David H. Burkhardt

2.0k total citations · 1 hit paper
7 papers, 1.4k citations indexed

About

David H. Burkhardt is a scholar working on Molecular Biology, Ecology and Genetics. According to data from OpenAlex, David H. Burkhardt has authored 7 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 2 papers in Ecology and 2 papers in Genetics. Recurrent topics in David H. Burkhardt's work include RNA and protein synthesis mechanisms (3 papers), Gene Regulatory Network Analysis (3 papers) and Bacteriophages and microbial interactions (2 papers). David H. Burkhardt is often cited by papers focused on RNA and protein synthesis mechanisms (3 papers), Gene Regulatory Network Analysis (3 papers) and Bacteriophages and microbial interactions (2 papers). David H. Burkhardt collaborates with scholars based in United States, Japan and Taiwan. David H. Burkhardt's co-authors include Carol A. Gross, Jonathan S. Weissman, Gene‐Wei Li, Yan Zhang, Silvi Rouskin, Todd C. Peterson, Virgil A. Rhodius, Ekaterina Orlova, Amar Ghodasara and Thomas H. Segall-Shapiro and has published in prestigious journals such as Cell, Journal of Biological Chemistry and Molecular Cell.

In The Last Decade

David H. Burkhardt

7 papers receiving 1.4k citations

Hit Papers

Quantifying Absolute Protein Synthesis Rates Reveals Prin... 2014 2026 2018 2022 2014 250 500 750
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.

  1. Quantifying Absolute Protein Synthesis Rates Reveals Principles Underlying Allocation of Cellular Resources
    2014 929 citations Gene‐Wei Li, David H. Burkhardt et al. Cell profile →

Peers

David H. Burkhardt
Bei‐Wen Ying Japan
Carl W. Gunderson United States
Jiqiang Ling United States
Norbert S. Hill United States
Shenghai Chang China
Nick T. Peters United States
Katsuya Satoh Japan
Scott Cayley United States
M.J. Fero United States
Aaron D. Goldman United States
Bei‐Wen Ying Japan
David H. Burkhardt
Citations per year, relative to David H. Burkhardt David H. Burkhardt (= 1×) peers Bei‐Wen Ying

Countries citing papers authored by David H. Burkhardt

Since Specialization
Citations

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

Fields of papers citing papers by David H. Burkhardt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David H. Burkhardt. 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 David H. Burkhardt. The network helps show where David H. Burkhardt may publish in the future.

Co-authorship network of co-authors of David H. Burkhardt

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

All Works

7 of 7 papers shown
1.
Zhang, Yan, David H. Burkhardt, Silvi Rouskin, et al.. (2018). A Stress Response that Monitors and Regulates mRNA Structure Is Central to Cold Shock Adaptation. Molecular Cell. 70(2). 274–286.e7. 134 indexed citations
2.
Burkhardt, David H., Silvi Rouskin, Yan Zhang, et al.. (2017). Operon mRNAs are organized into ORF-centric structures that predict translation efficiency. eLife. 6. 110 indexed citations
3.
Morgan, Gareth J., David H. Burkhardt, Jeffery W. Kelly, & Evan T. Powers. (2017). Translation efficiency is maintained at elevated temperature in Escherichia coli. Journal of Biological Chemistry. 293(3). 777–793. 20 indexed citations
4.
Li, Gene‐Wei, David H. Burkhardt, Carol A. Gross, & Jonathan S. Weissman. (2014). Quantifying Absolute Protein Synthesis Rates Reveals Principles Underlying Allocation of Cellular Resources. Cell. 157(3). 624–635. 929 indexed citations breakdown →
5.
Rhodius, Virgil A., Thomas H. Segall-Shapiro, Amar Ghodasara, et al.. (2013). Design of orthogonal genetic switches based on a crosstalk map of σs, anti‐σs, and promoters. Molecular Systems Biology. 9(1). 702–702. 138 indexed citations
6.
Rhodius, Virgil A., Ekaterina Orlova, Hannah Tabakh, et al.. (2013). Design of orthogonal genetic switches based on a crosstalk map of σs, anti-σs, and promoters. DSpace@MIT (Massachusetts Institute of Technology). 1 indexed citations
7.
Liu, Ningyu, Victor P. Pasko, David H. Burkhardt, et al.. (2006). Comparison of results from sprite streamer modeling with spectrophotometric measurements by ISUAL instrument on FORMOSAT‐2 satellite. Geophysical Research Letters. 33(1). 59 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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