Shekhar Saha

808 total citations
34 papers, 529 citations indexed

About

Shekhar Saha is a scholar working on Molecular Biology, Cancer Research and Cell Biology. According to data from OpenAlex, Shekhar Saha has authored 34 papers receiving a total of 529 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Molecular Biology, 13 papers in Cancer Research and 5 papers in Cell Biology. Recurrent topics in Shekhar Saha's work include Cancer-related molecular mechanisms research (7 papers), RNA Research and Splicing (7 papers) and Muscle Physiology and Disorders (4 papers). Shekhar Saha is often cited by papers focused on Cancer-related molecular mechanisms research (7 papers), RNA Research and Splicing (7 papers) and Muscle Physiology and Disorders (4 papers). Shekhar Saha collaborates with scholars based in United States, India and Germany. Shekhar Saha's co-authors include Anindya Dutta, Ajay Chatrath, Siddhartha S. Jana, Pankaj Kumar, Zhangli Su, Teressa Paulsen, Shashi Kiran, Yoshiyuki Shibata, Etsuko Shibata and Manjari Kiran and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Investigation and SHILAP Revista de lepidopterología.

In The Last Decade

Shekhar Saha

33 papers receiving 525 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shekhar Saha United States	13	339	240	73	69	47	34	529
Ophélie Meynet France	8	224 0.7×	130 0.5×	73 1.0×	81 1.2×	40 0.9×	9	449
Yian Wang China	9	395 1.2×	226 0.9×	25 0.3×	121 1.8×	22 0.5×	13	630
Daniel P. Sejas United States	10	475 1.4×	130 0.5×	54 0.7×	124 1.8×	14 0.3×	10	641
Christiane Brahimi‐Horn France	7	382 1.1×	346 1.4×	46 0.6×	74 1.1×	32 0.7×	9	584
Charlotte Hellmich United Kingdom	11	320 0.9×	121 0.5×	62 0.8×	80 1.2×	21 0.4×	30	587
Yi-Hui Lin China	9	867 2.6×	151 0.6×	19 0.3×	88 1.3×	17 0.4×	21	1.0k
Krista Rantanen Finland	10	325 1.0×	283 1.2×	30 0.4×	43 0.6×	40 0.9×	11	477
Sébastien Flajollet France	12	333 1.0×	70 0.3×	35 0.5×	80 1.2×	81 1.7×	17	616
Chetan K. Rane United States	8	305 0.9×	60 0.3×	22 0.3×	174 2.5×	61 1.3×	12	512

Countries citing papers authored by Shekhar Saha

Since Specialization

Citations

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

Fields of papers citing papers by Shekhar Saha

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shekhar Saha

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

All Works

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20 of 20 papers shown

Dehghani, Mohammad, et al.. (2024). BIOPROCESS DESIGN AND OPTIMIZATION FOR EXTRACELLULAR VESCILES DERIVED FROM MESENCHYMAL STEM CELLS. Cytotherapy. 26(6). S87–S87.

Zhang, Ying, Shekhar Saha, Myron Gibert, et al.. (2024). The role of microRNAs in brain metastasis. Journal of Neuro-Oncology. 166(2). 231–241. 11 indexed citations

Dinda, Biswanath, et al.. (2024). Therapeutic potential of natural alkaloid emetine against emerging COVID-19 and future viral pandemics. SHILAP Revista de lepidopterología. 12. 100173–100173. 3 indexed citations

Dinda, Manikarna, Shekhar Saha, Zhenjia Wang, et al.. (2023). Fob1-dependent condensin recruitment and loop extrusion on yeast chromosome III. PLoS Genetics. 19(4). e1010705–e1010705. 4 indexed citations

Hanif, Farina, Ying Zhang, Collin Dube, et al.. (2023). miR-3174 Is a New Tumor Suppressor MicroRNA That Inhibits Several Tumor-Promoting Genes in Glioblastoma. International Journal of Molecular Sciences. 24(11). 9326–9326. 1 indexed citations

Jayappa, Kallesh D., Vicki L. Gordon, Christopher G. Morris, et al.. (2023). PP2A modulation overcomes multidrug resistance in chronic lymphocytic leukemia via mPTP-dependent apoptosis. Journal of Clinical Investigation. 133(13). 10 indexed citations

Wilson, Briana, et al.. (2022). tRForest: a novel random forest-based algorithm for tRNA-derived fragment target prediction. NAR Genomics and Bioinformatics. 4(2). lqac037–lqac037. 5 indexed citations

Weidmann, Chase A., Shekhar Saha, Piotr Przanowski, et al.. (2022). Distinct MUNC lncRNA structural domains regulate transcription of different promyogenic factors. Cell Reports. 38(7). 110361–110361. 23 indexed citations

Saha, Shekhar, Ying Zhang, Briana Wilson, Roger Abounader, & Anindya Dutta. (2021). The tumor-suppressive long noncoding RNA DRAIC inhibits protein translation and induces autophagy by activating AMPK. Journal of Cell Science. 134(24). 23 indexed citations

10.

Jayappa, Kallesh D., Vicki L. Gordon, Christopher G. Morris, et al.. (2021). Extrinsic interactions in the microenvironment in vivo activate an antiapoptotic multidrug-resistant phenotype in CLL. Blood Advances. 5(17). 3497–3510. 13 indexed citations

11.

Su, Zhangli, Shekhar Saha, Teressa Paulsen, Pankaj Kumar, & Anindya Dutta. (2021). ATAC-Seq-based Identification of Extrachromosomal Circular DNA in Mammalian Cells and Its Validation Using Inverse PCR and FISH. BIO-PROTOCOL. 11(9). e4003–e4003. 13 indexed citations

12.

Saha, Shekhar, Manjari Kiran, Canan Kuscu, et al.. (2020). Long Noncoding RNA DRAIC Inhibits Prostate Cancer Progression by Interacting with IKK to Inhibit NF-κB Activation. Cancer Research. 80(5). 950–963. 56 indexed citations

13.

Chatrath, Ajay, Shashi Kiran, Zhangli Su, et al.. (2020). The pan-cancer landscape of prognostic germline variants in 10,582 patients. Genome Medicine. 12(1). 15–15. 23 indexed citations

14.

Buentzel, Judith, Judith Heinz, Annalen Bleckmann, et al.. (2019). Sarcopenia as Prognostic Factor in Lung Cancer Patients: A Systematic Review and Meta-analysis. Anticancer Research. 39(9). 4603–4612. 71 indexed citations

15.

Chattoraj, Shyamtanu, Shekhar Saha, Alakesh Das, et al.. (2017). Differential role of nonmuscle myosin II isoforms during blebbing of MCF-7 cells. Molecular Biology of the Cell. 28(8). 1034–1042. 9 indexed citations

16.

Ghosal, Suman, Shekhar Saha, Shaoli Das, et al.. (2016). miRepress: modelling gene expression regulation by microRNA with non-conventional binding sites. Scientific Reports. 6(1). 22334–22334. 9 indexed citations

17.

Saha, Shekhar, et al.. (2015). Role of Nonmuscle Myosin II in Migration of Wharton's Jelly-Derived Mesenchymal Stem Cells. Stem Cells and Development. 24(17). 2065–2077. 12 indexed citations

18.

Saha, Shekhar, et al.. (2014). Regulation of nonmuscle myosin II during 3-methylcholanthrene induced dedifferentiation of C2C12 myotubes. Experimental Cell Research. 326(1). 68–77. 2 indexed citations

19.

Dan, Krishna, et al.. (2013). Amphiphilic random copolymer vesicle induces differentiation of mouse C2C12 myoblasts. Biomaterials Science. 1(12). 1211–1211. 2 indexed citations

20.

Saha, Shekhar, et al.. (2011). Increased expression of nonmuscle myosin IIs is associated with 3MC‐induced mouse tumor. FEBS Journal. 278(21). 4025–4034. 8 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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