Hayden C. Metsky

4.1k total citations · 2 hit papers
8 papers, 951 citations indexed

About

Hayden C. Metsky is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine and Artificial Intelligence. According to data from OpenAlex, Hayden C. Metsky has authored 8 papers receiving a total of 951 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 1 paper in Cardiology and Cardiovascular Medicine and 1 paper in Artificial Intelligence. Recurrent topics in Hayden C. Metsky's work include CRISPR and Genetic Engineering (4 papers), RNA and protein synthesis mechanisms (2 papers) and Advanced biosensing and bioanalysis techniques (2 papers). Hayden C. Metsky is often cited by papers focused on CRISPR and Genetic Engineering (4 papers), RNA and protein synthesis mechanisms (2 papers) and Advanced biosensing and bioanalysis techniques (2 papers). Hayden C. Metsky collaborates with scholars based in United States, Netherlands and Denmark. Hayden C. Metsky's co-authors include Cameron Myhrvold, Pardis C. Sabeti, Chloe K. Boehm, Amber Carter, Catherine A. Freije, Cheri M. Ackerman, David Yang, Paul C. Blainey, Jared Kehe and Deborah T. Hung and has published in prestigious journals such as Nature, Nature Communications and Nature Biotechnology.

In The Last Decade

Hayden C. Metsky

7 papers receiving 935 citations

Hit Papers

Massively multiplexed nucleic acid detection with Cas13 2019 2026 2021 2023 2020 2019 100 200 300 400 500

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Hayden C. Metsky United States 4 787 304 227 128 84 8 951
Amber Carter United States 3 735 0.9× 288 0.9× 218 1.0× 124 1.0× 78 0.9× 3 895
Spencer C. Knight United States 5 1.2k 1.5× 150 0.5× 96 0.4× 96 0.8× 91 1.1× 6 1.3k
Tin Maršić Saudi Arabia 11 778 1.0× 363 1.2× 204 0.9× 95 0.7× 25 0.3× 14 917
Tinna-Sólveig F. Kosoko-Thoroddsen United States 2 488 0.6× 252 0.8× 139 0.6× 73 0.6× 36 0.4× 3 597
Lu Dang China 9 501 0.6× 139 0.5× 162 0.7× 72 0.6× 47 0.6× 11 603
Nicole L. Welch United States 6 386 0.5× 102 0.3× 99 0.4× 59 0.5× 51 0.6× 11 482
Xinlin Lei China 7 501 0.6× 131 0.4× 73 0.3× 38 0.3× 43 0.5× 9 584
Augustine Chemparathy United States 7 682 0.9× 49 0.2× 184 0.8× 63 0.5× 70 0.8× 10 820
Qingqin Gao China 6 567 0.7× 109 0.4× 57 0.3× 67 0.5× 39 0.5× 7 609
Hisato Hirano Japan 9 1.2k 1.6× 51 0.2× 59 0.3× 80 0.6× 60 0.7× 14 1.3k

Countries citing papers authored by Hayden C. Metsky

Since Specialization
Citations

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

Fields of papers citing papers by Hayden C. Metsky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hayden C. Metsky. 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 Hayden C. Metsky. The network helps show where Hayden C. Metsky may publish in the future.

Co-authorship network of co-authors of Hayden C. Metsky

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

All Works

8 of 8 papers shown
1.
Metsky, Hayden C., Katherine J. Siddle, Christian B. Matranga, & Pardis C. Sabeti. (2026). Best practices when benchmarking CATCH for the design of genome enrichment probes. Bioinformatics.
2.
Mantena, Sreekar, Brittany A. Petros, Nicole L. Welch, et al.. (2024). Model-directed generation of artificial CRISPR–Cas13a guide RNA sequences improves nucleic acid detection. Nature Biotechnology. 43(8). 1266–1273. 9 indexed citations
3.
Young, Mark, Timothy J. Straub, Colin J. Worby, et al.. (2024). Distinct Escherichia coli transcriptional profiles in the guts of recurrent UTI sufferers revealed by pangenome hybrid selection. Nature Communications. 15(1). 9466–9466. 3 indexed citations
4.
Metsky, Hayden C., Nicole L. Welch, Nicholas J. Haradhvala, et al.. (2022). Designing sensitive viral diagnostics with machine learning. Nature Biotechnology. 40(7). 1123–1131. 51 indexed citations
5.
Ackerman, Cheri M., Cameron Myhrvold, Sri Gowtham Thakku, et al.. (2020). Massively multiplexed nucleic acid detection with Cas13. Nature. 582(7811). 277–282. 592 indexed citations breakdown →
6.
Freije, Catherine A., Cameron Myhrvold, Chloe K. Boehm, et al.. (2019). Programmable Inhibition and Detection of RNA Viruses Using Cas13. Molecular Cell. 76(5). 826–837.e11. 293 indexed citations breakdown →
7.
Park, Daniel, Simon Ye, Irwin Jungreis, et al.. (2018). broadinstitute/viral-ngs: v1.19.2. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations
8.
Habash, Nizar & Hayden C. Metsky. (2008). Automatic Learning of Morphological Variations f or Handling Out-of-Vocabulary Terms in Urdu-English Machine Translation. Conference of the Association for Machine Translation in the Americas. 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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