Chheng-Orn Evans

924 citations
15 papers · 715 indexed · h-index 13
Topics
Pituitary Gland Disorders and Treatments (9 papers)TGF-β signaling in diseases (5 papers)Growth Hormone and Insulin-like Growth Factors (4 papers)

In The Last Decade

Chheng-Orn Evans

15 papers receiving 700 citations

Peers

Chheng-Orn Evans
Comparison fields: 5 of 77
  • Endocrinology, Diabetes and Metabolism 309
  • Molecular Biology 286
  • Epidemiology 149
  • Genetics 111
  • Neurology 111
Replace Carole Auger with:
Carole Auger France
Takashi Kokunai Japan
Hiromichi Nakabayashi Japan
Francesca Lessi Italy
Ram Kumar Selvaraju Sweden
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Jordan Jones Australia
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DeLellis Ra United States
J. Pinski United States
Chheng-Orn Evans relative to Carole Auger France Carole Auger's profile →
Citations per field
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Citations per year

Countries citing papers authored by Chheng-Orn Evans

Since Specialization
Citations

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

Fields of papers citing papers by Chheng-Orn Evans

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chheng-Orn Evans. 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 Chheng-Orn Evans. The network helps show where Chheng-Orn Evans may publish in the future.

Co-authorship network of co-authors of Chheng-Orn Evans

This figure shows the co-authorship network connecting the top 25 collaborators of Chheng-Orn Evans. A scholar is included among the top collaborators of Chheng-Orn Evans based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Chheng-Orn Evans. Chheng-Orn Evans is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

15 of 15 papers shown
#WorkIndexed citations
1 16
2 12
3 71
4 16
5 170
6 36
7
Differential expression of folate receptor in pituitary adenomas.
57
8 121
9 121
10 25
11 15
12 22
13 5
14 5
15 23

About Chheng-Orn Evans

Chheng-Orn Evans is a scholar working on Endocrinology, Diabetes and Metabolism, Virology and Cancer Research, having authored 15 papers that have together received 715 indexed citations. Recurring topics across this work include Pituitary Gland Disorders and Treatments (9 papers), TGF-β signaling in diseases (5 papers) and Growth Hormone and Insulin-like Growth Factors (4 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (309 citations), Developmental Neuroscience (49 citations) and Genetics (111 citations). Chheng-Orn Evans has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Nelson M. Oyesiku, Xianquan Zhan, Dominic M. Desiderio, Carlos S. Moreno, Daniel J. Brat, John S. Parks, Milton R. Brown, Andrew N. Young, Andrew S. Neish and Zoltán Fülöp. Their work appears in journals such as The Journal of Clinical Endocrinology & Metabolism, Cancer Research 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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