Rina J. Mepani

3.7k total citations · 1 hit paper
8 papers, 2.5k citations indexed

About

Rina J. Mepani is a scholar working on Molecular Biology, Physiology and Epidemiology. According to data from OpenAlex, Rina J. Mepani has authored 8 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 5 papers in Physiology and 3 papers in Epidemiology. Recurrent topics in Rina J. Mepani's work include Adipose Tissue and Metabolism (5 papers), Adipokines, Inflammation, and Metabolic Diseases (3 papers) and CRISPR and Genetic Engineering (3 papers). Rina J. Mepani is often cited by papers focused on Adipose Tissue and Metabolism (5 papers), Adipokines, Inflammation, and Metabolic Diseases (3 papers) and CRISPR and Genetic Engineering (3 papers). Rina J. Mepani collaborates with scholars based in United States, Ukraine and Italy. Rina J. Mepani's co-authors include Bruce M. Spiegelman, Sandra Kleiner, Jun Wu, Nicholas Douris, Alexei Kharitonenkov, Jeffrey S. Flier, Ffolliott M. Fisher, Francisco Verdeguer, Eleftheria Maratos–Flier and Li Ye and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Rina J. Mepani

7 papers receiving 2.5k citations

Hit Papers

FGF21 regulates PGC-1α and browning of white adipose tiss... 2012 2026 2016 2021 2012 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rina J. Mepani United States 6 1.7k 1.0k 1000 385 260 8 2.5k
Elayne Hondares Spain 19 1.7k 1.0× 1.5k 1.5× 912 0.9× 430 1.1× 252 1.0× 20 2.9k
Kathleen R. Markan United States 16 1.6k 0.9× 1.3k 1.3× 915 0.9× 398 1.0× 304 1.2× 19 2.9k
Haruya Ohno Japan 20 1.5k 0.9× 618 0.6× 889 0.9× 374 1.0× 345 1.3× 67 2.2k
Matthew Harms United States 15 2.4k 1.4× 752 0.7× 1.4k 1.4× 555 1.4× 421 1.6× 19 3.0k
Takamasa Higashimori United States 13 1.3k 0.8× 1.1k 1.1× 766 0.8× 253 0.7× 106 0.4× 15 2.3k
Ruidan Xue United States 13 1.3k 0.8× 410 0.4× 735 0.7× 320 0.8× 287 1.1× 14 1.6k
Matthias Johannes Betz Switzerland 20 1.3k 0.8× 355 0.3× 574 0.6× 408 1.1× 266 1.0× 48 1.9k
Alexander W. Fischer Germany 21 1.1k 0.7× 506 0.5× 507 0.5× 231 0.6× 213 0.8× 38 1.7k
Sandra Kleiner United States 18 2.6k 1.5× 1.9k 1.9× 1.2k 1.2× 588 1.5× 447 1.7× 27 4.1k
Rohit N. Kulkarni United States 19 1.3k 0.8× 1.0k 1.0× 710 0.7× 277 0.7× 123 0.5× 33 2.4k

Countries citing papers authored by Rina J. Mepani

Since Specialization
Citations

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

Fields of papers citing papers by Rina J. Mepani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rina J. Mepani. 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 Rina J. Mepani. The network helps show where Rina J. Mepani may publish in the future.

Co-authorship network of co-authors of Rina J. Mepani

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

All Works

8 of 8 papers shown
1.
Gowen, Benjamin G., Jean L. Chan, Aaron J. Cantor, et al.. (2024). Identification of a Guide RNA Targeting an Ultraconserved Element for Evaluation of Cas9 Genome Editors Across Mammalian Species. The CRISPR Journal. 7(6). 306–309.
2.
Maeder, Morgan L., Rina J. Mepani, Sebastian Gloskowski, et al.. (2016). 124. Therapeutic Correction of an LCA-Causing Splice Defect in the CEP290 Gene by CRISPR/Cas-Mediated Gene Editing. Molecular Therapy. 24. S51–S52. 4 indexed citations
3.
Maeder, Morgan L., Shen Shen, Erin R. Burnight, et al.. (2015). 687. Therapeutic Correction of an LCA-Causing Splice Defect in the CEP290 Gene by CRISPR/Cas-Mediated Genome Editing. Molecular Therapy. 23. S273–S274. 9 indexed citations
4.
Ye, Li, Sandra Kleiner, Jun Wu, et al.. (2012). TRPV4 Is a Regulator of Adipose Oxidative Metabolism, Inflammation, and Energy Homeostasis. Cell. 151(1). 96–110. 279 indexed citations
5.
Gupta, Rana K., Rina J. Mepani, Sandra Kleiner, et al.. (2012). Zfp423 Expression Identifies Committed Preadipocytes and Localizes to Adipose Endothelial and Perivascular Cells. Cell Metabolism. 15(2). 230–239. 327 indexed citations
6.
Fisher, Ffolliott M., Sandra Kleiner, Nicholas Douris, et al.. (2012). FGF21 regulates PGC-1α and browning of white adipose tissues in adaptive thermogenesis. Genes & Development. 26(3). 271–281. 1237 indexed citations breakdown →
7.
Kleiner, Sandra, Rina J. Mepani, Dina Laznik, et al.. (2012). Development of insulin resistance in mice lacking PGC-1α in adipose tissues. Proceedings of the National Academy of Sciences. 109(24). 9635–9640. 247 indexed citations
8.
Gupta, Rana K., Zoltàn Arany, Patrick Seale, et al.. (2010). Transcriptional control of preadipocyte determination by Zfp423. Nature. 464(7288). 619–623. 416 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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