Duncan Penfold-Brown

1.9k total citations · 1 hit paper
7 papers, 994 citations indexed

About

Duncan Penfold-Brown is a scholar working on Molecular Biology, Communication and Political Science and International Relations. According to data from OpenAlex, Duncan Penfold-Brown has authored 7 papers receiving a total of 994 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 1 paper in Communication and 1 paper in Political Science and International Relations. Recurrent topics in Duncan Penfold-Brown's work include Genomics and Phylogenetic Studies (3 papers), Machine Learning in Bioinformatics (2 papers) and RNA and protein synthesis mechanisms (2 papers). Duncan Penfold-Brown is often cited by papers focused on Genomics and Phylogenetic Studies (3 papers), Machine Learning in Bioinformatics (2 papers) and RNA and protein synthesis mechanisms (2 papers). Duncan Penfold-Brown collaborates with scholars based in United States, Switzerland and Germany. Duncan Penfold-Brown's co-authors include Richard Bonneau, Noah Youngs, Kevin Drew, Yasuhiro Murakawa, Christoph Dieterich, Emanuel Wyler, Miha Milek, Markus Schueler, Matthias Selbach and Mathias Munschauer and has published in prestigious journals such as Molecular Cell, Bioinformatics and PLoS Computational Biology.

In The Last Decade

Duncan Penfold-Brown

7 papers receiving 987 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

The mRNA-Bound Proteome and Its Global Occupancy Profile on Protein-Coding Transcripts

2012 923 citations Mathias Munschauer, Björn Schwanhäußer et al. Molecular Cell profile →

Peers

Duncan Penfold-Brown

MB

CR

IMMUN

CB

PS

Annalisa Marsico Germany

Mischa Reinhardt Switzerland

Catherine Snow United Kingdom

Matthew R. Gazzara United States

Alexandra Paillusson Switzerland

Jörn M. Schmiedel Spain

Guillaume Harmange United States

Huanhuan Wei China

Tomasz Konopka United Kingdom

Nancy George United Kingdom

Annalisa Marsico Germany

Duncan Penfold-Brown

436 ×0.5

MB

249 ×1.5

CR

51 ×1.2

IMMUN

13 ×0.4

CB

19 ×0.9

PS

Citations per year, relative to Duncan Penfold-Brown Duncan Penfold-Brown (= 1×) peers Annalisa Marsico

Countries citing papers authored by Duncan Penfold-Brown

Since Specialization

Citations

This map shows the geographic impact of Duncan Penfold-Brown's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Duncan Penfold-Brown with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Duncan Penfold-Brown more than expected).

Fields of papers citing papers by Duncan Penfold-Brown

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Duncan Penfold-Brown. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Duncan Penfold-Brown. The network helps show where Duncan Penfold-Brown may publish in the future.

Co-authorship network of co-authors of Duncan Penfold-Brown

This figure shows the co-authorship network connecting the top 25 collaborators of Duncan Penfold-Brown. A scholar is included among the top collaborators of Duncan Penfold-Brown based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Duncan Penfold-Brown. Duncan Penfold-Brown is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

7 of 7 papers shown

1.

Langer, Melanie, John T. Jost, Richard Bonneau, et al.. (2018). Digital dissent: An analysis of the motivational contents of tweets from an Occupy Wall Street demonstration.. Motivation Science. 5(1). 14–34. 10 indexed citations

2.

Tucker, Joshua A., Megan MacDuffee Metzger, Duncan Penfold-Brown, et al.. (2015). Protest in the age of social media. 4 indexed citations

3.

Tucker, Joshua A., Megan MacDuffee Metzger, Duncan Penfold-Brown, et al.. (2015). Protest in the Age of Social Media: Technology and Ukraine’s #Euromaidan. 4 indexed citations

4.

Youngs, Noah, Duncan Penfold-Brown, Richard Bonneau, & Dennis Shasha. (2014). Negative Example Selection for Protein Function Prediction: The NoGO Database. PLoS Computational Biology. 10(6). e1003644–e1003644. 26 indexed citations

5.

Youngs, Noah, Duncan Penfold-Brown, Kevin Drew, Dennis Shasha, & Richard Bonneau. (2013). Parametric Bayesian priors and better choice of negative examples improve protein function prediction. Bioinformatics. 29(9). 1190–1198. 20 indexed citations

6.

Munschauer, Mathias, Björn Schwanhäußer, Yasuhiro Murakawa, et al.. (2012). The mRNA-Bound Proteome and Its Global Occupancy Profile on Protein-Coding Transcripts. Molecular Cell. 46(5). 674–690. 923 indexed citations breakdown →

7.

Pentony, Melissa M., Duncan Penfold-Brown, Kevin Drew, et al.. (2012). The Plant Proteome Folding Project: Structure and Positive Selection in Plant Protein Families. Genome Biology and Evolution. 4(3). 360–371. 7 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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