Daniel S. May

14 papers receiving 290 citations

Peers

Daniel S. May
Comparison fields: 5 of 72
  • Endocrinology 28
  • Pharmacology 62
  • Biotechnology 31
  • Insect Science 32
  • Environmental Chemistry 24
Replace Melinda L. Micallef with:
Melinda L. Micallef Australia
Arwa Al-Dilaimi Germany
Judit Kucsera Hungary
Mario Alberto Martínez‐Núñez Mexico
Žiga Zebec United Kingdom
Xuehuan Feng United States
Cassandra Carroll Canada
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Daniel S. May relative to Melinda L. Micallef Australia Melinda L. Micallef's profile →
Citations per field
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Melinda L. Micallef · 1×
Citations per year

Countries citing papers authored by Daniel S. May

Since Specialization
Citations

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

Fields of papers citing papers by Daniel S. May

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel S. May. 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 Daniel S. May. The network helps show where Daniel S. May may publish in the future.

Co-authors

The 25 scholars most cited alongside Daniel S. May, 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 Daniel S. May Line = papers co-authored together Daniel S. May links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 201863
2 196547
3 201730
4 202029
5 201728
6 202426
7 202123
8 202114
9 201813
10 201810
11 20229
12 20184
13
Egg washing - trials and tribulations.
20132
14 20151
15 20240
16 20260
17 20250
18 20160
19 20160
20
Egg penetration by Salmonella Typhimurium in washed and unwashed eggs.
20130

About Daniel S. May

Daniel S. May is a scholar working on Molecular Biology, Ecology, Evolution, Behavior and Systematics, Renewable Energy, Sustainability and the Environment, Ecology and Pharmacology, having authored 20 papers that have together received 299 indexed citations. Recurring topics across this work include Algal biology and biofuel production (7 papers), Photosynthetic Processes and Mechanisms (4 papers), Insect and Arachnid Ecology and Behavior (3 papers), Insect and Pesticide Research (3 papers), Biocrusts and Microbial Ecology (3 papers), Plant and animal studies (3 papers), Microbial Natural Products and Biosynthesis (3 papers) and Aquatic Ecosystems and Phytoplankton Dynamics (2 papers). The work is most often cited by research in Endocrinology (28 citations), Pharmacology (62 citations), Biotechnology (31 citations), Insect Science (32 citations) and Environmental Chemistry (24 citations). Daniel S. May has collaborated with scholars based in United States, Brazil and Canada. Frequent co-authors include C.A. Knight, Jimmy Orjala, Camila Manoel Crnkovic, Cameron R. Currie, Aleksej Krunić, Marc G. Chevrette, Caitlin M. Carlson, Reed M. Stubbendieck, Evelyn Wendt-Pienkowski and James E. Gern. Their work appears in journals such as Planta Medica, Journal of Natural Products, Frontiers in Microbiology, Applied and Environmental Microbiology and Journal of Applied Phycology.

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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