David W. Elrod

1.4k citations
18 papers · 1.2k indexed · h-index 12
Topics
Machine Learning in Bioinformatics (7 papers)RNA and protein synthesis mechanisms (6 papers)Microbial Natural Products and Biosynthesis (4 papers)
Partner nations
United StatesNorway

In The Last Decade

David W. Elrod

18 papers receiving 1.1k citations

Peers

David W. Elrod
Comparison fields: 5 of 96
  • Molecular Biology 994
  • Computational Theory and Mathematics 196
  • Spectroscopy 85
  • Organic Chemistry 61
  • Pharmacology 40
Replace Michael Thormann with:
Michael Thormann Germany
John H. Van Drie United States
James L. Melville United Kingdom
Philip M. Dean United Kingdom
Hitomi Yuki Japan
K. V. Karapetyan United States
Jeffrey W. Godden United States
Paolo Benedetti Italy
Linda Traphagen United States
John W. Mayfield United States
David W. Elrod relative to Michael Thormann Germany Michael Thormann's profile →
Citations per field
00.5×4.1×
Michael Thormann · 1×
Citations per year

Countries citing papers authored by David W. Elrod

Since Specialization
Citations

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

Fields of papers citing papers by David W. Elrod

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David W. Elrod

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

All Works

18 of 18 papers shown
#WorkIndexed citations
1 99
2 1
3 47
4 150
5 10
6 323
7 204
8 83
9 33
10 58
11 10
12 59
13 5
14 24
15 7
16 26
17 24
18 11

About David W. Elrod

David W. Elrod is a scholar working on Toxicology, Pharmacology and Molecular Biology, having authored 18 papers that have together received 1.2k indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (7 papers), RNA and protein synthesis mechanisms (6 papers) and Microbial Natural Products and Biosynthesis (4 papers). The work is most often cited by research in Molecular Biology (994 citations), Computational Theory and Mathematics (196 citations) and Spectroscopy (85 citations). David W. Elrod has collaborated with scholars based in United States and Norway. Frequent co-authors include Kuo‐Chen Chou, Kuo‐Chen Chou, Gerald M. Maggiora, Paul F. Wiley, V. P. MARSHALL, Chun‐Ting Zhang, William C. Krueger, Albert Moscowitz, Donald E. Harper and James M. Slavicek. Their work appears in journals such as Biochemical and Biophysical Research Communications, Journal of Medicinal Chemistry and The Journal of Organic Chemistry.

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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