Raj K. Tiwari

2.3k total citations
91 papers, 1.6k citations indexed

About

Raj K. Tiwari is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Raj K. Tiwari has authored 91 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Molecular Biology, 23 papers in Oncology and 21 papers in Cancer Research. Recurrent topics in Raj K. Tiwari's work include Thyroid Cancer Diagnosis and Treatment (20 papers), Immunotherapy and Immune Responses (10 papers) and Estrogen and related hormone effects (9 papers). Raj K. Tiwari is often cited by papers focused on Thyroid Cancer Diagnosis and Treatment (20 papers), Immunotherapy and Immune Responses (10 papers) and Estrogen and related hormone effects (9 papers). Raj K. Tiwari collaborates with scholars based in United States, Colombia and China. Raj K. Tiwari's co-authors include Jan Geliebter, Robert Suriano, Shilpi Rajoria, Abraham Mittelman, Arulkumaran Shanmugam, Andrea L. George, Stimson P. Schantz, Augustine Moscatello, Badithe T. Ashok and Yushan Lisa Wilson and has published in prestigious journals such as PLoS ONE, The Journal of Clinical Endocrinology & Metabolism and Cancer Research.

In The Last Decade

Raj K. Tiwari

85 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
Raj K. Tiwari United States 23 804 318 295 273 237 91 1.6k
Onn Haji Hashim Malaysia 26 933 1.2× 220 0.7× 211 0.7× 230 0.8× 254 1.1× 114 2.0k
Sun‐Mi Park South Korea 22 738 0.9× 319 1.0× 186 0.6× 314 1.2× 145 0.6× 89 1.4k
Ashok Sharma United States 30 1.2k 1.5× 313 1.0× 250 0.8× 399 1.5× 337 1.4× 192 2.9k
Huan Deng China 23 692 0.9× 321 1.0× 216 0.7× 240 0.9× 254 1.1× 84 1.7k
Qianchuan He United States 19 586 0.7× 153 0.5× 133 0.5× 199 0.7× 208 0.9× 55 1.4k
Zhan Zhou China 27 1.5k 1.8× 489 1.5× 107 0.4× 287 1.1× 460 1.9× 113 2.7k
Maria Thomas Germany 26 823 1.0× 422 1.3× 95 0.3× 212 0.8× 416 1.8× 62 2.1k
Jing Guan China 25 817 1.0× 149 0.5× 146 0.5× 213 0.8× 480 2.0× 119 2.0k
Ming Ni China 23 1.1k 1.4× 152 0.5× 113 0.4× 148 0.5× 164 0.7× 128 2.1k
Shuqi Mao China 23 544 0.7× 143 0.4× 311 1.1× 222 0.8× 122 0.5× 57 1.5k

Countries citing papers authored by Raj K. Tiwari

Since Specialization
Citations

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

Fields of papers citing papers by Raj K. Tiwari

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Raj K. Tiwari. 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 Raj K. Tiwari. The network helps show where Raj K. Tiwari may publish in the future.

Co-authorship network of co-authors of Raj K. Tiwari

This figure shows the co-authorship network connecting the top 25 collaborators of Raj K. Tiwari. A scholar is included among the top collaborators of Raj K. Tiwari 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 Raj K. Tiwari. Raj K. Tiwari 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.
Huang, Audrey, et al.. (2025). Artificial Intelligence Advancements in Oncology: A Review of Current Trends and Future Directions. Biomedicines. 13(4). 951–951. 11 indexed citations
2.
Gonzalez, Ernesto, et al.. (2025). Traumatic Brain Injury and Artificial Intelligence: Shaping the Future of Neurorehabilitation—A Review. Life. 15(3). 424–424. 8 indexed citations
3.
Abraham, Elizabeth, et al.. (2025). The Role of Artificial Intelligence in Obesity Risk Prediction and Management: Approaches, Insights, and Recommendations. Medicina. 61(2). 358–358. 10 indexed citations
4.
Tiwari, Raj K., et al.. (2025). Natural Compounds Targeting MAPK, PI3K/Akt, and JAK/STAT Signaling in Papillary Thyroid Cancer. International Journal of Molecular Sciences. 26(21). 10498–10498.
5.
Werner, Robert A., et al.. (2025). The Etiology of IgE-Mediated Food Allergy: Potential Therapeutics and Challenges. International Journal of Molecular Sciences. 26(4). 1563–1563. 1 indexed citations
6.
Islam, Humayun, et al.. (2024). Abstract 4633: Differentiation driver gene HOXD4 as a potential prognostic indicator and therapeutic target in anaplastic thyroid cancer. Cancer Research. 84(6_Supplement). 4633–4633. 1 indexed citations
7.
Hirani, Rahim, et al.. (2024). Artificial Intelligence and Healthcare: A Journey through History, Present Innovations, and Future Possibilities. Life. 14(5). 557–557. 57 indexed citations
8.
Reyes, Niradiz, et al.. (2024). Effects of Multi-component TCM Therapy on Skin Microbiome of Infants With Severe Eczema Associated With Topical Steroid Withdrawal.. Journal of Allergy and Clinical Immunology. 153(2). AB66–AB66. 1 indexed citations
9.
Suriano, Robert, et al.. (2024). Dysregulated Expression Patterns of Circular RNAs in Cancer: Uncovering Molecular Mechanisms and Biomarker Potential. Biomolecules. 14(4). 384–384. 7 indexed citations
10.
Tiwari, Raj K., et al.. (2023). Interactome of Long Non-Coding RNAs: Transcriptomic Expression Patterns and Shaping Cancer Cell Phenotypes. International Journal of Molecular Sciences. 24(12). 9914–9914. 5 indexed citations
11.
Zalvan, Craig H., et al.. (2019). A Trigger Reduction Approach to Treatment of Paradoxical Vocal Fold Motion Disorder in the Pediatric Population. Journal of Voice. 35(2). 323.e9–323.e15. 10 indexed citations
12.
Maniyar, Rachana, et al.. (2018). Macrophage inflammatory factors promote epithelial-mesenchymal transition in breast cancer. Oncotarget. 9(36). 24272–24282. 32 indexed citations
13.
George, Andrea L., et al.. (2012). Hypoxia and estrogen are functionally equivalent in breast cancer-endothelial cell interdependence. Molecular Cancer. 11(1). 80–80. 41 indexed citations
14.
Rajoria, Shilpi, Robert Suriano, Yushan Lisa Wilson, et al.. (2011). 3,3′-Diindolylmethane Modulates Estrogen Metabolism in Patients with Thyroid Proliferative Disease: A Pilot Study. Thyroid. 21(3). 299–304. 37 indexed citations
15.
Nowicki, Theodore S., Hong Zhao, Zbigniew Darżynkiewicz, et al.. (2011). Downregulation of uPAR inhibits migration, invasion, proliferation, FAK/PI3K/Akt signaling and induces senescence in papillary thyroid carcinoma cells. Cell Cycle. 10(1). 100–107. 52 indexed citations
16.
Rajoria, Shilpi, Robert Suriano, Andrea L. George, et al.. (2011). Estrogen Induced Metastatic Modulators MMP-2 and MMP-9 Are Targets of 3,3′-Diindolylmethane in Thyroid Cancer. PLoS ONE. 6(1). e15879–e15879. 69 indexed citations
17.
Suriano, Robert, et al.. (2008). 17β-Estradiol Mobilizes Bone Marrow–Derived Endothelial Progenitor Cells to Tumors. Cancer Research. 68(15). 6038–6042. 42 indexed citations
18.
Ashok, Badithe T., et al.. (2005). Induction of androgen receptor by a novel nitroacridine, C-1748: Implications for its role as a chemotherapeutic agent in hormone independent prostate cancer. Cancer Research. 65. 1385–1385. 1 indexed citations
19.
Ashok, Badithe T., et al.. (2005). Synthetic dimer of indole‐3‐carbinol: Second generation diet derived anti‐cancer agent in hormone sensitive prostate cancer. The Prostate. 66(5). 453–462. 20 indexed citations
20.
Liu, Xinyan, Raj K. Tiwari, Jan Geliebter, Joseph Wu, & Henry P. Godfrey. (2004). Interaction of a Mycobacterium tuberculosis repetitive DNA sequence with eukaryotic proteins. Biochemical and Biophysical Research Communications. 320(3). 966–972. 3 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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