Ryun S. Ahn

1.3k total citations
44 papers, 1.0k citations indexed

About

Ryun S. Ahn is a scholar working on Behavioral Neuroscience, Endocrinology, Diabetes and Metabolism and Reproductive Medicine. According to data from OpenAlex, Ryun S. Ahn has authored 44 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Behavioral Neuroscience, 12 papers in Endocrinology, Diabetes and Metabolism and 12 papers in Reproductive Medicine. Recurrent topics in Ryun S. Ahn's work include Stress Responses and Cortisol (16 papers), Reproductive biology and impacts on aquatic species (11 papers) and Sperm and Testicular Function (6 papers). Ryun S. Ahn is often cited by papers focused on Stress Responses and Cortisol (16 papers), Reproductive biology and impacts on aquatic species (11 papers) and Sperm and Testicular Function (6 papers). Ryun S. Ahn collaborates with scholars based in South Korea, United States and United Kingdom. Ryun S. Ahn's co-authors include Hyuk Bang Kwon, Jae Young Seong, Jun Young Choi, Da Young Oh, Jaemog Soh, Hueng-Sik Choi, Keesook Lee, Chul‐Ho Lee, Yong Deuk Kim and Eunsook Park and has published in prestigious journals such as Journal of Biological Chemistry, PLoS ONE and Biochemical and Biophysical Research Communications.

In The Last Decade

Ryun S. Ahn

42 papers receiving 1.0k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ryun S. Ahn South Korea 20 189 183 177 165 133 44 1.0k
Fabio Bianchi United Kingdom 13 245 1.3× 156 0.9× 318 1.8× 206 1.2× 183 1.4× 21 1.5k
Ana Paula Tanno Brazil 8 247 1.3× 262 1.4× 189 1.1× 220 1.3× 196 1.5× 13 1.4k
Elizabeth C. Cottrell United Kingdom 18 126 0.7× 172 0.9× 257 1.5× 233 1.4× 329 2.5× 40 1.6k
Shannon Whirledge United States 16 324 1.7× 177 1.0× 132 0.7× 218 1.3× 102 0.8× 34 1.2k
Kathleen S. Curtis United States 18 202 1.1× 195 1.1× 93 0.5× 201 1.2× 177 1.3× 54 1.2k
S. J. Nazian United States 18 361 1.9× 214 1.2× 194 1.1× 81 0.5× 154 1.2× 62 1.1k
Roberto Chavira Mexico 22 292 1.5× 186 1.0× 115 0.6× 236 1.4× 101 0.8× 61 1.2k
A. Wozniak United Kingdom 15 211 1.1× 207 1.1× 93 0.5× 163 1.0× 92 0.7× 16 936
Klaudia Barabás Hungary 13 260 1.4× 114 0.6× 199 1.1× 94 0.6× 90 0.7× 33 1.2k
Klara Szigeti‐Buck United States 16 72 0.4× 90 0.5× 359 2.0× 163 1.0× 305 2.3× 21 2.2k

Countries citing papers authored by Ryun S. Ahn

Since Specialization
Citations

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

Fields of papers citing papers by Ryun S. Ahn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ryun S. Ahn. 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 Ryun S. Ahn. The network helps show where Ryun S. Ahn may publish in the future.

Co-authorship network of co-authors of Ryun S. Ahn

This figure shows the co-authorship network connecting the top 25 collaborators of Ryun S. Ahn. A scholar is included among the top collaborators of Ryun S. Ahn 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 Ryun S. Ahn. Ryun S. Ahn is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Jang, Sooah, Anna Lee, Manjae Kwon, et al.. (2024). Exploratory Clinical Trial of a Depression Diagnostic Software That Integrates Stress Biomarkers and Composite Psychometrics. Psychiatry Investigation. 21(3). 230–241. 2 indexed citations
2.
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Oh, In‐Jae, Kyu-Sik Kim, Young Chul Kim, et al.. (2018). Altered Hypothalamus-Pituitary-Adrenal Axis Function: A Potential Underlying Biological Pathway for Multiple Concurrent Symptoms in Patients With Advanced Lung Cancer. Psychosomatic Medicine. 81(1). 41–50. 15 indexed citations
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Pomykala, Kelsey L., Patricia A. Ganz, Julienne E. Bower, et al.. (2013). The association between pro-inflammatory cytokines, regional cerebral metabolism, and cognitive complaints following adjuvant chemotherapy for breast cancer. Brain Imaging and Behavior. 7(4). 511–523. 100 indexed citations
7.
Tadi, Surendar, Balachandar Nedumaran, Yong Deuk Kim, et al.. (2012). Phosphoenolpyruvate Carboxykinase and Glucose-6-phosphatase Are Required for Steroidogenesis in Testicular Leydig Cells. Journal of Biological Chemistry. 287(50). 41875–41887. 30 indexed citations
8.
Ahn, Ryun S., et al.. (2012). Hypothalamic–pituitary–adrenal axis function in patients with complex regional pain syndrome type 1. Psychoneuroendocrinology. 37(9). 1557–1568. 12 indexed citations
9.
Park, Eunsook, et al.. (2012). ERα/E2 signaling suppresses the expression of steroidogenic enzyme genes via cross-talk with orphan nuclear receptor Nur77 in the testes. Molecular and Cellular Endocrinology. 362(1-2). 91–103. 23 indexed citations
10.
Ahn, Ryun S., et al.. (2011). Cortisol, estradiol-17β, and progesterone secretion within the first hour after awakening in women with regular menstrual cycles. Journal of Endocrinology. 211(3). 285–295. 28 indexed citations
11.
Ahn, Ryun S., et al.. (2010). Effect of 6-Hydroxydopamine (6-OHDA) on the Expression of Testicular Steroidogenic Genes in Adult Rats. 14(3). 199–205. 4 indexed citations
12.
Chung, Yong Gu, et al.. (2010). Abnormal diurnal pattern of cortisol secretion in patients after aneurysmal subarachnoid hemorrhage. Stress. 14(2). 156–165. 7 indexed citations
13.
Kim, Seungchang, et al.. (2009). Molecular cloning and expression of steroidogenic acute regulatory protein from bullfrog (Rana catesbeiana). General and Comparative Endocrinology. 162(2). 146–152. 3 indexed citations
14.
Lee, Sung-Ho, et al.. (2008). Age-related Changes in Luteinizing Hormone and Testosterone Levels in Korean Men. 12(1). 57–66. 2 indexed citations
15.
Oh, D-Y., et al.. (2004). Molecular cloning, pharmacological characterization, and histochemical distribution of frog vasotocin and mesotocin receptors. Journal of Molecular Endocrinology. 33(1). 293–313. 44 indexed citations
16.
Oh, Da Young, Ryun S. Ahn, Han Choe, et al.. (2004). Identification of Amino Acid Residues That Direct Differential Ligand Selectivity of Mammalian and Nonmammalian V1a Type Receptors for Arginine Vasopressin and Vasotocin. Journal of Biological Chemistry. 279(52). 54445–54453. 36 indexed citations
17.
Kim, Jisun, Cynthia Gomes, Sung‐Dug Oh, et al.. (2004). Effect of ascorbic acid supplementation on testicular steroidogenesis and germ cell death in cadmium-treated male rats. Molecular and Cellular Endocrinology. 221(1-2). 57–66. 95 indexed citations
18.
Oh, Da Young, Li Wang, Ryun S. Ahn, et al.. (2003). Differential G protein coupling preference of mammalian and nonmammalian gonadotropin-releasing hormone receptors. Molecular and Cellular Endocrinology. 205(1-2). 89–98. 33 indexed citations
19.
Ahn, Ryun S., et al.. (1997). Nucleotide Sequence of Rat Steroidogenic Acute Regulatory Protein Complementary DNA. Biochemical and Biophysical Research Communications. 230(3). 528–532. 20 indexed citations
20.
Kwon, Hyuk Bang & Ryun S. Ahn. (1994). Relative Roles of Theca and Granulosa Cells in Ovarian Follicular Steroidogenesis in the Amphibian, Rana nigromaculata. General and Comparative Endocrinology. 94(2). 207–214. 22 indexed citations

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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