D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 59 Citations 23,546 240 World Ranking 2184 National Ranking 1188
Genetics D-index 73 Citations 29,374 284 World Ranking 1321 National Ranking 627

Research.com Recognitions

Awards & Achievements

2019 - Fellow of the International Society for Computational Biology

2009 - Fellow of Alfred P. Sloan Foundation

Overview

What is he best known for?

The fields of study he is best known for:

  • Gene
  • Statistics
  • Genetics

The scientist’s investigation covers issues in Genetics, Genome-wide association study, Quantitative trait locus, Artificial intelligence and Genetic association. Genetic variation, Gene, Inbred strain, Linkage disequilibrium and Genome are among the areas of Genetics where Eleazar Eskin concentrates his study. His Genome-wide association study study integrates concerns from other disciplines, such as Expression quantitative trait loci, Pairwise comparison, Heritability, Computational biology and Candidate gene.

Eleazar Eskin combines subjects such as Spurious relationship and Statistical hypothesis testing with his study of Quantitative trait locus. His Artificial intelligence research includes elements of Machine learning, Information retrieval and Pattern recognition. His biological study spans a wide range of topics, including False positive paradox and Principal component analysis.

His most cited work include:

  • Variance component model to account for sample structure in genome-wide association studies (1646 citations)
  • Efficient Control of Population Structure in Model Organism Association Mapping (1369 citations)
  • Assessing computational tools for the discovery of transcription factor binding sites. (1177 citations)

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

Eleazar Eskin focuses on Genetics, Computational biology, Genome-wide association study, Genetic association and Gene. Quantitative trait locus, Single-nucleotide polymorphism, Genome, Expression quantitative trait loci and Haplotype are among the areas of Genetics where the researcher is concentrating his efforts. He has researched Single-nucleotide polymorphism in several fields, including Genetic variation and Allele frequency.

His Computational biology research incorporates elements of RNA, Microbiome, Bioinformatics and Genomics. His Genome-wide association study research is multidisciplinary, relying on both Meta-analysis, Locus, Imputation, Multivariate normal distribution and Candidate gene. The Genetic association study combines topics in areas such as Association mapping, Linkage disequilibrium, Inbred strain and Statistical power.

He most often published in these fields:

  • Genetics (43.24%)
  • Computational biology (28.92%)
  • Genome-wide association study (24.32%)

What were the highlights of his more recent work (between 2016-2021)?

  • Computational biology (28.92%)
  • Genome-wide association study (24.32%)
  • Genetic association (19.46%)

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

His scientific interests lie mostly in Computational biology, Genome-wide association study, Genetic association, Genetics and Gene. His Computational biology research is multidisciplinary, incorporating perspectives in Microbiome, DNA methylation, RNA, Genomics and Epigenetics. His work carried out in the field of Genome-wide association study brings together such families of science as Phenotype, Statistical power, Quantitative trait locus, Imputation and Multivariate normal distribution.

His Quantitative trait locus study combines topics in areas such as Expression quantitative trait loci, Genetic variation and Heritability. His Genetic association study also includes fields such as

  • Linkage disequilibrium and Genetic correlation most often made with reference to Locus,
  • Context most often made with reference to Confounding. His Genetics study frequently draws connections between adjacent fields such as Covariate.

Between 2016 and 2021, his most popular works were:

  • Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics. (320 citations)
  • Using an atlas of gene regulation across 44 human tissues to inform complex disease- and trait-associated variation. (222 citations)
  • Loci associated with skin pigmentation identified in African populations (159 citations)

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

  • Gene
  • Statistics
  • Genetics

Eleazar Eskin mainly investigates Genetics, Genome-wide association study, Computational biology, Gene and Data science. His Genome-wide association study research integrates issues from Quantitative trait locus, Linkage disequilibrium and Functional genomics, Genomics. His studies deal with areas such as Expression quantitative trait loci, Genetic variation and Heritability as well as Quantitative trait locus.

His Linkage disequilibrium study deals with Genetic Pleiotropy intersecting with Data mining. His Computational biology research incorporates elements of Methylation, DNA methylation, RNA, Genetic association and Epigenetics. Eleazar Eskin interconnects Locus and Genetic architecture in the investigation of issues within Genetic association.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Variance component model to account for sample structure in genome-wide association studies

Hyun Min Kang;Jae Hoon Sul;Noah A. Zaitlen.
Nature Genetics (2010)

1974 Citations

Efficient Control of Population Structure in Model Organism Association Mapping

Hyun Min Kang;Noah A. Zaitlen;Claire M. Wade;Claire M. Wade;Andrew Kirby;Andrew Kirby.
Genetics (2008)

1752 Citations

Assessing computational tools for the discovery of transcription factor binding sites.

Martin Tompa;Nan Li;Timothy L. Bailey;George M. Church.
Nature Biotechnology (2005)

1576 Citations

Mouse genomic variation and its effect on phenotypes and gene regulation

T M Keane;L Goodstadt;P Danecek;M A White.
Nature (2011)

1466 Citations

Whole-Genome Patterns of Common DNA Variation in Three Human Populations

David A. Hinds;David A. Hinds;Laura L. Stuve;Laura L. Stuve;Geoffrey B. Nilsen;Geoffrey B. Nilsen;Eran Halperin;Eran Halperin.
Science (2005)

1441 Citations

A Geometric Framework for Unsupervised Anomaly Detection

Eleazar Eskin;Andrew Arnold;Michael J. Prerau;Leonid Portnoy.
Applications of Data Mining in Computer Security (2002)

1440 Citations

The spectrum kernel: a string kernel for SVM protein classification.

Christina S. Leslie;Eleazar Eskin;William Stafford Noble.
pacific symposium on biocomputing (2001)

1429 Citations

Data mining methods for detection of new malicious executables

M.G. Schultz;E. Eskin;F. Zadok;S.J. Stolfo.
ieee symposium on security and privacy (2001)

1413 Citations

A GEOMETRIC FRAMEWORK FOR UNSUPERVISED ANOMALY DETECTION: DETECTING INTRUSIONS IN UNLABELED DATA

E Eskin;A Arnold;M Prerau.
Applications of Data Mining in Computer Security (2002)

1025 Citations

Mismatch string kernels for discriminative protein classification

Christina S. Leslie;Eleazar Eskin;Adiel Cohen;Jason Weston.
Bioinformatics (2004)

951 Citations

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