Gordon Rix

423 total citations
4 papers, 114 citations indexed

About

Gordon Rix is a scholar working on Molecular Biology, Genetics and Artificial Intelligence. According to data from OpenAlex, Gordon Rix has authored 4 papers receiving a total of 114 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 2 papers in Genetics and 1 paper in Artificial Intelligence. Recurrent topics in Gordon Rix's work include CRISPR and Genetic Engineering (2 papers), Evolution and Genetic Dynamics (2 papers) and Amino Acid Enzymes and Metabolism (1 paper). Gordon Rix is often cited by papers focused on CRISPR and Genetic Engineering (2 papers), Evolution and Genetic Dynamics (2 papers) and Amino Acid Enzymes and Metabolism (1 paper). Gordon Rix collaborates with scholars based in United States and Japan. Gordon Rix's co-authors include Chang C. Liu, Patrick J. Almhjell, Frances H. Arnold, Christina Smith, Ella J. Watkins‐Dulaney, Debora S. Marks and James A. Van Deventer and has published in prestigious journals such as Science, Nature Communications and Current Opinion in Chemical Biology.

In The Last Decade

Gordon Rix

4 papers receiving 114 citations

Peers

Gordon Rix
Kadina E. Johnston United States
Liang Fang United States
Karen R. Khar United States
Ka‐Hei Siu United States
Stacey Gerben United States
Ana Crnković United States
Jernej Turnšek United States
Yisi Li China
Kadina E. Johnston United States
Gordon Rix
Citations per year, relative to Gordon Rix Gordon Rix (= 1×) peers Kadina E. Johnston

Countries citing papers authored by Gordon Rix

Since Specialization
Citations

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

Fields of papers citing papers by Gordon Rix

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gordon Rix

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

All Works

4 of 4 papers shown
1.
Rix, Gordon, et al.. (2025). Directed evolution of aminoacyl-tRNA synthetases through in vivo hypermutation. Nature Communications. 16(1). 4832–4832. 1 indexed citations
2.
Rix, Gordon, et al.. (2024). Continuous evolution of user-defined genes at 1 million times the genomic mutation rate. Science. 386(6722). eadm9073–eadm9073. 16 indexed citations
3.
Rix, Gordon & Chang C. Liu. (2021). Systems for in vivo hypermutation: a quest for scale and depth in directed evolution. Current Opinion in Chemical Biology. 64. 20–26. 29 indexed citations
4.
Rix, Gordon, Ella J. Watkins‐Dulaney, Patrick J. Almhjell, et al.. (2020). Scalable continuous evolution for the generation of diverse enzyme variants encompassing promiscuous activities. Nature Communications. 11(1). 5644–5644. 68 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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