Dedeepya Vaka

4.7k total citations · 1 hit paper
18 papers, 1.4k citations indexed

About

Dedeepya Vaka is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Dedeepya Vaka has authored 18 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 8 papers in Oncology and 6 papers in Cancer Research. Recurrent topics in Dedeepya Vaka's work include Cancer Cells and Metastasis (5 papers), Cancer Genomics and Diagnostics (3 papers) and Neuroendocrine Tumor Research Advances (2 papers). Dedeepya Vaka is often cited by papers focused on Cancer Cells and Metastasis (5 papers), Cancer Genomics and Diagnostics (3 papers) and Neuroendocrine Tumor Research Advances (2 papers). Dedeepya Vaka collaborates with scholars based in United States, Canada and Türkiye. Dedeepya Vaka's co-authors include Atul J. Butte, Purvesh Khatri, Richard M. Locksley, Jinwoo Lee, Walter L. Eckalbar, Jesse C. Nussbaum, Christoph Schneider, Steven J. Van Dyken, David J. Erle and Ari B. Molofsky and has published in prestigious journals such as Cell, Journal of Clinical Investigation and Nature Immunology.

In The Last Decade

Dedeepya Vaka

17 papers receiving 1.4k citations

Hit Papers

Tissue signals imprint ILC2 identity with anticipatory fu... 2018 2026 2020 2023 2018 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
Dedeepya Vaka United States 13 665 401 399 265 205 18 1.4k
Karin Wadt Denmark 18 701 1.1× 298 0.7× 528 1.3× 147 0.6× 319 1.6× 65 1.4k
Jessica Pruessmeyer Germany 14 611 0.9× 252 0.6× 356 0.9× 66 0.2× 237 1.2× 15 1.3k
Sandro Goruppi United States 21 1.0k 1.5× 611 1.5× 397 1.0× 252 1.0× 196 1.0× 28 1.8k
Sara Tomei Qatar 20 521 0.8× 405 1.0× 534 1.3× 79 0.3× 251 1.2× 59 1.2k
Jie Dai China 26 937 1.4× 394 1.0× 1.0k 2.6× 99 0.4× 271 1.3× 98 1.8k
Wendy S. Halsey United States 13 536 0.8× 274 0.7× 371 0.9× 80 0.3× 105 0.5× 19 1.3k
Yanyan Han China 10 691 1.0× 568 1.4× 870 2.2× 175 0.7× 317 1.5× 21 1.9k
Sílvia Carvalho Israel 23 1.1k 1.7× 108 0.3× 516 1.3× 228 0.9× 429 2.1× 36 1.8k
Ann Marie Egloff United States 29 1.2k 1.8× 324 0.8× 837 2.1× 320 1.2× 371 1.8× 63 2.3k
Julia Gilhodes France 19 513 0.8× 309 0.8× 459 1.2× 82 0.3× 218 1.1× 38 1.2k

Countries citing papers authored by Dedeepya Vaka

Since Specialization
Citations

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

Fields of papers citing papers by Dedeepya Vaka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dedeepya Vaka

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

All Works

18 of 18 papers shown
1.
Cortez, Victor S., Sara Viragova, Satoshi Koga, et al.. (2025). IL-25-induced memory type 2 innate lymphoid cells enforce mucosal immunity. Cell. 188(22). 6220–6235.e22.
2.
Zwick, Rachel K., Petr Kašpárek, Brisa Palikuqi, et al.. (2024). Epithelial zonation along the mouse and human small intestine defines five discrete metabolic domains. Nature Cell Biology. 26(2). 250–262. 22 indexed citations
3.
Huycke, Tyler R., Teemu J. Häkkinen, Vasudha Srivastava, et al.. (2024). Patterning and folding of intestinal villi by active mesenchymal dewetting. Cell. 187(12). 3072–3089.e20. 32 indexed citations
4.
Palikuqi, Brisa, et al.. (2022). Lymphangiocrine signals are required for proper intestinal repair after cytotoxic injury. Cell stem cell. 29(8). 1262–1272.e5. 43 indexed citations
5.
Wong, K., Michal Levy‐Sakin, Nina Gonzaludo, et al.. (2019). Three patients with homozygous familial hypercholesterolemia: Genomic sequencing and kindred analysis. Molecular Genetics & Genomic Medicine. 7(12). e1007–e1007. 3 indexed citations
6.
Ricardo-González, Roberto R., Steven J. Van Dyken, Christoph Schneider, et al.. (2018). Tissue signals imprint ILC2 identity with anticipatory function. Nature Immunology. 19(10). 1093–1099. 327 indexed citations breakdown →
7.
Chiou, Shin-Heng, Viviana I. Risca, Gordon Wang, et al.. (2017). BLIMP1 Induces Transient Metastatic Heterogeneity in Pancreatic Cancer. Cancer Discovery. 7(10). 1184–1199. 49 indexed citations
8.
Bassaganyas, Laia, Dedeepya Vaka, Eunice Wan, et al.. (2017). Whole exome and whole genome sequencing with dried blood spot DNA without whole genome amplification. Human Mutation. 39(1). 167–171. 26 indexed citations
9.
Koehne, Amanda, Leanne C. Sayles, Marcus R. Breese, Dedeepya Vaka, & E. Alejandro Sweet‐Cordero. (2016). Abstract A35: Characterization of the genomic landscape of osteosarcoma metastasis. Cancer Research. 76(5_Supplement). A35–A35. 1 indexed citations
10.
Ron, Chen, Purvesh Khatri, Paweł K. Mazur, et al.. (2014). A Meta-analysis of Lung Cancer Gene Expression Identifies PTK7 as a Survival Gene in Lung Adenocarcinoma. Cancer Research. 74(10). 2892–2902. 116 indexed citations
11.
Ehmer, Ursula, Anne‐Flore Zmoos, Raymond K. Auerbach, et al.. (2014). Organ Size Control Is Dominant over Rb Family Inactivation to Restrict Proliferation In Vivo. Cell Reports. 8(2). 371–381. 32 indexed citations
12.
Kareta, Michael S., Bérénice A. Benayoun, Samuele Marro, et al.. (2014). Inhibition of Pluripotency Networks by the Rb Tumor Suppressor Restricts Reprogramming and Tumorigenesis. Cell stem cell. 16(1). 39–50. 156 indexed citations
13.
Simpson, David, Siu P. Ngok, Chen Ron, et al.. (2014). Long noncoding RNA EWSAT1-mediated gene repression facilitates Ewing sarcoma oncogenesis. Journal of Clinical Investigation. 124(12). 5275–5290. 70 indexed citations
14.
Jahchan, Nadine S., Joel T. Dudley, Paweł K. Mazur, et al.. (2014). Abstract 4610: A drug repositioning approach identifies tricyclic antidepressants as inhibitors of small cell lung cancer and other neuroendocrine tumors. Cancer Research. 74(19_Supplement). 4610–4610. 2 indexed citations
15.
Jahchan, Nadine S., Joel T. Dudley, Paweł K. Mazur, et al.. (2013). A Drug Repositioning Approach Identifies Tricyclic Antidepressants as Inhibitors of Small Cell Lung Cancer and Other Neuroendocrine Tumors. Cancer Discovery. 3(12). 1364–1377. 275 indexed citations
16.
Zheng, Yanyan, Cecile C. de la Cruz, Leanne C. Sayles, et al.. (2013). A Rare Population of CD24+ITGB4+Notchhi Cells Drives Tumor Propagation in NSCLC and Requires Notch3 for Self-Renewal. Cancer Cell. 24(1). 59–74. 113 indexed citations
17.
Ron, Chen, et al.. (2013). Abstract PR08: Identifying effectors of WT1 that regulate KRAS-induced senescence and chemoresistance in non-small cell lung cancer. Molecular Cancer Therapeutics. 12(5_Supplement). PR08–PR08. 1 indexed citations
18.
Vicent, Silvestre, Leanne C. Sayles, Dedeepya Vaka, et al.. (2012). Cross-Species Functional Analysis of Cancer-Associated Fibroblasts Identifies a Critical Role for CLCF1 and IL-6 in Non–Small Cell Lung Cancer In Vivo. Cancer Research. 72(22). 5744–5756. 102 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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