Rauf Latif
- Endocrinology, Diabetes and Metabolism top 0.5%
- Molecular Biology top 10%
- Pathology and Forensic Medicine top 2%
- Genetics top 5%
- Physiology top 10%
- Co-authors
- Terry F. DaviesSyed A. MorshedRisheng MaRussell MariansTakao AndoPeter N. GravesMone ZaidiYuji Nagayama
- Topics
- Thyroid Disorders and Treatments (41 papers)Receptor Mechanisms and Signaling (17 papers)Growth Hormone and Insulin-like Growth Factors (15 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of Biological ChemistryJournal of Clinical Investigation
- Partner nations
- United StatesAustraliaJapan
In The Last Decade
Rauf Latif
84 papers receiving 3.0k citations
Hit Papers
Peers
Comparison fields: 5 of 110
- Endocrinology, Diabetes and Metabolism 1.8k
- Molecular Biology 1.2k
- Pathology and Forensic Medicine 551
- Genetics 511
- Physiology 331
Countries citing papers authored by Rauf Latif
This map shows the geographic impact of Rauf Latif'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 Rauf Latif with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rauf Latif more than expected).
Fields of papers citing papers by Rauf Latif
This network shows the impact of papers produced by Rauf Latif. 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 Rauf Latif. The network helps show where Rauf Latif may publish in the future.
Co-authorship network of co-authors of Rauf Latif
This figure shows the co-authorship network connecting the top 25 collaborators of Rauf Latif. A scholar is included among the top collaborators of Rauf Latif 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 Rauf Latif. Rauf Latif is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 7 | |
| 4 | 16 | |
| 5 | 4 | |
| 6 | 10 | |
| 7 | 7 | |
| 8 | Graves’ diseasebreakdown → | 243 |
| 9 | 19 | |
| 10 | 45 | |
| 11 | 116 | |
| 12 | 49 | |
| 13 | 36 | |
| 14 | 127 | |
| 15 | 68 | |
| 16 | 16 | |
| 17 | 139 | |
| 18 | 71 | |
| 19 | 172 | |
| 20 | 104 |
About Rauf Latif
Rauf Latif is a scholar working on Endocrinology, Diabetes and Metabolism, Genetics and Molecular Biology, having authored 84 papers that have together received 3.1k indexed citations. Recurring topics across this work include Thyroid Disorders and Treatments (41 papers), Receptor Mechanisms and Signaling (17 papers) and Growth Hormone and Insulin-like Growth Factors (15 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (1.8k citations), Pathology and Forensic Medicine (551 citations) and Genetics (511 citations). Rauf Latif has collaborated with scholars based in United States, Australia and Japan. Frequent co-authors include Terry F. Davies, Syed A. Morshed, Risheng Ma, Russell Marians, Takao Ando, Peter N. Graves, Mone Zaidi, Yuji Nagayama, Xiao‐Ming Yin and Mihaly Mezei. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Investigation.
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.