Premal Shah

2.8k total citations
41 papers, 1.7k citations indexed

About

Premal Shah is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Premal Shah has authored 41 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Molecular Biology, 12 papers in Genetics and 6 papers in Cancer Research. Recurrent topics in Premal Shah's work include RNA and protein synthesis mechanisms (24 papers), RNA modifications and cancer (20 papers) and Genomics and Phylogenetic Studies (14 papers). Premal Shah is often cited by papers focused on RNA and protein synthesis mechanisms (24 papers), RNA modifications and cancer (20 papers) and Genomics and Phylogenetic Studies (14 papers). Premal Shah collaborates with scholars based in United States, Netherlands and United Kingdom. Premal Shah's co-authors include Joshua B. Plotkin, Michael A. Gilchrist, Yang Ding, Grzegorz Kudla, David M. McCandlish, David E. Weinberg, Jeffrey A. Hussmann, David P. Bartel, Stephen W. Eichhorn and Yi Liu and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Premal Shah

39 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Premal Shah United States 19 1.4k 340 89 87 61 41 1.7k
Bjarne Knudsen Denmark 18 1.2k 0.9× 226 0.7× 149 1.7× 127 1.5× 173 2.8× 29 1.6k
Karol Szafranski Germany 25 1.3k 0.9× 216 0.6× 194 2.2× 251 2.9× 108 1.8× 65 1.9k
Michael J. Bozzella United States 8 1.1k 0.8× 208 0.6× 75 0.8× 88 1.0× 171 2.8× 12 1.5k
Alison J. Coffey United Kingdom 9 883 0.6× 491 1.4× 98 1.1× 178 2.0× 186 3.0× 11 1.3k
Corinna Herrnstadt United States 15 1.1k 0.8× 655 1.9× 113 1.3× 122 1.4× 27 0.4× 16 1.6k
Jessica Alföldi United States 11 488 0.4× 307 0.9× 78 0.9× 119 1.4× 65 1.1× 12 793
Eleanor Howard United Kingdom 3 551 0.4× 364 1.1× 98 1.1× 135 1.6× 152 2.5× 3 862
Janet Chênevert France 18 1.2k 0.9× 156 0.5× 54 0.6× 118 1.4× 22 0.4× 43 1.6k
Egor Prokhortchouk Russia 19 1.5k 1.1× 511 1.5× 65 0.7× 152 1.7× 127 2.1× 70 1.9k
Kathleen T. Xie United States 6 920 0.7× 148 0.4× 47 0.5× 205 2.4× 121 2.0× 7 1.4k

Countries citing papers authored by Premal Shah

Since Specialization
Citations

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

Fields of papers citing papers by Premal Shah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Premal Shah

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

All Works

20 of 20 papers shown
1.
2.
Ratman, Dariusz, Michael G. Levin, Jiayi Sun, et al.. (2025). Polygenic risk scores improve CAD risk prediction in individuals at borderline and intermediate clinical risk. PubMed. 2(1). 2 indexed citations
3.
Morishita, Yoshikazu, Ko Zushida, Akinori Nishi, et al.. (2024). Dopamine release and dopamine-related gene expression in the amygdala are modulated by the gastrin-releasing peptide in opposite directions during stress-enhanced fear learning and extinction. Molecular Psychiatry. 30(6). 2381–2394. 1 indexed citations
4.
Danan, Charles, Katharina E. Hayer, Emily A. McMillan, et al.. (2023). Intestinal transit-amplifying cells require METTL3 for growth factor signaling and cell survival. JCI Insight. 8(23). 4 indexed citations
5.
Salamon, Iva, Yongkyu Park, Paul G. Matteson, et al.. (2023). Celf4 controls mRNA translation underlying synaptic development in the prenatal mammalian neocortex. Nature Communications. 14(1). 6025–6025. 15 indexed citations
6.
Sharma, Sunny, et al.. (2023). NADcapPro and circNC: methods for accurate profiling of NAD and non-canonical RNA caps in eukaryotes. Communications Biology. 6(1). 406–406. 8 indexed citations
7.
Jackson, Michael, Amanda Mok, Junchen Liu, et al.. (2022). riboviz 2: a flexible and robust ribosome profiling data analysis and visualization workflow. Bioinformatics. 38(8). 2358–2360. 4 indexed citations
8.
Nikonorova, Inna A., et al.. (2022). Isolation, profiling, and tracking of extracellular vesicle cargo in Caenorhabditis elegans. Current Biology. 32(9). 1924–1936.e6. 29 indexed citations
9.
Vora, Mehul, et al.. (2022). The hypoxia response pathway promotes PEP carboxykinase and gluconeogenesis in C. elegans. Nature Communications. 13(1). 6168–6168. 21 indexed citations
10.
11.
Li, Lingting, Yuanchao Zhang, Irina O. Vvedenskaya, et al.. (2021). Promoter-sequence determinants and structural basis of primer-dependent transcription initiation in Escherichia coli. Proceedings of the National Academy of Sciences. 118(27). 7 indexed citations
12.
Yadavalli, Srujana S., et al.. (2021). Exploring Ribosome-Positioning on Translating Transcripts with Ribosome Profiling. Methods in molecular biology. 2404. 83–110. 5 indexed citations
13.
Campos, Rafael K., H. R. Sagara Wijeratne, Premal Shah, Mariano A. García-Blanco, & Shelton S. Bradrick. (2020). Ribosomal stalk proteins RPLP1 and RPLP2 promote biogenesis of flaviviral and cellular multi-pass transmembrane proteins. Nucleic Acids Research. 48(17). 9872–9885. 21 indexed citations
14.
Holmes, Michael J., Premal Shah, Ronald C. Wek, & William J. Sullivan. (2019). Simultaneous Ribosome Profiling of Human Host Cells Infected with Toxoplasma gondii. mSphere. 4(3). 14 indexed citations
15.
Chatterji, Priya, Patrick A. Williams, Kelly A. Whelan, et al.. (2019). Posttranscriptional regulation of colonic epithelial repair by RNA binding protein IMP 1/ IGF 2 BP 1. EMBO Reports. 20(6). e47074–e47074. 23 indexed citations
16.
Carja, Oana, Tongji Xing, Edward W. Wallace, Joshua B. Plotkin, & Premal Shah. (2017). riboviz: analysis and visualization of ribosome profiling datasets. BMC Bioinformatics. 18(1). 461–461. 28 indexed citations
17.
McCandlish, David M., Premal Shah, & Joshua B. Plotkin. (2016). Epistasis and the Dynamics of Reversion in Molecular Evolution. Genetics. 203(3). 1335–1351. 32 indexed citations
18.
Shah, Premal, et al.. (2013). Rate-Limiting Steps in Yeast Protein Translation. Cell. 153(7). 1589–1601. 334 indexed citations
19.
Xu, Yao, Peijun Ma, Premal Shah, et al.. (2013). Non-optimal codon usage is a mechanism to achieve circadian clock conditionality. Nature. 495(7439). 116–120. 136 indexed citations
20.
Shore, Eileen M., Meiqi Xu, Premal Shah, et al.. (1998). The Human Bone Morphogenetic Protein 4 (BMP-4) Gene: Molecular Structure and Transcriptional Regulation. Calcified Tissue International. 63(3). 221–229. 43 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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Breakdown of academic impact, for papers by Bjarne Knudsen Breakdown of academic impact, for papers by Karol Szafranski Breakdown of academic impact, for papers by Michael J. Bozzella Breakdown of academic impact, for papers by Alison J. Coffey Breakdown of academic impact, for papers by Corinna Herrnstadt Breakdown of academic impact, for papers by Jessica Alföldi Breakdown of academic impact, for papers by Eleanor Howard Breakdown of academic impact, for papers by Janet Chênevert Breakdown of academic impact, for papers by Egor Prokhortchouk Breakdown of academic impact, for papers by Kathleen T. Xie
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