Maryam Nasiri
- Endocrinology, Diabetes and Metabolism top 5%
- Epidemiology top 10%
- Molecular Biology
- Surgery
- Physiology
- Co-authors
- Jeremy TomlinsonMatthew J. ArmstrongLaura GathercoleJonathan HazlehurstJinglei YuPhilip N. NewsomeDiana HullKathy Guo
- Topics
- COVID-19 Clinical Research Studies (5 papers)Liver Disease Diagnosis and Treatment (4 papers)Diet, Metabolism, and Disease (3 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEHepatology
- Partner nations
- IranUnited KingdomNetherlands
In The Last Decade
Maryam Nasiri
22 papers receiving 587 citations
Hit Papers
Peers
Comparison fields: 5 of 91
- Endocrinology, Diabetes and Metabolism 362
- Epidemiology 333
- Molecular Biology 124
- Surgery 117
- Physiology 105
Countries citing papers authored by Maryam Nasiri
This map shows the geographic impact of Maryam Nasiri'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 Maryam Nasiri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maryam Nasiri more than expected).
Fields of papers citing papers by Maryam Nasiri
This network shows the impact of papers produced by Maryam Nasiri. 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 Maryam Nasiri. The network helps show where Maryam Nasiri may publish in the future.
Co-authorship network of co-authors of Maryam Nasiri
This figure shows the co-authorship network connecting the top 25 collaborators of Maryam Nasiri. A scholar is included among the top collaborators of Maryam Nasiri 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 Maryam Nasiri. Maryam Nasiri 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 | 0 | |
| 3 | 3 | |
| 4 | 3 | |
| 5 | 2 | |
| 6 | 6 | |
| 7 | 13 | |
| 8 | 4 | |
| 9 | 2 | |
| 10 | 29 | |
| 11 | 1 | |
| 12 | 6 | |
| 13 | 3 | |
| 14 | 38 | |
| 15 | Glucagon-like peptide 1 decreases lipotoxicity in non-alcoholic steatohepatitisbreakdown → | 351 |
| 16 | 1 | |
| 17 | Association of G-2548A Polymorphism in the Promoter of Leptin Gene with Plasma Leptin Level and Risk of Type 2 Diabetes | 5 |
| 18 | Glucagon like peptide 1 analogue, Liraglutide, reduces adipose insulin resistance and hepatic de novo lipogenesis in Nonalcoholic Steatohepatitis: Sub-study results of a phase II randomised-control clinical trial | 1 |
| 19 | 51 | |
| 20 | 4 |
About Maryam Nasiri
Maryam Nasiri is a scholar working on Endocrinology, Diabetes and Metabolism, Infectious Diseases and Small Animals, having authored 23 papers that have together received 598 indexed citations. Recurring topics across this work include COVID-19 Clinical Research Studies (5 papers), Liver Disease Diagnosis and Treatment (4 papers) and Diet, Metabolism, and Disease (3 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (362 citations), Epidemiology (333 citations) and Hepatology (44 citations). Maryam Nasiri has collaborated with scholars based in Iran, United Kingdom and Netherlands. Frequent co-authors include Jeremy Tomlinson, Matthew J. Armstrong, Laura Gathercole, Jonathan Hazlehurst, Jinglei Yu, Philip N. Newsome, Diana Hull, Kathy Guo, Stephen Gough and Darren Barton. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Hepatology.
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.