Chitra Venugopal

3.7k total citations · 1 hit paper
94 papers, 2.0k citations indexed

About

Chitra Venugopal is a scholar working on Oncology, Molecular Biology and Genetics. According to data from OpenAlex, Chitra Venugopal has authored 94 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Oncology, 40 papers in Molecular Biology and 37 papers in Genetics. Recurrent topics in Chitra Venugopal's work include Glioma Diagnosis and Treatment (37 papers), Cancer Cells and Metastasis (30 papers) and CAR-T cell therapy research (15 papers). Chitra Venugopal is often cited by papers focused on Glioma Diagnosis and Treatment (37 papers), Cancer Cells and Metastasis (30 papers) and CAR-T cell therapy research (15 papers). Chitra Venugopal collaborates with scholars based in Canada, United States and United Kingdom. Chitra Venugopal's co-authors include Sheila K. Singh, Mohini Singh, Parvez Vora, Kumar Sambamurti, Nicole McFarlane, Maleeha Qazi, Jason Moffat, Branavan Manoranjan, Charles Swanton and Sachdev S. Sidhu and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Journal of Clinical Oncology.

In The Last Decade

Chitra Venugopal

88 papers receiving 2.0k citations

Hit Papers

EMT: Mechanisms and therapeutic implications 2017 2026 2020 2023 2017 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chitra Venugopal Canada 21 1.1k 623 483 467 242 94 2.0k
Deobrat Dixit India 22 1.1k 1.1× 327 0.5× 584 1.2× 304 0.7× 138 0.6× 31 1.8k
Dara Ditsworth United States 19 2.0k 1.9× 484 0.8× 781 1.6× 509 1.1× 242 1.0× 21 3.2k
Lenka Munoz Australia 20 1.0k 1.0× 369 0.6× 259 0.5× 163 0.3× 297 1.2× 38 2.0k
Shizuka Seino Japan 26 1.4k 1.3× 614 1.0× 457 0.9× 303 0.6× 78 0.3× 44 2.0k
Maode Wang China 22 1.2k 1.1× 479 0.8× 768 1.6× 461 1.0× 75 0.3× 71 1.9k
Zhihu Ding United States 14 2.1k 2.0× 452 0.7× 516 1.1× 278 0.6× 375 1.5× 21 2.7k
Maty Tzukerman Israel 28 2.4k 2.3× 562 0.9× 296 0.6× 262 0.6× 334 1.4× 46 3.6k
Sabine Spiegl‐Kreinecker Austria 22 866 0.8× 288 0.5× 265 0.5× 348 0.7× 128 0.5× 45 1.6k
Péter Ács United States 26 969 0.9× 451 0.7× 282 0.6× 134 0.3× 326 1.3× 42 2.1k

Countries citing papers authored by Chitra Venugopal

Since Specialization
Citations

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

Fields of papers citing papers by Chitra Venugopal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chitra Venugopal

This figure shows the co-authorship network connecting the top 25 collaborators of Chitra Venugopal. A scholar is included among the top collaborators of Chitra Venugopal 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 Chitra Venugopal. Chitra Venugopal 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.
Chafe, Shawn C., et al.. (2025). Proximity Ligation Assay. Methods in molecular biology. 2944. 135–140. 1 indexed citations
2.
Noel, Mathew Mithra, et al.. (2024). Novel Darknet traffic data synthesis using Generative Adversarial Networks enhanced with oscillatory Growing Cosine Unit activated convolution layers. SHILAP Revista de lepidopterología. 5. 58–65. 2 indexed citations
3.
Adile, Ashley, David Bakhshinyan, Yujin Suk, et al.. (2023). An effective kinase inhibition strategy for metastatic recurrent childhood medulloblastoma. Journal of Neuro-Oncology. 163(3). 635–645. 2 indexed citations
4.
Kieliszek, Agata, Deepak Upreti, Darin Bloemberg, et al.. (2023). Intratumoral Delivery of Chimeric Antigen Receptor T Cells Targeting CD133 Effectively Treats Brain Metastases. Clinical Cancer Research. 30(3). 554–563. 15 indexed citations
5.
Chokshi, Chirayu, Agata Kieliszek, Nazanin Tatari, et al.. (2023). An HLA-G/SPAG9/STAT3 axis promotes brain metastases. Proceedings of the National Academy of Sciences. 120(8). e2205247120–e2205247120. 8 indexed citations
6.
Martell, Emma, Subir Roy Chowdhury, Agnes Fresnoza, et al.. (2023). Metabolism-based targeting of MYC via MPC-SOD2 axis-mediated oxidation promotes cellular differentiation in group 3 medulloblastoma. Nature Communications. 14(1). 2502–2502. 10 indexed citations
7.
Tatari, Nazanin, Andreas Zingg, Viviane J. Tschan, et al.. (2023). P06.15.B IMMUNOTHERAPEUTIC TARGETING OF FIBROBLAST ACTIVATION PROTEIN (FAP) IN TREATMENT REFRACTORY GLIOBLASTOMA USING NOVEL CAR-T CELL THERAPY. Neuro-Oncology. 25(Supplement_2). ii49–ii49. 1 indexed citations
8.
Venugopal, Chitra, et al.. (2023). Rees algebra of maximal order Pfaffians and its diagonal subalgebras. Communications in Algebra. 52(4). 1374–1388.
9.
Suk, Yujin, et al.. (2022). Childhood Medulloblastoma: An Overview. Methods in molecular biology. 2423. 1–12. 10 indexed citations
10.
Suk, Yujin, et al.. (2022). Derivation and culturing of neural stem cells from human embryonic brain tissue. STAR Protocols. 3(3). 101628–101628. 4 indexed citations
11.
Chokshi, Chirayu, et al.. (2021). In vitro evaluation of CAR-T cells in patient-derived glioblastoma models. STAR Protocols. 2(4). 100920–100920. 9 indexed citations
12.
Shah, Fenil, Justyna M. Gawel, Yasir S. Raouf, et al.. (2019). Identification and Characterization of AES-135, a Hydroxamic Acid-Based HDAC Inhibitor That Prolongs Survival in an Orthotopic Mouse Model of Pancreatic Cancer. Journal of Medicinal Chemistry. 62(5). 2651–2665. 28 indexed citations
13.
Singh, Mohini, Chitra Venugopal, Tomáš Tokár, et al.. (2018). Therapeutic Targeting of the Premetastatic Stage in Human Lung-to-Brain Metastasis. Cancer Research. 78(17). 5124–5134. 34 indexed citations
14.
Sharif, Tanveer, Cathleen Dai, Emma Martell, et al.. (2018). TAp73 Modifies Metabolism and Positively Regulates Growth of Cancer Stem–Like Cells in a Redox-Sensitive Manner. Clinical Cancer Research. 25(6). 2001–2017. 27 indexed citations
15.
Bien-Möller, Sandra, Susann Herzog, Silke Vogelgesang, et al.. (2018). Association of Glioblastoma Multiforme Stem Cell Characteristics, Differentiation, and Microglia Marker Genes with Patient Survival. Stem Cells International. 2018. 1–19. 36 indexed citations
16.
Bakhshinyan, David, Ashley Adile, Chitra Venugopal, & Sheila K. Singh. (2017). Bmi1 – A Path to Targeting Cancer Stem Cells. European Oncology & Haematology. 13(2). 147–147. 2 indexed citations
17.
Garg, Neha, et al.. (2015). MicroRNA Regulation of Brain Tumour Initiating Cells in Central Nervous System Tumours. Stem Cells International. 2015. 1–15. 20 indexed citations
18.
Wang, Xin, Chitra Venugopal, Branavan Manoranjan, et al.. (2011). Sonic hedgehog regulates Bmi1 in human medulloblastoma brain tumor-initiating cells. Oncogene. 31(2). 187–199. 104 indexed citations
19.
Sambamurti, Kumar, et al.. (2007). Amyloid Precursor Protein Metabolism in Retinal Degeneration. Investigative Ophthalmology & Visual Science. 48(13). 26–26. 1 indexed citations
20.
Sambamurti, Kumar, Anitha Suram, Chitra Venugopal, et al.. (2006). A Partial Failure of Membrane Protein Turnover May Cause Alzheimers Disease: A New Hypothesis. Current Alzheimer Research. 3(1). 81–90. 49 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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