L. Wayne Schultz

2.0k citations
33 papers · 1.6k · h-index 20

Impact in

Papers in

    • RNA and protein synthesis mechanisms 6
    • Protein Structure and Dynamics 4
    • Signaling Pathways in Disease 3
    • DNA and Nucleic Acid Chemistry 3
    • Bacterial Genetics and Biotechnology 6

L. Wayne Schultz

33 papers receiving 1.5k citations

Peers

L. Wayne Schultz
Comparison fields: 5 of 102
  • Molecular Medicine 354
  • Endocrinology 225
  • Molecular Biology 1.1k
  • Microbiology 51
  • Immunology 158
Replace Timothy C. Umland with:
Timothy C. Umland United States
L. Pernot Switzerland
Hein‐Peter Kroll Germany
Roman P. Jakob Switzerland
Xiuju Jiang United States
Shigeo Tamaki Japan
Laurent Maveyraud France
Jarrod W. Johnson Canada
L. Buts Belgium
Valérie Guillet France
L. Wayne Schultz relative to Timothy C. Umland United States Timothy C. Umland's profile →
Citations per field
00.5×1.5×2.4×
Timothy C. Umland · 1×
Citations per year

Countries citing papers authored by L. Wayne Schultz

Since Specialization
Citations

This map shows the geographic impact of L. 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 L. 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 L. Wayne Schultz more than expected).

Fields of papers citing papers by L. Wayne Schultz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside L. 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 L. Wayne Schultz Line = papers co-authored together L. 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 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010272
2 1998195
3 1993175
4 1980135
5 200985
6 200983
7 201270
8 199865
9 199859
10 198643
11 200542
12 200137
13 199929
14 201129
15 199926
16 199424
17 199422
18 199821
19 199421
20 201220

About L. Wayne Schultz

L. Wayne Schultz is a scholar working on Molecular Biology, Genetics, Oncology, Molecular Medicine and Materials Chemistry, having authored 33 papers that have together received 1.6k indexed citations. Recurring topics across this work include Bacterial Genetics and Biotechnology (6 papers), RNA and protein synthesis mechanisms (6 papers), Protein Structure and Dynamics (4 papers), Antibiotic Resistance in Bacteria (4 papers), Enzyme Structure and Function (4 papers), Signaling Pathways in Disease (3 papers), Peptidase Inhibition and Analysis (3 papers) and DNA and Nucleic Acid Chemistry (3 papers). The work is most often cited by research in Molecular Medicine (354 citations), Endocrinology (225 citations), Molecular Biology (1.1k citations), Microbiology (51 citations) and Immunology (158 citations). L. Wayne Schultz has collaborated with scholars based in United States, Canada and China. Frequent co-authors include Ronald T. Raines, Timothy C. Umland, Byung Moon Kim, Thomas A. Russo, Ulrike MacDonald, Ruth Olson, Janet M. Beanan, Peter A. Leland, Ralph Shapiro and Anita K. Hopper. Their work appears in journals such as Biochemistry, Journal of the American Chemical Society, Protein Science, Proceedings of the National Academy of Sciences and Virus Research.

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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