brain (726 citations)
- Analysis of shared heritability in common disorders of the brain (726 citations)
- Large-scale meta-analysis of genome-wide association data identifies six new risk loci for Parkinson’s disease (395 citations)
In her most recent research, the most cited papers focused on:
Her scientific interests lie mostly in Genome-wide association study, Genetic association, Parkinson's disease, Meta-analysis and Single-nucleotide polymorphism.
Her Genome-wide association study research is multidisciplinary, incorporating perspectives in Computational biology and Comorbidity.
Her multidisciplinary approach integrates Computational biology and Scale in her work.
Her Comorbidity study incorporates themes from Heritability, Genetic heterogeneity, Clinical psychology and Risk factor.
Maria Martinez conducted interdisciplinary study in her works that combined Risk factor and Bipolar disorder.
Her Single-nucleotide polymorphism study introduces a deeper knowledge of Genetics.
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