Shilpaa Mukundan

800 total citations
18 papers, 670 citations indexed

About

Shilpaa Mukundan is a scholar working on Oncology, Biomedical Engineering and Biomaterials. According to data from OpenAlex, Shilpaa Mukundan has authored 18 papers receiving a total of 670 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Oncology, 9 papers in Biomedical Engineering and 4 papers in Biomaterials. Recurrent topics in Shilpaa Mukundan's work include Cancer Cells and Metastasis (6 papers), 3D Printing in Biomedical Research (6 papers) and Electrospun Nanofibers in Biomedical Applications (4 papers). Shilpaa Mukundan is often cited by papers focused on Cancer Cells and Metastasis (6 papers), 3D Printing in Biomedical Research (6 papers) and Electrospun Nanofibers in Biomedical Applications (4 papers). Shilpaa Mukundan collaborates with scholars based in United States, China and Belgium. Shilpaa Mukundan's co-authors include Akhilesh K. Gaharwar, Silvia M. Mihăilă, Ali Khademhosseini, Giorgio Iviglia, Alpesh Patel, Hongbin Zhang, Shilpa Sant, Danilo Demarchi, Vinayak Sant and Akhil Patel and has published in prestigious journals such as Biomaterials, Cancer Research and Scientific Reports.

In The Last Decade

Shilpaa Mukundan

18 papers receiving 665 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shilpaa Mukundan United States 11 394 307 93 85 78 18 670
Sandra Hauser Germany 13 406 1.0× 265 0.9× 61 0.7× 139 1.6× 100 1.3× 31 816
Ahmad Rezaei Kolahchi Canada 10 470 1.2× 273 0.9× 53 0.6× 71 0.8× 140 1.8× 12 741
Raminder Singh Germany 18 406 1.0× 371 1.2× 54 0.6× 80 0.9× 119 1.5× 26 818
Prachi Desai Germany 9 649 1.6× 377 1.2× 95 1.0× 75 0.9× 229 2.9× 16 1.1k
Bahareh Nazari Iran 11 402 1.0× 319 1.0× 43 0.5× 94 1.1× 147 1.9× 19 778
Haofang Zhu China 16 420 1.1× 286 0.9× 35 0.4× 137 1.6× 96 1.2× 26 942
Gabriella Lindberg New Zealand 12 617 1.6× 198 0.6× 53 0.6× 79 0.9× 59 0.8× 22 847
Zhixiang Tong United States 17 229 0.6× 231 0.8× 89 1.0× 127 1.5× 53 0.7× 23 738
Dinglingge Cao China 16 367 0.9× 325 1.1× 34 0.4× 111 1.3× 123 1.6× 25 786
Antonios G. Mikos United States 8 306 0.8× 191 0.6× 105 1.1× 101 1.2× 31 0.4× 10 597

Countries citing papers authored by Shilpaa Mukundan

Since Specialization
Citations

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

Fields of papers citing papers by Shilpaa Mukundan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shilpaa Mukundan

This figure shows the co-authorship network connecting the top 25 collaborators of Shilpaa Mukundan. A scholar is included among the top collaborators of Shilpaa Mukundan 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 Shilpaa Mukundan. Shilpaa Mukundan 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.
King, Benjamin, Kirill Gorshkov, Gregory Barker, et al.. (2024). Identification of a fibronectin-binding protein signature associated with idiopathic pulmonary fibrosis. PubMed. 179. 203941–203941. 3 indexed citations
2.
Mukundan, Shilpaa, et al.. (2022). Automated Assessment of Cancer Drug Efficacy On Breast Tumor Spheroids in Aggrewell™400 Plates Using Image Cytometry. Journal of Fluorescence. 32(2). 521–531. 12 indexed citations
3.
Mukundan, Shilpaa, et al.. (2021). 3D host cell and pathogen-based bioassay development for testing anti-tuberculosis (TB) drug response and modeling immunodeficiency. BioMolecular Concepts. 12(1). 117–128. 5 indexed citations
4.
Mukundan, Shilpaa, Pooja Singh, Ranjeet Kumar, et al.. (2021). In Vitro Miniaturized Tuberculosis Spheroid Model. Biomedicines. 9(9). 1209–1209. 12 indexed citations
5.
Lucas, John J., et al.. (2021). Non-invasive image-based cytometry for high throughput NK cell cytolysis analysis. Journal of Immunological Methods. 491. 112992–112992. 3 indexed citations
6.
Mukundan, Shilpaa, et al.. (2018). Artificial T Cell Mimetics to Combat Melanoma Tumor Growth. PubMed. 6(1). 21–32. 2 indexed citations
7.
Mukundan, Shilpaa, et al.. (2018). Image-Based Profiling of Patient-Derived Pancreatic Tumor–Stromal Cell Interactions Within a Micropatterned Tumor Model. Technology in Cancer Research & Treatment. 17. 1077071280–1077071280. 1 indexed citations
8.
Khong, Danika, et al.. (2017). Orthogonal potency analysis of mesenchymal stromal cell function during ex vivo expansion. Experimental Cell Research. 362(1). 102–110. 9 indexed citations
9.
Khong, Danika, et al.. (2017). An engineered biomarker system to monitor and modulate immune clearance of cell therapies. Cytotherapy. 19(12). 1537–1545. 1 indexed citations
10.
Mukundan, Shilpaa, et al.. (2016). Three-Dimensional Breast Cancer Models Mimic Hallmarks of Size-Induced Tumor Progression. Cancer Research. 76(13). 3732–3743. 61 indexed citations
11.
Shen, K. Robert, et al.. (2016). Suicide Gene-Engineered Stromal Cells Reveal a Dynamic Regulation of Cancer Metastasis. Scientific Reports. 6(1). 21239–21239. 12 indexed citations
12.
Patel, Akhil, Shilpaa Mukundan, Wenhu Wang, et al.. (2016). Carbon-based hierarchical scaffolds for myoblast differentiation: Synergy between nano-functionalization and alignment. Acta Biomaterialia. 32. 77–88. 59 indexed citations
13.
Patel, Akhil, Yingfei Xue, Shilpaa Mukundan, et al.. (2016). Cell-Instructive Graphene-Containing Nanocomposites Induce Multinucleated Myotube Formation. Annals of Biomedical Engineering. 44(6). 2036–2048. 32 indexed citations
14.
Close, David A., et al.. (2015). Production of Uniform 3D Microtumors in Hydrogel Microwell Arrays for Measurement of Viability, Morphology, and Signaling Pathway Activation. Assay and Drug Development Technologies. 13(9). 570–583. 55 indexed citations
15.
Mukundan, Shilpaa, et al.. (2015). Nanofibrous composite scaffolds of poly(ester amides) with tunable physicochemical and degradation properties. European Polymer Journal. 68. 21–35. 19 indexed citations
16.
Gaharwar, Akhilesh K., Shilpaa Mukundan, Elif Karaca, et al.. (2014). Nanoclay-Enriched Poly(ɛ-caprolactone) Electrospun Scaffolds for Osteogenic Differentiation of Human Mesenchymal Stem Cells. Tissue Engineering Part A. 20(15-16). 2088–2101. 132 indexed citations
17.
Patel, Alpesh, Akhilesh K. Gaharwar, Giorgio Iviglia, et al.. (2013). Highly elastomeric poly(glycerol sebacate)-co-poly(ethylene glycol) amphiphilic block copolymers. Biomaterials. 34(16). 3970–3983. 150 indexed citations
18.
Zhang, Hongbin, Alpesh Patel, Akhilesh K. Gaharwar, et al.. (2013). Hyperbranched Polyester Hydrogels with Controlled Drug Release and Cell Adhesion Properties. Biomacromolecules. 14(5). 1299–1310. 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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