Gavin Hanson

1.9k total citations · 2 hit papers
7 papers, 1.2k citations indexed

About

Gavin Hanson is a scholar working on Molecular Biology, Cognitive Neuroscience and Artificial Intelligence. According to data from OpenAlex, Gavin Hanson has authored 7 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 1 paper in Cognitive Neuroscience and 1 paper in Artificial Intelligence. Recurrent topics in Gavin Hanson's work include RNA modifications and cancer (5 papers), RNA and protein synthesis mechanisms (5 papers) and RNA Research and Splicing (5 papers). Gavin Hanson is often cited by papers focused on RNA modifications and cancer (5 papers), RNA and protein synthesis mechanisms (5 papers) and RNA Research and Splicing (5 papers). Gavin Hanson collaborates with scholars based in United States and Canada. Gavin Hanson's co-authors include Jeff Coller, Thomas J. Sweet, Najwa Alhusaini, David Sturgill, Daniel Arango, Kyster K. Nanan, Thomas Zengeya, Shalini Oberdoerffer, Stephen D. Fox and Allissa Dillman and has published in prestigious journals such as Cell, Nature Reviews Molecular Cell Biology and PLoS ONE.

In The Last Decade

Gavin Hanson

7 papers receiving 1.2k 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.

Acetylation of Cytidine in mRNA Promotes Translation Efficiency

2018 566 citations Daniel Arango, David Sturgill et al. Cell profile →
Codon optimality, bias and usage in translation and mRNA decay

2017 515 citations Gavin Hanson, Jeff Coller Nature Reviews Molecular Cell Biology profile →

Peers

Gavin Hanson

MB

CR

GENET

ONCOL

IMMUN

Najwa Alhusaini United States

Tracy Nissan Sweden

Stefan Bresson United Kingdom

Georgij Arapidi Russia

Christine Strand United States

Hiroyuki Wakaguri Japan

Christina Begon‐Pescia France

John Dresios United States

Danny D. Nedialkova Germany

David A. Mangus United States

Najwa Alhusaini United States

Gavin Hanson

1.8k ×1.7

MB

264 ×1.2

CR

130 ×1.4

GENET

83 ×1.3

ONCOL

102 ×1.8

IMMUN

Citations per year, relative to Gavin Hanson Gavin Hanson (= 1×) peers Najwa Alhusaini

Countries citing papers authored by Gavin Hanson

Since Specialization

Citations

This map shows the geographic impact of Gavin Hanson'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 Gavin Hanson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gavin Hanson more than expected).

Fields of papers citing papers by Gavin Hanson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gavin Hanson. 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 Gavin Hanson. The network helps show where Gavin Hanson may publish in the future.

Co-authorship network of co-authors of Gavin Hanson

This figure shows the co-authorship network connecting the top 25 collaborators of Gavin Hanson. A scholar is included among the top collaborators of Gavin Hanson 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 Gavin Hanson. Gavin Hanson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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7 of 7 papers shown

1.

Forrest, Megan E., Otis Pinkard, Sophie Martin, et al.. (2020). Codon and amino acid content are associated with mRNA stability in mammalian cells. PLoS ONE. 15(2). e0228730–e0228730. 66 indexed citations

2.

Arango, Daniel, David Sturgill, Najwa Alhusaini, et al.. (2018). Acetylation of Cytidine in mRNA Promotes Translation Efficiency. Cell. 175(7). 1872–1886.e24. 566 indexed citations breakdown →

3.

Hanson, Gavin, Najwa Alhusaini, Nathan Morris, Thomas J. Sweet, & Jeff Coller. (2018). Translation elongation and mRNA stability are coupled through the ribosomal A-site. RNA. 24(10). 1377–1389. 38 indexed citations

4.

Forrest, Megan E., Ashrut Narula, Thomas J. Sweet, et al.. (2018). Codon Usage and Amino Acid Identity Are Major Determinants of MRNA Stability in Humans. SSRN Electronic Journal. 1 indexed citations

5.

Hanson, Gavin & Evangelia G. Chrysikou. (2017). Attention to Distinct Goal-relevant Features Differentially Guides Semantic Knowledge Retrieval. Journal of Cognitive Neuroscience. 29(7). 1178–1193. 5 indexed citations

6.

Hanson, Gavin & Jeff Coller. (2017). Codon optimality, bias and usage in translation and mRNA decay. Nature Reviews Molecular Cell Biology. 19(1). 20–30. 515 indexed citations breakdown →

7.

Chrysikou, Evangelia G., Gavin Hanson, Laura E. Martin, et al.. (2017). Proceedings #7. Transcranial direct current stimulation effects on prefrontal cortex in major depressive disorder (MDD) measured by in vivo proton magnetic resonance spectroscopy ( 1 H MRS). Brain stimulation. 10(4). e53–e54. 2 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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