Geda Unabia
- Endocrinology, Diabetes and Metabolism top 2%
- Molecular Biology
- Physiology top 5%
- Cellular and Molecular Neuroscience top 5%
- Pathology and Forensic Medicine top 5%
- Co-authors
- Gwen V. ChildsClaire E. HulseboschYoung Seob GwakJonghoon KangJonathan M. LloydKathia M. JohnsonJ. R. Perez‐PoloKarin N. Westlund
- Topics
- Growth Hormone and Insulin-like Growth Factors (17 papers)Reproductive Biology and Fertility (10 papers)Stress Responses and Cortisol (9 papers)
- Journals
- PainEndocrinologyNeuroscience
- Partner nations
- United StatesVietnamGermany
In The Last Decade
Geda Unabia
42 papers receiving 2.1k citations
Peers
Comparison fields: 5 of 105
- Endocrinology, Diabetes and Metabolism 629
- Molecular Biology 591
- Physiology 491
- Cellular and Molecular Neuroscience 387
- Pathology and Forensic Medicine 382
Countries citing papers authored by Geda Unabia
This map shows the geographic impact of Geda Unabia'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 Geda Unabia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Geda Unabia more than expected).
Fields of papers citing papers by Geda Unabia
This network shows the impact of papers produced by Geda Unabia. 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 Geda Unabia. The network helps show where Geda Unabia may publish in the future.
Co-authorship network of co-authors of Geda Unabia
This figure shows the co-authorship network connecting the top 25 collaborators of Geda Unabia. A scholar is included among the top collaborators of Geda Unabia 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 Geda Unabia. Geda Unabia is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 83 | |
| 2 | 214 | |
| 3 | 29 | |
| 4 | 47 | |
| 5 | 138 | |
| 6 | 29 | |
| 7 | 24 | |
| 8 | 33 | |
| 9 | 74 | |
| 10 | 27 | |
| 11 | 17 | |
| 12 | 33 | |
| 13 | 13 | |
| 14 | 35 | |
| 15 | 51 | |
| 16 | 31 | |
| 17 | 44 | |
| 18 | 59 | |
| 19 | Identification of Living Pituitary Cells with Biotin-Labeled Ligands and Avidin Fluorescein. | 1 |
| 20 | 25 |
About Geda Unabia
Geda Unabia is a scholar working on Behavioral Neuroscience, Endocrinology, Diabetes and Metabolism and Reproductive Medicine, having authored 43 papers that have together received 2.2k indexed citations. Recurring topics across this work include Growth Hormone and Insulin-like Growth Factors (17 papers), Reproductive Biology and Fertility (10 papers) and Stress Responses and Cortisol (9 papers). The work is most often cited by research in Behavioral Neuroscience (226 citations), Endocrinology, Diabetes and Metabolism (629 citations) and Reproductive Medicine (319 citations). Geda Unabia has collaborated with scholars based in United States, Vietnam and Germany. Frequent co-authors include Gwen V. Childs, Claire E. Hulsebosch, Young Seob Gwak, Jonghoon Kang, Jonathan M. Lloyd, Kathia M. Johnson, J. R. Perez‐Polo, Karin N. Westlund, Ping Wu and William W. Chin. Their work appears in journals such as Pain, Endocrinology and Neuroscience.
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.