T. Wayne Schultz

63 papers receiving 1.4k citations

Peers

T. Wayne Schultz
Comparison fields: 5 of 126
  • Computational Theory and Mathematics 715
  • Health, Toxicology and Mutagenesis 446
  • Pollution 222
  • Environmental Chemistry 144
  • Chemical Health and Safety 9
Replace Simona Kovarich with:
Simona Kovarich Italy
Robert L. Lipnick United States
R.M. McDowell United States
Stefano Cassani Italy
Marjan Vračko Slovenia
Indrani Mitra India
Sabcho D. Dimitrov Bulgaria
Krista L. Dobo United States
Laura L. Custer United States
Tatiana I. Netzeva Italy
T. Wayne Schultz relative to Simona Kovarich Italy Simona Kovarich's profile →
Citations per field
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Simona Kovarich · 1×
Citations per year

Countries citing papers authored by T. Wayne Schultz

Since Specialization
Citations

This map shows the geographic impact of T. Wayne Schultz'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 T. Wayne Schultz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Wayne Schultz more than expected).

Fields of papers citing papers by T. Wayne Schultz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by T. Wayne Schultz. 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 T. Wayne Schultz. The network helps show where T. Wayne Schultz may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 65 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1998128
2 200183
3 200167
4 200866
5 200558
6 200458
7 199758
8 200552
9 198548
10 199848
11 200346
12 199544
13 200844
14 198237
15 199737
16 199934
17 200734
18 199633
19 199930
20 200327

About T. Wayne Schultz

T. Wayne Schultz is a scholar working on Health, Toxicology and Mutagenesis, Computational Theory and Mathematics, Pollution, Organic Chemistry and Spectroscopy, having authored 65 papers that have together received 1.5k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (19 papers), Environmental Toxicology and Ecotoxicology (15 papers), Free Radicals and Antioxidants (8 papers), Analytical Chemistry and Chromatography (8 papers), Pesticide Exposure and Toxicity (8 papers), Toxic Organic Pollutants Impact (7 papers), Chemical Reaction Mechanisms (6 papers) and Pesticide and Herbicide Environmental Studies (5 papers). The work is most often cited by research in Computational Theory and Mathematics (715 citations), Health, Toxicology and Mutagenesis (446 citations), Pollution (222 citations), Environmental Chemistry (144 citations) and Chemical Health and Safety (9 citations). T. Wayne Schultz has collaborated with scholars based in United States, United Kingdom and Bulgaria. Frequent co-authors include Mark Cronin, Tatiana I. Netzeva, Glendon D. Sinks, B. Gregory, Julie R. Seward, Jiřı́ Damborský, Jason W. Yarbrough, Aynur O. Aptula, Judith Clare Madden and David W. Roberts. Their work appears in journals such as SAR and QSAR in environmental research, Environmental Toxicology and Chemistry, Ecotoxicology and Environmental Safety, Bulletin of Environmental Contamination and Toxicology and Food and Chemical Toxicology.

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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