D-Index & Metrics Best Publications

D-Index & Metrics

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
Medicine D-index 88 Citations 38,533 230 World Ranking 6424 National Ranking 3555

Overview

What is he best known for?

The fields of study he is best known for:

  • Gene
  • Cancer
  • Internal medicine

His primary areas of investigation include Genetics, Gene expression profiling, Gene, Epigenetics and DNA methylation. His Genetics study integrates concerns from other disciplines, such as Autism and Autism spectrum disorder. His research in Gene expression profiling intersects with topics in Human brain, Transcriptome and Computational biology, Systems biology.

His studies in Epigenetics integrate themes in fields like Cancer, Obesity, Internal medicine, Disease and Biomarker. His studies deal with areas such as Young adult and Biomarkers of aging as well as DNA methylation. His Weighted correlation network analysis research incorporates elements of Data mining and Gene co-expression network.

His most cited work include:

  • WGCNA: an R package for weighted correlation network analysis. (7072 citations)
  • A General Framework for Weighted Gene Co-Expression Network Analysis (2897 citations)
  • DNA methylation age of human tissues and cell types (2454 citations)

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

His primary areas of study are Epigenetics, DNA methylation, Genetics, Gene and Internal medicine. Steve Horvath combines subjects such as Evolutionary biology, Ageing, Disease, Cell biology and Biomarkers of aging with his study of Epigenetics. His DNA methylation research incorporates themes from Biomarker and Methylation.

His Gene study incorporates themes from Computational biology and Immunology. Steve Horvath has included themes like Endocrinology and Oncology in his Internal medicine study. His study looks at the relationship between Gene expression profiling and fields such as Transcriptome, as well as how they intersect with chemical problems.

He most often published in these fields:

  • Epigenetics (41.26%)
  • DNA methylation (39.79%)
  • Genetics (21.26%)

What were the highlights of his more recent work (between 2018-2021)?

  • Epigenetics (41.26%)
  • DNA methylation (39.79%)
  • Methylation (17.47%)

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

His primary areas of investigation include Epigenetics, DNA methylation, Methylation, dNaM and Internal medicine. His Epigenetics research is multidisciplinary, relying on both Evolutionary biology, Ageing, Physiology, Biomarkers of aging and Cell biology. His DNA methylation study focuses on Genetics and Gene.

His Methylation study combines topics from a wide range of disciplines, such as Chromatin, Bivalent chromatin and Longevity. His dNaM research focuses on Body mass index and how it relates to Incidence. The concepts of his Internal medicine study are interwoven with issues in Endocrinology and Oncology.

Between 2018 and 2021, his most popular works were:

  • DNA methylation GrimAge strongly predicts lifespan and healthspan (231 citations)
  • DNA methylation aging clocks: challenges and recommendations (142 citations)
  • Reversal of epigenetic aging and immunosenescent trends in humans. (101 citations)

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

  • Gene
  • Internal medicine
  • Cancer

His main research concerns Epigenetics, DNA methylation, dNaM, Internal medicine and Ageing. The study incorporates disciplines such as Methylation, Senescence, Stem cell, Cell biology and Neuroscience in addition to Epigenetics. His study explores the link between Neuroscience and topics such as In vivo that cross with problems in Organoid and Gene expression.

Part of his project on DNA methylation includes research on Genetics and Gene. His dNaM research includes themes of Body mass index, Pregnancy, Gestational age, Andrology and Hazard ratio. Steve Horvath interconnects Endocrinology, Minor allele frequency, Single-nucleotide polymorphism and Oncology in the investigation of issues within Internal medicine.

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

WGCNA: an R package for weighted correlation network analysis.

Peter Langfelder;Steve Horvath.
BMC Bioinformatics (2008)

8356 Citations

A General Framework for Weighted Gene Co-Expression Network Analysis

Bin Zhang;Steve Horvath.
Statistical Applications in Genetics and Molecular Biology (2005)

3668 Citations

DNA methylation age of human tissues and cell types

Steve Horvath.
Genome Biology (2013)

3020 Citations

Defining clusters from a hierarchical cluster tree

Peter Langfelder;Bin Zhang;Steve Horvath.
Bioinformatics (2008)

1780 Citations

An anatomically comprehensive atlas of the adult human brain transcriptome

Michael J. Hawrylycz;Ed S. Lein;Angela L. Guillozet-Bongaarts;Elaine H. Shen.
Nature (2012)

1707 Citations

Molecular determinants of the response of glioblastomas to EGFR kinase inhibitors.

Ingo K. Mellinghoff;Maria Y. Wang;Igor Vivanco;Daphne A. Haas-Kogan.
The New England Journal of Medicine (2005)

1629 Citations

Transcriptomic analysis of autistic brain reveals convergent molecular pathology

Irina Voineagu;Xinchen Wang;Patrick G Johnston;Jennifer K Lowe.
Nature (2011)

1508 Citations

Global histone modification patterns predict risk of prostate cancer recurrence

David B. Seligson;Steve Horvath;Tao Shi;Hong Yu.
Nature (2005)

1133 Citations

Implementing a unified approach to family-based tests of association.

Nan M. Laird;Steve Horvath;Steve Horvath;Xin Xu.
Genetic Epidemiology (2000)

1005 Citations

Variations in DNA elucidate molecular networks that cause disease

Yanqing Chen;Jun Zhu;Pek Yee Lum;Xia Yang.
Nature (2008)

974 Citations

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