Srikumar Sengupta

2.0k total citations
19 papers, 1.6k citations indexed

About

Srikumar Sengupta is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Srikumar Sengupta has authored 19 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 8 papers in Cancer Research and 3 papers in Oncology. Recurrent topics in Srikumar Sengupta's work include Cancer-related molecular mechanisms research (5 papers), RNA and protein synthesis mechanisms (5 papers) and MicroRNA in disease regulation (4 papers). Srikumar Sengupta is often cited by papers focused on Cancer-related molecular mechanisms research (5 papers), RNA and protein synthesis mechanisms (5 papers) and MicroRNA in disease regulation (4 papers). Srikumar Sengupta collaborates with scholars based in United States, Slovakia and Taiwan. Srikumar Sengupta's co-authors include Michael A. Newton, Paul Ahlquist, Johan A. den Boon, Bill Sugden, Allan Hildesheim, I‐How Chen, Yu-Juen Cheng, James A. Thomson, Chien‐Jen Chen and Ron Stewart and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and PLoS ONE.

In The Last Decade

Srikumar Sengupta

19 papers receiving 1.6k citations

Peers

Srikumar Sengupta

MB

CR

ONCOL

EPIDE

IMMUN

Astrid E. Greijer Netherlands

No-Hee Park United States

Daoud Sie Netherlands

Sonia Lameiras France

Seiya Yokoyama Japan

Alice Chuang United States

Susanne Popp Germany

Yoshihiro Yoshitake Japan

Tobias Grob Germany

Rekha V. Kumar India

Astrid E. Greijer Netherlands

Srikumar Sengupta

590 ×0.5

MB

557 ×0.8

CR

648 ×1.9

ONCOL

243 ×1.2

EPIDE

140 ×1.0

IMMUN

Citations per year, relative to Srikumar Sengupta Srikumar Sengupta (= 1×) peers Astrid E. Greijer

Countries citing papers authored by Srikumar Sengupta

Since Specialization

Citations

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

Fields of papers citing papers by Srikumar Sengupta

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Srikumar Sengupta

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

All Works

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19 of 19 papers shown

1.

Sengupta, Srikumar, Scott Swanson, Brian E. McIntosh, et al.. (2022). Rapid changes in chromatin structure during dedifferentiation of primary hepatocytes in vitro. Genomics. 114(3). 110330–110330. 8 indexed citations

2.

Chu, Li‐Fang, Srikumar Sengupta, Ning Leng, et al.. (2020). Reproducibility across single-cell RNA-seq protocols for spatial ordering analysis. PLoS ONE. 15(9). e0239711–e0239711. 4 indexed citations

3.

Sengupta, Srikumar, Brian P. Johnson, Bret Duffin, et al.. (2020). Co-culture with mouse embryonic fibroblasts improves maintenance of metabolic function of human small hepatocyte progenitor cells. Current Research in Toxicology. 1. 70–84. 4 indexed citations

4.

Sengupta, Srikumar, et al.. (2019). 3-D culture and endothelial cells improve maturity of human pluripotent stem cell-derived hepatocytes. Acta Biomaterialia. 95. 371–381. 63 indexed citations

5.

Sengupta, Srikumar, Brian P. Johnson, Scott Swanson, et al.. (2014). Aggregate Culture of Human Embryonic Stem Cell-Derived Hepatocytes in Suspension Are an Improved In Vitro Model for Drug Metabolism and Toxicity Testing. Toxicological Sciences. 140(1). 236–245. 36 indexed citations

6.

Stewart, Ron, Shulan Tian, Jeff Nie, et al.. (2013). Comparative RNA-seq Analysis in the Unsequenced Axolotl: The Oncogene Burst Highlights Early Gene Expression in the Blastema. PLoS Computational Biology. 9(3). e1002936–e1002936. 105 indexed citations

7.

Sengupta, Srikumar, Jennifer M. Bolin, Victor Ruotti, et al.. (2011). Single Read and Paired End mRNA-Seq Illumina Libraries from 10 Nanograms Total RNA. Journal of Visualized Experiments. e3340–e3340. 22 indexed citations

8.

Sengupta, Srikumar, Jennifer M. Bolin, Victor Ruotti, et al.. (2011). Single Read and Paired End mRNA-Seq Illumina Libraries from 10 Nanograms Total RNA. Journal of Visualized Experiments. 4 indexed citations

9.

Sengupta, Srikumar, Victor Ruotti, Jennifer M. Bolin, et al.. (2010). Highly Consistent, Fully Representative mRNA-Seq Libraries from ten Nanograms of Total RNA. BioTechniques. 49(6). 898–904. 17 indexed citations

10.

Sengupta, Srikumar & Anupam Bishayee. (2010). MicroRNAs in Cancer Therapy: From Bench to Bedside. Current Cancer Therapy Reviews. 6(2). 157–162. 2 indexed citations

11.

Stanhope, Stephen A., et al.. (2009). Statistical Use of Argonaute Expression and RISC Assembly in microRNA Target Identification. PLoS Computational Biology. 5(9). e1000516–e1000516. 10 indexed citations

12.

Sengupta, Srikumar, et al.. (2009). The microRNAs of Epstein–Barr Virus are expressed at dramatically differing levels among cell lines. Virology. 386(2). 387–397. 114 indexed citations

13.

Sengupta, Srikumar, et al.. (2009). MicroRNA 92b Controls the G1/S Checkpoint Gene p57 in Human Embryonic Stem Cells. Stem Cells. 27(7). 1524–1528. 100 indexed citations

14.

Wei, Hairong, Pei Fen Kuan, Shulan Tian, et al.. (2008). A study of the relationships between oligonucleotide properties and hybridization signal intensities from NimbleGen microarray datasets. Nucleic Acids Research. 36(9). 2926–2938. 36 indexed citations

15.

Sengupta, Srikumar, Johan A. den Boon, I‐How Chen, et al.. (2008). MicroRNA 29c is down-regulated in nasopharyngeal carcinomas, up-regulating mRNAs encoding extracellular matrix proteins. Proceedings of the National Academy of Sciences. 105(15). 5874–5878. 341 indexed citations

16.

Pyeon, Dohun, Michael A. Newton, Paul F. Lambert, et al.. (2007). Fundamental Differences in Cell Cycle Deregulation in Human Papillomavirus–Positive and Human Papillomavirus–Negative Head/Neck and Cervical Cancers. Cancer Research. 67(10). 4605–4619. 382 indexed citations

17.

Sengupta, Srikumar, Johan A. den Boon, I‐How Chen, et al.. (2006). Genome-Wide Expression Profiling Reveals EBV-Associated Inhibition of MHC Class I Expression in Nasopharyngeal Carcinoma. Cancer Research. 66(16). 7999–8006. 194 indexed citations

18.

Dodd, Lori E., Srikumar Sengupta, I‐How Chen, et al.. (2006). Genes Involved in DNA Repair and Nitrosamine Metabolism and Those Located on Chromosome 14q32 Are Dysregulated in Nasopharyngeal Carcinoma. Cancer Epidemiology Biomarkers & Prevention. 15(11). 2216–2225. 70 indexed citations

19.

Sengupta, Srikumar, et al.. (2003). Molecular Detection and Identification of Influenza Viruses by Oligonucleotide Microarray Hybridization. Journal of Clinical Microbiology. 41(10). 4542–4550. 86 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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