Chad W. Euler

34 papers receiving 3.2k citations

Chad W. Euler's Hit Papers

Exploiting CRISPR-Cas nucleases to produce sequence-specific antimicrobials 2014 · 793 citations
7930+4+8Years since publication250500750

Peers

Chad W. Euler
Comparison fields: 5 of 84
  • Ecology 1.5k
  • Applied Microbiology and Biotechnology 70
  • Molecular Medicine 188
  • Microbiology 131
  • Rheumatology 250
Replace José Yuste with:
José Yuste Spain
Krystyna Dąbrowska Poland
Yan Q. Xiong United States
Leo Y.-C. Lin United States
P. Patrick Cleary United States
Laurent Debarbieux France
Olga Danilchanka United States
Pieter‐Jan Haas Netherlands
Caroline Westwater United States
Christiane Goerke Germany
Chad W. Euler relative to José Yuste Spain José Yuste's profile →
Citations per field
00.5×5×11.6×
José Yuste · 1×
Citations per year

Countries citing papers authored by Chad W. Euler

Since Specialization
Citations

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

Fields of papers citing papers by Chad W. Euler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Chad W. Euler, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Chad W. Euler Line = papers co-authored together Chad W. Euler links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Exploiting CRISPR-Cas nucleases to produce sequence-specific antimicrobials
Hit paper breakdown →
2014793
2 2002459
3 2015227
4 2010209
5 2013192
6 2010158
7 2016123
8 2020110
9 2015105
10 201996
11 201995
12 200582
13 201860
14 202158
15 201551
16 201446
17 202342
18 201340
19 202040
20 200639

About Chad W. Euler

Chad W. Euler is a scholar working on Ecology, Infectious Diseases, Immunology, Rheumatology and Microbiology, having authored 35 papers that have together received 3.3k indexed citations. Recurring topics across this work include Bacteriophages and microbial interactions (17 papers), T-cell and B-cell Immunology (6 papers), Antimicrobial Resistance in Staphylococcus (5 papers), CRISPR and Genetic Engineering (5 papers), Streptococcal Infections and Treatments (4 papers), Antimicrobial Peptides and Activities (2 papers), Rheumatoid Arthritis Research and Therapies (2 papers) and Systemic Lupus Erythematosus Research (2 papers). The work is most often cited by research in Ecology (1.5k citations), Applied Microbiology and Biotechnology (70 citations), Molecular Medicine (188 citations), Microbiology (131 citations) and Rheumatology (250 citations). Chad W. Euler has collaborated with scholars based in United States, China and Spain. Frequent co-authors include Vincent A. Fischetti, Mark Jay Shlomchik, Jacqueline William, Sean R. Christensen, Luciano A. Marraffini, Xavier Duportet, David Bikard, Gregory W. Goldberg, Wenyan Jiang and Peter Chahales. Their work appears in journals such as Antimicrobial Agents and Chemotherapy, PLoS ONE, The Journal of Immunology, Frontiers in Microbiology and Antibiotics.

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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