Shreyas S. Rao

2.1k total citations
54 papers, 1.7k citations indexed

About

Shreyas S. Rao is a scholar working on Oncology, Biomedical Engineering and Cell Biology. According to data from OpenAlex, Shreyas S. Rao has authored 54 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Oncology, 22 papers in Biomedical Engineering and 15 papers in Cell Biology. Recurrent topics in Shreyas S. Rao's work include Cancer Cells and Metastasis (27 papers), 3D Printing in Biomedical Research (17 papers) and Cellular Mechanics and Interactions (10 papers). Shreyas S. Rao is often cited by papers focused on Cancer Cells and Metastasis (27 papers), 3D Printing in Biomedical Research (17 papers) and Cellular Mechanics and Interactions (10 papers). Shreyas S. Rao collaborates with scholars based in United States, India and Philippines. Shreyas S. Rao's co-authors include Jessica O. Winter, Jeffrey A. Hubbell, Stephen P. Massia, Atom Sarkar, Brian A. Aguado, Jacqueline S. Jeruss, Grace G. Bushnell, Lonnie D. Shea, Samira M. Azarin and Yonghyun Kim and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and Journal of Clinical Oncology.

In The Last Decade

Shreyas S. Rao

50 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shreyas S. Rao United States 25 833 621 383 379 326 54 1.7k
Delphine Gourdon United States 17 569 0.7× 423 0.7× 262 0.7× 853 2.3× 411 1.3× 19 2.0k
Karin Wang United States 18 548 0.7× 345 0.6× 528 1.4× 301 0.8× 708 2.2× 25 2.0k
Julie Chang United States 19 695 0.8× 546 0.9× 171 0.4× 660 1.7× 429 1.3× 24 1.7k
Umber Cheema United Kingdom 28 1.3k 1.6× 587 0.9× 828 2.2× 572 1.5× 575 1.8× 77 2.7k
Guanqing Ou United States 7 520 0.6× 366 0.6× 317 0.8× 643 1.7× 531 1.6× 7 1.7k
Laura J. Bray Australia 20 655 0.8× 325 0.5× 380 1.0× 178 0.5× 281 0.9× 66 1.4k
Yongchao Mou United States 14 1.0k 1.2× 274 0.4× 373 1.0× 226 0.6× 564 1.7× 25 2.0k
Joseph P. Califano United States 15 830 1.0× 366 0.6× 207 0.5× 1.2k 3.1× 538 1.7× 20 2.1k
Meng Yang China 25 551 0.7× 258 0.4× 324 0.8× 137 0.4× 748 2.3× 59 2.1k
Marcel Alexander Heinrich Netherlands 13 1.5k 1.7× 512 0.8× 214 0.6× 145 0.4× 266 0.8× 19 1.8k

Countries citing papers authored by Shreyas S. Rao

Since Specialization
Citations

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

Fields of papers citing papers by Shreyas S. Rao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shreyas S. Rao. 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 Shreyas S. Rao. The network helps show where Shreyas S. Rao may publish in the future.

Co-authorship network of co-authors of Shreyas S. Rao

This figure shows the co-authorship network connecting the top 25 collaborators of Shreyas S. Rao. A scholar is included among the top collaborators of Shreyas S. Rao 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 Shreyas S. Rao. Shreyas S. Rao 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.
2.
Shevde, Lalita A., et al.. (2024). Laminin I mediates resistance to lapatinib in HER2-positive brain metastatic breast cancer cells in vitro. Biochemical and Biophysical Research Communications. 720. 150142–150142. 4 indexed citations
3.
Shevde, Lalita A., et al.. (2024). Matrix stiffness influences response to chemo and targeted therapy in brain metastatic breast cancer cells. Biomaterials Science. 12(15). 3882–3895. 3 indexed citations
4.
Shevde, Lalita A., et al.. (2024). Protocol for generating dormant human brain metastatic breast cancer spheroids in vitro. STAR Protocols. 5(2). 102962–102962. 5 indexed citations
5.
Rao, Shreyas S., et al.. (2024). Glioblastoma mechanobiology at multiple length scales. Biomaterials Advances. 160. 213860–213860. 7 indexed citations
6.
Rao, Shreyas S., et al.. (2024). Structurally decoupled hyaluronic acid hydrogels for studying matrix metalloproteinase-mediated invasion of metastatic breast cancer cells. International Journal of Biological Macromolecules. 277(Pt 4). 134493–134493. 8 indexed citations
7.
Winter, Jessica O. & Shreyas S. Rao. (2022). Biomaterial Based Approaches to Study the Tumour Microenvironment. 2 indexed citations
8.
Rao, Shreyas S., et al.. (2021). Transfer learning-based Plant Disease Detection. 469–477. 4 indexed citations
9.
Kim, Yonghyun, et al.. (2021). The Impact of Astrocytes and Endothelial Cells on Glioblastoma Stemness Marker Expression in Multicellular Spheroids. Cellular and Molecular Bioengineering. 14(6). 639–651. 7 indexed citations
10.
Rao, Shreyas S., et al.. (2020). Fabrication of micro-porous hyaluronic acid hydrogels through salt leaching. European Polymer Journal. 135. 109870–109870. 42 indexed citations
11.
Crossman, David K., et al.. (2020). An in vitro hyaluronic acid hydrogel based platform to model dormancy in brain metastatic breast cancer cells. Acta Biomaterialia. 107. 65–77. 45 indexed citations
12.
Bushnell, Grace G., Shreyas S. Rao, Yining Zhang, et al.. (2019). Microporous scaffolds loaded with immunomodulatory lentivirus to study the contribution of immune cell populations to tumor cell recruitment in vivo. Biotechnology and Bioengineering. 117(1). 210–222. 9 indexed citations
13.
Park, Seungjo, et al.. (2019). Targeting Hyaluronan Interactions for Glioblastoma Stem Cell Therapy. Cancer Microenvironment. 12(1). 47–56. 25 indexed citations
14.
Kim, Yonghyun, et al.. (2019). Three‐dimensional biomimetic hyaluronic acid hydrogels to investigate glioblastoma stem cell behaviors. Biotechnology and Bioengineering. 117(2). 511–522. 35 indexed citations
15.
Kim, Yonghyun, et al.. (2018). Biomimetic models to examine microenvironmental regulation of glioblastoma stem cells. Cancer Letters. 429. 41–53. 25 indexed citations
16.
Shevde, Lalita A., et al.. (2017). Biomimetic strategies to recapitulate organ specific microenvironments for studying breast cancer metastasis. International Journal of Cancer. 141(6). 1091–1109. 26 indexed citations
17.
Rao, Shreyas S., Grace G. Bushnell, Samira M. Azarin, et al.. (2016). Enhanced Survival with Implantable Scaffolds That Capture Metastatic Breast Cancer Cells In Vivo. Cancer Research. 76(18). 5209–5218. 74 indexed citations
18.
Short, Aaron, Shreyas S. Rao, Jessica O. Winter, et al.. (2015). Glioma‐astrocyte interactions on white matter tract‐mimetic aligned electrospun nanofibers. Biotechnology Progress. 31(5). 1406–1415. 22 indexed citations
19.
Rao, Shreyas S., John J. Lannutti, Mariano S. Viapiano, Atom Sarkar, & Jessica O. Winter. (2013). Toward 3D Biomimetic Models to Understand the Behavior of Glioblastoma Multiforme Cells. Tissue Engineering Part B Reviews. 20(4). 314–327. 49 indexed citations
20.
Isaacs, Claudine, et al.. (2008). Circulating tumor cells (CTC): A reliable predictor of treatment efficacy in metastatic breast cancer (MBC). Journal of Clinical Oncology. 26(15_suppl). 11018–11018. 4 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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