Ayesh D. Perera

613 citations
17 papers · 453 · h-index 12

Impact in

Papers in

Ayesh D. Perera

17 papers receiving 445 citations

Peers

Ayesh D. Perera
Comparison fields: 5 of 64
  • Reproductive Medicine 172
  • Endocrine and Autonomic Systems 89
  • Developmental Neuroscience 28
  • Behavioral Neuroscience 24
  • Endocrinology, Diabetes and Metabolism 75
Replace Masakatsu Kato with:
Masakatsu Kato Japan
Louis DePalatis United States
A Lauber United States
M. Joffre France
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Masataka Shiino United States
Jeffrey Schwartz United States
Lynn P. Chorich United States
Susan R. Fox United States
Céline Rouget France
Ayesh D. Perera relative to Masakatsu Kato Japan Masakatsu Kato's profile →
Citations per field
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Citations per year

Countries citing papers authored by Ayesh D. Perera

Since Specialization
Citations

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

Fields of papers citing papers by Ayesh D. Perera

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ayesh D. Perera. 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 Ayesh D. Perera. The network helps show where Ayesh D. Perera may publish in the future.

Co-authors

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

All Works

17 of 17 papers shown
#Work
1 199465
2 200250
3 199347
4 200341
5 199540
6 199237
7
Requirement for the von Hippel-Lindau tumor suppressor gene for functional epidermal growth factor receptor blockade by monoclonal antibody C225 in renal cell carcinoma.
200037
8 199736
9 199323
10 199920
11 199317
12 199214
13 200410
14 19937
15 20174
16 20164
17 20071

About Ayesh D. Perera

Ayesh D. Perera is a scholar working on Reproductive Medicine, Molecular Biology, Social Psychology, Pulmonary and Respiratory Medicine and Endocrine and Autonomic Systems, having authored 17 papers that have together received 453 indexed citations. Recurring topics across this work include Hypothalamic control of reproductive hormones (9 papers), Neuroendocrine regulation and behavior (5 papers), Inhalation and Respiratory Drug Delivery (3 papers), Growth Hormone and Insulin-like Growth Factors (3 papers), Stress Responses and Cortisol (3 papers), Circadian rhythm and melatonin (2 papers), Plant Reproductive Biology (2 papers) and Monoclonal and Polyclonal Antibodies Research (2 papers). The work is most often cited by research in Reproductive Medicine (172 citations), Endocrine and Autonomic Systems (89 citations), Developmental Neuroscience (28 citations), Behavioral Neuroscience (24 citations) and Endocrinology, Diabetes and Metabolism (75 citations). Ayesh D. Perera has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Tony M. Plant, B. K. Follett, T. M. Plant, Paul C. Goldsmith, Khushdev K. Thind, Carl F. Lagenaur, Cheryl L. Walker, Elena Kleymenova, Д. А. Шапиро and Robert Fishman. Their work appears in journals such as Endocrinology, Journal of Clinical Oncology, Diabetes Care, Diabetes Technology & Therapeutics and The Journal of Comparative Neurology.

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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