Sanjeev Raghuwanshi

786 total citations · 1 hit paper
16 papers, 543 citations indexed

About

Sanjeev Raghuwanshi is a scholar working on Molecular Biology, Hematology and Surgery. According to data from OpenAlex, Sanjeev Raghuwanshi has authored 16 papers receiving a total of 543 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 6 papers in Hematology and 5 papers in Surgery. Recurrent topics in Sanjeev Raghuwanshi's work include Platelet Disorders and Treatments (5 papers), Cancer-related molecular mechanisms research (5 papers) and RNA modifications and cancer (2 papers). Sanjeev Raghuwanshi is often cited by papers focused on Platelet Disorders and Treatments (5 papers), Cancer-related molecular mechanisms research (5 papers) and RNA modifications and cancer (2 papers). Sanjeev Raghuwanshi collaborates with scholars based in India, United States and Brazil. Sanjeev Raghuwanshi's co-authors include Ravi Kumar Gutti, Swati Dahariya, Indira Paddibhatla, Santosh Kumar, Deepa Deswal, Matti Karp, Ramesh Chander Kuhad, Andrei L. Gartel, Itishri Sahu and Usha Gutti and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Pharmacology and Experimental Therapeutics and Fuel.

In The Last Decade

Sanjeev Raghuwanshi

16 papers receiving 535 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.

Long non-coding RNA: Classification, biogenesis and functions in blood cells

2019 332 citations Swati Dahariya, Indira Paddibhatla et al. Molecular Immunology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sanjeev Raghuwanshi India	10	398	319	73	41	39	16	543
Yunzhi Pan China	13	320 0.8×	159 0.5×	42 0.6×	17 0.4×	29 0.7×	30	543
Luyi Ye China	13	218 0.5×	155 0.5×	69 0.9×	23 0.6×	117 3.0×	43	526
Haiping Zhang China	15	471 1.2×	320 1.0×	21 0.3×	23 0.6×	17 0.4×	36	640
Sheng Zheng China	9	274 0.7×	168 0.5×	45 0.6×	39 1.0×	6 0.2×	12	399
Mohamed Hammad United States	13	210 0.5×	71 0.2×	50 0.7×	23 0.6×	16 0.4×	29	426
Dongyuan Zhang China	10	438 1.1×	362 1.1×	40 0.5×	20 0.5×	5 0.1×	18	609
Hong Yuan China	16	477 1.2×	237 0.7×	23 0.3×	7 0.2×	12 0.3×	28	636
Ju Ma China	13	297 0.7×	189 0.6×	31 0.4×	11 0.3×	8 0.2×	19	487
Yihang Gong China	11	179 0.4×	123 0.4×	71 1.0×	18 0.4×	10 0.3×	23	461

Countries citing papers authored by Sanjeev Raghuwanshi

Since Specialization

Citations

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

Fields of papers citing papers by Sanjeev Raghuwanshi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sanjeev Raghuwanshi

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

All Works

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16 of 16 papers shown

Raghuwanshi, Sanjeev, Ahmed Magdy, Nissim Hay, & Andrei L. Gartel. (2025). A novel FOXM1–BCL2A1 axis determines unfavorable response to venetoclax in AML. Journal of Biological Chemistry. 301(3). 108240–108240. 1 indexed citations

Raghuwanshi, Sanjeev, Xu Zhang, Zarema Arbieva, et al.. (2024). Novel FOXM1 inhibitor STL001 sensitizes human cancers to a broad-spectrum of cancer therapies. Cell Death Discovery. 10(1). 211–211. 9 indexed citations

Raghuwanshi, Sanjeev & Andrei L. Gartel. (2023). Small-molecule inhibitors targeting FOXM1: Current challenges and future perspectives in cancer treatments. Biochimica et Biophysica Acta (BBA) - Reviews on Cancer. 1878(6). 189015–189015. 14 indexed citations

Dahariya, Swati, et al.. (2022). Role of Long Non-Coding RNAs in Human-Induced Pluripotent Stem Cells Derived Megakaryocytes: A p53, HOX Antisense Intergenic RNA Myeloid 1, and miR-125b Interaction Study. Journal of Pharmacology and Experimental Therapeutics. 384(1). 92–101. 2 indexed citations

Dahariya, Swati, et al.. (2021). Megakaryoblastic leukemia: a study on novel role of clinically significant long non-coding RNA signatures in megakaryocyte development during treatment with phorbol ester. Cancer Immunology Immunotherapy. 70(12). 3477–3488. 3 indexed citations

Raghuwanshi, Sanjeev, et al.. (2021). Co-stimulatory effect of TLR2 and TLR4 stimulation on megakaryocytic development is mediated through PI3K/NF-ĸB and XBP-1 loop. Cellular Signalling. 80. 109924–109924. 7 indexed citations

Paddibhatla, Indira, et al.. (2021). Endocannabinoid system: Role in blood cell development, neuroimmune interactions and associated disorders. Journal of Neuroimmunology. 353. 577501–577501. 8 indexed citations

Raghuwanshi, Sanjeev, et al.. (2020). Virodhamine, an endocannabinoid, induces megakaryocyte differentiation by regulating MAPK activity and function of mitochondria. Journal of Cellular Physiology. 236(2). 1445–1453. 9 indexed citations

Raghuwanshi, Sanjeev, et al.. (2020). RUNX1 and TGF‐β signaling cross talk regulates Ca²⁺ ion channels expression and activity during megakaryocyte development. FEBS Journal. 287(24). 5411–5438. 20 indexed citations

10.

Raghuwanshi, Sanjeev, et al.. (2019). Endoplasmic reticulum stress induced apoptosis and caspase activation is mediated through mitochondria during megakaryocyte differentiation. Mitochondrion. 50. 115–120. 16 indexed citations

11.

Dahariya, Swati, et al.. (2019). Long non-coding RNA: Classification, biogenesis and functions in blood cells. Molecular Immunology. 112. 82–92. 332 indexed citations breakdown →

12.

Raghuwanshi, Sanjeev, Swati Dahariya, Usha Gutti, et al.. (2018). MicroRNA function in megakaryocytes. Platelets. 30(7). 809–816. 15 indexed citations

13.

Raghuwanshi, Sanjeev, et al.. (2018). Current Updates on Role of Lipids in Hematopoiesis. Infectious Disorders - Drug Targets. 18(3). 192–198. 8 indexed citations

14.

Raghuwanshi, Sanjeev, Swati Dahariya, Ravinder Kandi, et al.. (2017). Epigenetic Mechanisms: Role in Hematopoietic Stem Cell Lineage Commitment and Differentiation. Current Drug Targets. 19(14). 1683–1695. 15 indexed citations

15.

Karnati, Hanuma Kumar, et al.. (2015). microRNAs: Key Players in Hematopoiesis. Advances in experimental medicine and biology. 887. 171–211. 11 indexed citations

16.

Raghuwanshi, Sanjeev, Deepa Deswal, Matti Karp, & Ramesh Chander Kuhad. (2014). Bioprocessing of enhanced cellulase production from a mutant of Trichoderma asperellum RCK2011 and its application in hydrolysis of cellulose. Fuel. 124. 183–189. 73 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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