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
Biology and Biochemistry D-index 83 Citations 23,393 341 World Ranking 1479 National Ranking 39

Overview

What is he best known for?

The fields of study he is best known for:

  • Gene
  • Ecology
  • Statistics

His primary areas of study are Cell biology, Ecology, Paraspeckles, Meta-analysis and Paraspeckle. His Cell biology research is multidisciplinary, relying on both RNA, RNA-binding protein, Cadherin and Cellular differentiation. His Ecology research includes elements of Demography and Akaike information criterion.

His Akaike information criterion research incorporates themes from Generalized linear model, Multilevel model, Imputation and Model selection. Shinichi Nakagawa usually deals with Multilevel model and limits it to topics linked to Econometrics and Information Criteria, Linear model, Goodness of fit, Explained variation and Statistical power. His Meta-analysis research incorporates elements of Ecology, Process, Field and Data science.

His most cited work include:

  • A general and simple method for obtaining R2 from generalized linear mixed-effects models (5211 citations)
  • A general and simple method for obtaining R2 from generalized linear mixed-effects models (5211 citations)
  • Effect size, confidence interval and statistical significance: a practical guide for biologists. (2221 citations)

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

Ecology, Cell biology, Meta-analysis, Genetics and Demography are his primary areas of study. His work in Ecology covers topics such as Evolutionary biology which are related to areas like Quantitative genetics. In Cell biology, Shinichi Nakagawa works on issues like Paraspeckles, which are connected to Paraspeckle.

Much of his study explores Meta-analysis relationship to Cognitive psychology. His work on Genetics deals in particular with Gene and Epigenetics. His study in Demography is interdisciplinary in nature, drawing from both Offspring, Sexual selection, Mating, Mating system and Sparrow.

He most often published in these fields:

  • Ecology (29.89%)
  • Cell biology (14.47%)
  • Meta-analysis (16.54%)

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

  • Meta-analysis (16.54%)
  • Cell biology (14.47%)
  • Ecology (29.89%)

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

His primary areas of investigation include Meta-analysis, Cell biology, Ecology, Statistics and Paraspeckles. Shinichi Nakagawa has included themes like Sperm, Cognitive psychology, Perspective and Developmental psychology in his Meta-analysis study. The various areas that Shinichi Nakagawa examines in his Cell biology study include Polyadenylation, Downregulation and upregulation, RNA, Long non-coding RNA and Knockout mouse.

His biological study spans a wide range of topics, including Function and Intron. His work in the fields of Statistics, such as Repeatability, Covariate and Explained variation, intersects with other areas such as Variance and Anxiety. His Paraspeckles study integrates concerns from other disciplines, such as Ribonucleoprotein and Gene isoform.

Between 2018 and 2021, his most popular works were:

  • Immune system-mediated atherosclerosis caused by deficiency of long non-coding RNA MALAT1 in ApoE-/-mice. (45 citations)
  • Robustness of linear mixed-effects models to violations of distributional assumptions (44 citations)
  • Research Weaving: Visualizing the Future of Research Synthesis (35 citations)

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

  • Gene
  • Ecology
  • Statistics

His scientific interests lie mostly in Cell biology, Meta-analysis, Ecology, Paraspeckles and Ecology. His Cell biology research integrates issues from Knockout mouse, Gene expression and Alternative splicing. His Meta-analysis research includes themes of Zoology, Affect, Ambiguity, Judgement and Effect size.

His Ecology research is multidisciplinary, incorporating elements of Conservation science, Biodiversity, Range and Scientific progress. The study incorporates disciplines such as Paraspeckle, Compartmentalization and Gene isoform in addition to Paraspeckles. His work deals with themes such as Diversity, Biological system and Metagenomics, which intersect with Ecology.

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

A general and simple method for obtaining R2 from generalized linear mixed-effects models

Shinichi Nakagawa;Shinichi Nakagawa;Holger Schielzeth.
Methods in Ecology and Evolution (2013)

6628 Citations

Effect size, confidence interval and statistical significance: a practical guide for biologists.

Shinichi Nakagawa;Innes C. Cuthill.
Biological Reviews (2007)

2851 Citations

A farewell to Bonferroni: the problems of low statistical power and publication bias

Shinichi Nakagawa.
Behavioral Ecology (2004)

2142 Citations

Redefine statistical significance

.
Nature Human Behaviour (2018)

2045 Citations

Multimodel inference in ecology and evolution: challenges and solutions

.
Journal of Evolutionary Biology (2011)

1973 Citations

Repeatability for Gaussian and non-Gaussian data: a practical guide for biologists.

Shinichi Nakagawa;Holger Schielzeth.
Biological Reviews (2010)

1830 Citations

Meta-analysis and the science of research synthesis

.
Nature (2018)

821 Citations

Redefine Statistical Significance

Daniel Benjamin;James Berger;Magnus Johannesson;Brian Nosek.
Research Papers in Economics (2017)

778 Citations

The coefficient of determination R2 and intra-class correlation coefficient from generalized linear mixed-effects models revisited and expanded.

Shinichi Nakagawa;Shinichi Nakagawa;Paul C. D. Johnson;Holger Schielzeth.
Journal of the Royal Society Interface (2017)

716 Citations

rptR: repeatability estimation and variance decomposition by generalized linear mixed-effects models

Martin A. Stoffel;Martin A. Stoffel;Shinichi Nakagawa;Holger Schielzeth;Holger Schielzeth.
Methods in Ecology and Evolution (2017)

602 Citations

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