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
Genetics and Molecular Biology D-index 72 Citations 30,372 188 World Ranking 1381 National Ranking 720

Overview

What is he best known for?

The fields of study he is best known for:

  • Gene
  • Enzyme
  • DNA

His main research concerns Genetics, Proteomics, Molecular biology, Biochemistry and Computational biology. His Proteomics study combines topics in areas such as Proteome, Tandem affinity purification, Protein–protein interaction and Mass spectrometry. As part of the same scientific family, Andrew Emili usually focuses on Tandem affinity purification, concentrating on Protein–protein interaction prediction and intersecting with Experimental data, Bayes' theorem and Bayesian network.

His studies in Molecular biology integrate themes in fields like Histone H3, Histone methyltransferase, Chromatin immunoprecipitation, Histone H1 and Cell biology. Andrew Emili has included themes like Platelet activation, Platelet and Cyclophilin A in his Biochemistry study. His Computational biology study integrates concerns from other disciplines, such as Tandem mass spectrometry, Bioinformatics, Chaperone, Proteomic Profiling and DNA microarray.

His most cited work include:

  • Global landscape of protein complexes in the yeast Saccharomyces cerevisiae (2539 citations)
  • Quantifying E. coli proteome and transcriptome with single-molecule sensitivity in single cells. (1539 citations)
  • Enrichment Map: A Network-Based Method for Gene-Set Enrichment Visualization and Interpretation (1184 citations)

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

Computational biology, Cell biology, Proteomics, Biochemistry and Genetics are his primary areas of study. Andrew Emili combines subjects such as Proteome, Bioinformatics, Proteomic Profiling, Interactome and Mass spectrometry with his study of Computational biology. His studies in Cell biology integrate themes in fields like Nuclear export signal, Transcription factor, Molecular biology, RNA splicing and RNA-binding protein.

His study in Molecular biology is interdisciplinary in nature, drawing from both RNA polymerase II and Gene expression. His biological study spans a wide range of topics, including Tandem mass spectrometry, Tandem affinity purification, Systems biology and Gene expression profiling. His study in Gene, Genome, Saccharomyces cerevisiae, Chromatin and Synthetic genetic array falls under the purview of Genetics.

He most often published in these fields:

  • Computational biology (30.20%)
  • Cell biology (23.83%)
  • Proteomics (22.48%)

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

  • Cell biology (23.83%)
  • Computational biology (30.20%)
  • Cancer research (3.02%)

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

Andrew Emili mainly investigates Cell biology, Computational biology, Cancer research, Protein–protein interaction and Proteome. His Cell biology research includes themes of Nuclear export signal, Gene, RNA, Gene knockdown and Adipose tissue. His research integrates issues of Cell, Myocardial fibrosis, Hypertrophic cardiomyopathy, Function and Interactome in his study of Computational biology.

His research investigates the connection between Cell and topics such as Proteomics that intersect with problems in Tauopathy. His Protein–protein interaction study improves the overall literature in Biochemistry. His Proteome study incorporates themes from Exosome, Protein Interaction Map, MEDLINE and Nanoparticle tracking analysis.

Between 2018 and 2021, his most popular works were:

  • EPIC: software toolkit for elution profile-based inference of protein complexes. (29 citations)
  • EPIC: software toolkit for elution profile-based inference of protein complexes. (29 citations)
  • SARS-CoV-2 Spike Protein Interacts with Multiple Innate Immune Receptors. (27 citations)

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

  • Gene
  • Enzyme
  • DNA

Andrew Emili mainly focuses on Interactome, Cell biology, Computational biology, Innate immune system and Proteome. His Interactome research includes elements of Inference, Native protein and Mass spectrometry. Andrew Emili has researched Cell biology in several fields, including RNA splicing, NXF1 and Messenger RNA, Gene, Intron.

His Computational biology research incorporates elements of Transgenic Model, Elution, Chaperone and Protein–protein interaction. In his study, which falls under the umbrella issue of Innate immune system, Cell cycle checkpoint, Pathogen and Translation is strongly linked to Virus. The various areas that Andrew Emili examines in his Proteome study include Protein aggregation, R2TP complex, Hsp90, Antifungal drug and Stress granule.

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

Global landscape of protein complexes in the yeast Saccharomyces cerevisiae

Nevan J. Krogan;Gerard Cagney;Gerard Cagney;Haiyuan Yu;Gouqing Zhong.
Nature (2006)

3085 Citations

Quantifying E. coli proteome and transcriptome with single-molecule sensitivity in single cells.

Yuichi Taniguchi;Paul J. Choi;Gene-Wei Li;Huiyi Chen.
Science (2010)

1906 Citations

A Bayesian networks approach for predicting protein-protein interactions from genomic data.

Ronald Jansen;Haiyuan Yu;Dov Greenbaum;Yuval Kluger.
Science (2003)

1518 Citations

Nanoparticle Size and Surface Chemistry Determine Serum Protein Adsorption and Macrophage Uptake

Carl D. Walkey;Jonathan B. Olsen;Hongbo Guo;Andrew Emili.
Journal of the American Chemical Society (2012)

1459 Citations

Enrichment Map: A Network-Based Method for Gene-Set Enrichment Visualization and Interpretation

Daniele Merico;Ruth Isserlin;Oliver Stueker;Andrew Emili.
PLOS ONE (2010)

1401 Citations

Interaction network containing conserved and essential protein complexes in Escherichia coli

Gareth Butland;José Manuel Peregrín-Alvarez;Joyce Li;Wehong Yang.
Nature (2005)

1302 Citations

Functional dissection of protein complexes involved in yeast chromosome biology using a genetic interaction map

Sean R. Collins;Kyle M. Miller;Nancy L. Maas;Assen Roguev.
Nature (2007)

955 Citations

Characterization of the proteins released from activated platelets leads to localization of novel platelet proteins in human atherosclerotic lesions

Judith A. Coppinger;Gerard Cagney;Gerard Cagney;Sinead Toomey;Sinead Toomey;Thomas Kislinger;Thomas Kislinger.
Blood (2004)

861 Citations

Cotranscriptional set2 methylation of histone H3 lysine 36 recruits a repressive Rpd3 complex.

Michael Christopher Keogh;Siavash K. Kurdistani;Stephanie A. Morris;Seong Hoon Ahn.
Cell (2005)

846 Citations

Navigating the Chaperone Network: An Integrative Map of Physical and Genetic Interactions Mediated by the Hsp90 Chaperone

Rongmin Zhao;Mike Davey;Ya-Chieh Hsu;Pia Kaplanek.
Cell (2005)

827 Citations

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