Samar P. Shah

2.5k total citations · 1 hit paper
9 papers, 1.3k citations indexed

About

Samar P. Shah is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Samar P. Shah has authored 9 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Pulmonary and Respiratory Medicine and 2 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Samar P. Shah's work include RNA Research and Splicing (3 papers), RNA modifications and cancer (2 papers) and Neonatal Respiratory Health Research (2 papers). Samar P. Shah is often cited by papers focused on RNA Research and Splicing (3 papers), RNA modifications and cancer (2 papers) and Neonatal Respiratory Health Research (2 papers). Samar P. Shah collaborates with scholars based in United States, Russia and Canada. Samar P. Shah's co-authors include George Q. Daley, Gen Shinoda, Hao Zhu, Ng Shyh‐Chang, Ayumu Takeuchi, William S. Einhorn, Richard I. Gregory, John P. Hagan, David Altshuler and Michael G. Kharas and has published in prestigious journals such as Cell, Nature Genetics and Cancer Cell.

In The Last Decade

Samar P. Shah

9 papers receiving 1.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

The Lin28/let-7 Axis Regulates Glucose Metabolism

2011 724 citations Hao Zhu, Ng Shyh‐Chang et al. Cell profile →

Peers

Samar P. Shah

MB

CR

IMMUN

PHYSI

SURGE

William S. Einhorn United States

Shuling Zhou China

Martin Hart Germany

Motohiko Oshima Japan

Karl Worm Germany

Christoph Schorl United States

Fumiko Saito-Ohara Japan

Charlie Degui Chen China

Tony E. Chavarria United States

William S. Einhorn United States

Samar P. Shah

912 ×1.0

MB

548 ×0.9

CR

111 ×1.0

IMMUN

73 ×0.7

PHYSI

82 ×0.9

SURGE

Citations per year, relative to Samar P. Shah Samar P. Shah (= 1×) peers William S. Einhorn

Countries citing papers authored by Samar P. Shah

Since Specialization

Citations

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

Fields of papers citing papers by Samar P. Shah

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Samar P. Shah

This figure shows the co-authorship network connecting the top 25 collaborators of Samar P. Shah. A scholar is included among the top collaborators of Samar P. 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 Samar P. Shah. Samar P. 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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9 of 9 papers shown

1.

Shah, Samar P., Zainab Bibi, Saeed Ahmad, et al.. (2024). Association of Caffeine Daily Dose With Respiratory Outcomes in Preterm Neonates: A Retrospective Cohort Study. INQUIRY The Journal of Health Care Organization Provision and Financing. 61. 2876841826–2876841826. 1 indexed citations

2.

Shah, Amit, et al.. (2023). Images: Caffeine therapy for central sleep apnea, hypoxemia, and hypoventilation in a term neonate. Journal of Clinical Sleep Medicine. 19(5). 1005–1008. 1 indexed citations

3.

Shah, Samar P., Jocelyn R. Grunwell, Jennifer Shih, Susan T. Stephenson, & Anne M. Fitzpatrick. (2019). Exploring the Utility of Noninvasive Type 2 Inflammatory Markers for Prediction of Severe Asthma Exacerbations in Children and Adolescents. The Journal of Allergy and Clinical Immunology In Practice. 7(8). 2624–2633.e2. 26 indexed citations

4.

Nguyen, Liem H., Daisy A. Robinton, Marc T. Seligson, et al.. (2014). Lin28b Is Sufficient to Drive Liver Cancer and Necessary for Its Maintenance in Murine Models. Cancer Cell. 26(2). 248–261. 157 indexed citations

5.

Tsukada, Takehiro, Stefanie M. Novak, Maxim V. Dorovkov, et al.. (2014). Phosphorylation of tropomodulin1 contributes to the regulation of actin filament architecture in cardiac muscle. The FASEB Journal. 28(9). 3987–3995. 8 indexed citations

6.

Shinoda, Gen, Ng Shyh‐Chang, T. Yvanka de Soysa, et al.. (2013). Fetal Deficiency of Lin28 Programs Life-Long Aberrations in Growth and Glucose Metabolism. Stem Cells. 31(8). 1563–1573. 99 indexed citations

7.

Zhu, Hao, Ng Shyh‐Chang, Ayellet V. Segrè, et al.. (2011). The Lin28/let-7 Axis Regulates Glucose Metabolism. Cell. 147(1). 81–94. 724 indexed citations breakdown →

8.

Uversky, Vladimir N., et al.. (2011). Systematic analysis of tropomodulin/tropomyosin interactions uncovers fine‐tuned binding specificity of intrinsically disordered proteins. Journal of Molecular Recognition. 24(4). 647–655. 34 indexed citations

9.

Zhu, Hao, Samar P. Shah, Ng Shyh‐Chang, et al.. (2010). Lin28a transgenic mice manifest size and puberty phenotypes identified in human genetic association studies. Nature Genetics. 42(7). 626–630. 247 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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