Ross Lazarus

What is he best known for?

The fields of study he is best known for:

• Internal medicine
• Gene
• Statistics

Ross Lazarus spends much of his time researching Single-nucleotide polymorphism, Genetics, Internal medicine, Linkage disequilibrium and Data science. His studies deal with areas such as Asthma, Immunology, Haplotype and Cohort as well as Single-nucleotide polymorphism. Within one scientific family, Ross Lazarus focuses on topics pertaining to Endocrinology under Internal medicine, and may sometimes address concerns connected to FEV1/FVC ratio.

His studies examine the connections between Linkage disequilibrium and genetics, as well as such issues in Genome-wide association study, with regards to Genetic determinism, Methylenetetrahydrofolate reductase, Vitamin B12 and Homocysteine. His work on Web service expands to the thematically related Data science. His research on SNP frequently links to adjacent areas such as Bioinformatics.

His most cited work include:

• Galaxy: A Web‐Based Genome Analysis Tool for Experimentalists (1199 citations)
• Galaxy: A Web‐Based Genome Analysis Tool for Experimentalists (1199 citations)
• Predicting Flu Trends using Twitter data (324 citations)

What are the main themes of his work throughout his whole career to date?

His primary areas of study are Genetics, Single-nucleotide polymorphism, Immunology, Asthma and Internal medicine. His study in Genetic variation, Genome-wide association study, Allele frequency, Genotype and Gene falls under the purview of Genetics. His research integrates issues of Haplotype and Candidate gene in his study of Single-nucleotide polymorphism.

As part of one scientific family, Ross Lazarus deals mainly with the area of Immunology, narrowing it down to issues related to the Intensive care, and often Respiratory disease. Many of his studies on Asthma apply to Pharmacogenetics as well. His Internal medicine study deals with Endocrinology intersecting with FEV1/FVC ratio and Vital capacity.

He most often published in these fields:

• Genetics (25.76%)
• Single-nucleotide polymorphism (23.74%)
• Immunology (23.74%)

What were the highlights of his more recent work (between 2010-2020)?

• Transcriptome (8.08%)
• Gene expression (9.09%)
• Genetics (25.76%)

In recent papers he was focusing on the following fields of study:

Transcriptome, Gene expression, Genetics, Cell biology and Internal medicine are his primary areas of study. His Transcriptome study incorporates themes from Inflammation, Immunology, Endurance training, Skeletal muscle and Innate immune system. His Immunology research is multidisciplinary, incorporating perspectives in Pharmacogenetics and Single-nucleotide polymorphism.

His Genetics study frequently links to adjacent areas such as Computational biology. His work in Internal medicine covers topics such as Endocrinology which are related to areas like Respiratory burst. While the research belongs to areas of Leukocyte migration, Ross Lazarus spends his time largely on the problem of Bioinformatics, intersecting his research to questions surrounding Gene.

Between 2010 and 2020, his most popular works were:

• Predicting Flu Trends using Twitter data (324 citations)
• Genomewide association between GLCCI1 and response to glucocorticoid therapy in asthma (280 citations)
• Automated Detection and Classification of Type 1 Versus Type 2 Diabetes Using Electronic Health Record Data (101 citations)

In his most recent research, the most cited papers focused on:

• Internal medicine
• Gene
• Statistics

His primary areas of investigation include Gene expression, Cell biology, Transcriptome, Gene and Genotype. His research in Gene expression intersects with topics in RNA and Replicate. His Cell biology research is multidisciplinary, relying on both Proinflammatory cytokine and Receptor, Innate immune system.

His Transcriptome research incorporates themes from Immune system, Immunology and Endurance training. His work is connected to SNP, Linkage disequilibrium, Pharmacogenetics and Single-nucleotide polymorphism, as a part of Genotype. His study connects Bioinformatics and SNP.