Supriya Shah

54 total papers · 1.7k total citations
20 papers, 846 citations indexed

About

Supriya Shah is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Oncology. According to data from OpenAlex, Supriya Shah has authored 20 papers receiving a total of 846 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 3 papers in Pulmonary and Respiratory Medicine and 3 papers in Oncology. Recurrent topics in Supriya Shah's work include Epigenetics and DNA Methylation (3 papers), Plant tissue culture and regeneration (3 papers) and Photosynthetic Processes and Mechanisms (3 papers). Supriya Shah is often cited by papers focused on Epigenetics and DNA Methylation (3 papers), Plant tissue culture and regeneration (3 papers) and Photosynthetic Processes and Mechanisms (3 papers). Supriya Shah collaborates with scholars based in United States, China and Pakistan. Supriya Shah's co-authors include Debra Hanks, Karina Kulangara, Jonathan Juco, Kenneth Emancipator, Jared Lunceford, Nancy R. Zhang, Jiangdian Wang, Mary J. Savage, Ellie Corigliano and Malinka Jansson and has published in prestigious journals such as Journal of Clinical Oncology, Cancer Research and Nature Chemical Biology.

In The Last Decade

Supriya Shah

20 papers receiving 832 citations

Hit Papers

Clinical Utility of the C... 2018 2026 2020 2023 2018 100 200 300

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Supriya Shah 390 233 226 168 157 20 846
Balraj Mittal 306 0.8× 285 1.2× 184 0.8× 241 1.4× 132 0.8× 43 836
Yuki Obata 252 0.6× 240 1.0× 110 0.5× 224 1.3× 112 0.7× 29 744
Guang‐wei Xu 151 0.4× 285 1.2× 326 1.4× 485 2.9× 108 0.7× 31 1.0k
H. O. Klein 329 0.8× 168 0.7× 374 1.7× 246 1.5× 47 0.3× 39 1.0k
Yuanyu Wu 252 0.6× 507 2.2× 252 1.1× 107 0.6× 353 2.2× 21 957
Jan Hajer 358 0.9× 165 0.7× 221 1.0× 257 1.5× 159 1.0× 24 1.0k
Sang Hyeok Woo 293 0.8× 522 2.2× 272 1.2× 315 1.9× 131 0.8× 36 1.1k
Kah Hoong Chang 351 0.9× 434 1.9× 117 0.5× 251 1.5× 398 2.5× 27 1.0k
William Tzu-Liang Chen 394 1.0× 244 1.0× 133 0.6× 328 2.0× 166 1.1× 35 933
Nektaria Makrilia 325 0.8× 280 1.2× 291 1.3× 126 0.8× 99 0.6× 23 1.0k

Countries citing papers authored by Supriya Shah

Since Specialization
Citations

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

Fields of papers citing papers by Supriya Shah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Supriya Shah. 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 Supriya Shah. The network helps show where Supriya Shah may publish in the future.

Co-authorship network of co-authors of Supriya Shah

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

All Works

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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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