K. Lederis

197 papers receiving 6.1k citations

Peers

K. Lederis
Comparison fields: 5 of 124
  • Behavioral Neuroscience 1.7k
  • Endocrine and Autonomic Systems 1.1k
  • Cellular and Molecular Neuroscience 1.8k
  • Social Psychology 1.9k
  • Endocrinology, Diabetes and Metabolism 1.2k
Replace Sergio R. Ojeda with:
Sergio R. Ojeda United States
A. Negro‐Vilar United States
James L. Roberts United States
G. Pelletier Canada
J. Meites United States
J. Rivier United States
John C. Porter United States
Robert L. Eskay United States
Zsolt Liposits Hungary
Claude Kordon France
K. Lederis relative to Sergio R. Ojeda United States Sergio R. Ojeda's profile →
Citations per field
00.5×1.5×
Sergio R. Ojeda · 1×
Citations per year

Countries citing papers authored by K. Lederis

Since Specialization
Citations

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

Fields of papers citing papers by K. Lederis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by K. Lederis. 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 K. Lederis. The network helps show where K. Lederis may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 204 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1987290
2 1986286
3 1982239
4 1979207
5
Neurosecretion : molecules, cells, systems
1981198
6 1989163
7 1994126
8 1982104
9 1966103
10 198795
11 198893
12 198380
13
A reference preparation for the study of active substances in the caudal neurosecretory system of teleosts.
196976
14 196374
15 199571
16 198771
17 195971
18 196571
19 198371
20 196470

About K. Lederis

K. Lederis is a scholar working on Surgery, Social Psychology, Endocrinology, Diabetes and Metabolism, Pharmacology and Behavioral Neuroscience, having authored 204 papers that have together received 6.3k indexed citations. Recurring topics across this work include Cardiovascular, Neuropeptides, and Oxidative Stress Research (78 papers), Neuroendocrine regulation and behavior (60 papers), Hormonal Regulation and Hypertension (51 papers), Apelin-related biomedical research (49 papers), Stress Responses and Cortisol (42 papers), Neuropeptides and Animal Physiology (23 papers), Neuroscience of respiration and sleep (13 papers) and Cardiovascular Disease and Adiposity (13 papers). The work is most often cited by research in Behavioral Neuroscience (1.7k citations), Endocrine and Autonomic Systems (1.1k citations), Cellular and Molecular Neuroscience (1.8k citations), Social Psychology (1.9k citations) and Endocrinology, Diabetes and Metabolism (1.2k citations). K. Lederis has collaborated with scholars based in Canada, Germany and United States. Frequent co-authors include Masahiro Sakanaka, Tamotsu Shibasaki, D. McMaster, James N. Fryer, W. L. Veale, Donald S. Farner, Jean Rivier, Quentin J. Pittman, H. Heller and Morley D. Hollenberg. Their work appears in journals such as Cell and Tissue Research, General and Comparative Endocrinology, Peptides, Canadian Journal of Physiology and Pharmacology and Brain 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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