Stephen E. de Laszlo

1.4k citations
34 papers · 1.1k · h-index 18

Impact in

Papers in

Stephen E. de Laszlo

33 papers receiving 973 citations

Peers

Stephen E. de Laszlo
Comparison fields: 5 of 73
  • Organic Chemistry 624
  • Endocrinology, Diabetes and Metabolism 129
  • Molecular Biology 538
  • Immunology and Allergy 33
  • Cardiology and Cardiovascular Medicine 87
Replace Mitree M. Ponpipom with:
Mitree M. Ponpipom United States
Nicolas Inguimbert France
Allan Hallett United Kingdom
Randall W. Hungate United States
John W. Ellingboe United States
John J. Piwinski United States
Joseph P. Burkhart United States
Ivan L. Pinto United Kingdom
Ila Sircar United States
Richard E. Mewshaw United States
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Citations per year

Countries citing papers authored by Stephen E. de Laszlo

Since Specialization
Citations

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

Fields of papers citing papers by Stephen E. de Laszlo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stephen E. de Laszlo. 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 Stephen E. de Laszlo. The network helps show where Stephen E. de Laszlo may publish in the future.

Co-authors

The 25 scholars most cited alongside Stephen E. de Laszlo, 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 Stephen E. de Laszlo Line = papers co-authored together Stephen E. de Laszlo links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1999157
2 1993107
3 200195
4 199887
5 199979
6 198546
7 199245
8 198644
9 199941
10 200038
11 198934
12 198428
13 200224
14 199320
15 199420
16 199319
17 199718
18 198517
19 200416
20 199516

About Stephen E. de Laszlo

Stephen E. de Laszlo is a scholar working on Molecular Biology, Organic Chemistry, Cardiology and Cardiovascular Medicine, Oncology and Cellular and Molecular Neuroscience, having authored 34 papers that have together received 1.1k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (11 papers), Quinazolinone synthesis and applications (7 papers), Renin-Angiotensin System Studies (7 papers), Peptidase Inhibition and Analysis (5 papers), Cell Adhesion Molecules Research (5 papers), Neuropeptides and Animal Physiology (5 papers), Chemical Synthesis and Analysis (3 papers) and Synthesis and Biological Activity (3 papers). The work is most often cited by research in Organic Chemistry (624 citations), Endocrinology, Diabetes and Metabolism (129 citations), Molecular Biology (538 citations), Immunology and Allergy (33 citations) and Cardiology and Cardiovascular Medicine (87 citations). Stephen E. de Laszlo has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Paul G. Williard, William K. Hagmann, Malcolm MacCoss, Margaret A. Cascieri, Nathan B. Mantlo, William J. Greenlee, Raymond S.L. Chang, Gregory Koch, Victor J. Lotti and Arthur A. Patchett. Their work appears in journals such as Bioorganic & Medicinal Chemistry Letters, Tetrahedron Letters, The Journal of Organic Chemistry, Biochemistry and Journal of Medicinal 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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