Triantafyllos Stylianopoulos

19.6k total citations · 11 hit papers
167 papers, 14.9k citations indexed

About

Triantafyllos Stylianopoulos is a scholar working on Biomedical Engineering, Cell Biology and Oncology. According to data from OpenAlex, Triantafyllos Stylianopoulos has authored 167 papers receiving a total of 14.9k indexed citations (citations by other indexed papers that have themselves been cited), including 75 papers in Biomedical Engineering, 48 papers in Cell Biology and 41 papers in Oncology. Recurrent topics in Triantafyllos Stylianopoulos's work include Cellular Mechanics and Interactions (46 papers), Nanoplatforms for cancer theranostics (26 papers) and Nanoparticle-Based Drug Delivery (25 papers). Triantafyllos Stylianopoulos is often cited by papers focused on Cellular Mechanics and Interactions (46 papers), Nanoplatforms for cancer theranostics (26 papers) and Nanoparticle-Based Drug Delivery (25 papers). Triantafyllos Stylianopoulos collaborates with scholars based in Cyprus, United States and United Kingdom. Triantafyllos Stylianopoulos's co-authors include Rakesh K. Jain, John D. Martin, Lance L. Munn, Vikash P. Chauhan, Dai Fukumura, Panagiotis Papageorgis, Fotios Mpekris, Vasiliki Gkretsi, Chrysovalantis Voutouri and Victor H. Barocas and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Medicine and Nature Communications.

In The Last Decade

Triantafyllos Stylianopoulos

157 papers receiving 14.7k citations

Hit Papers

Delivering nanomedicine t... 2009 2026 2014 2020 2010 2012 2011 2014 2012 500 1000 1.5k 2.0k 2.5k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Delivering nanomedicine to solid tumors
    2010 2.5k citations Rakesh K. Jain, Triantafyllos Stylianopoulos profile →
  2. Normalization of tumour blood vessels improves the delivery of nanomedicines in a size-dependent manner
    2012 918 citations Vikash P. Chauhan, Triantafyllos Stylianopoulos et al. profile →
  3. Multistage nanoparticle delivery system for deep penetration into tumor tissue
    2011 895 citations Triantafyllos Stylianopoulos, John D. Martin et al. Proceedings of the National Academy of Sciences profile →
  4. The Role of Mechanical Forces in Tumor Growth and Therapy
    2014 754 citations Rakesh K. Jain, John D. Martin et al. profile →
  5. Causes, consequences, and remedies for growth-induced solid stress in murine and human tumors
    2012 682 citations Triantafyllos Stylianopoulos, John D. Martin et al. Proceedings of the National Academy of Sciences profile →
  6. Three-dimensional microscopy of the tumor microenvironment in vivo using optical frequency domain imaging
    2009 548 citations Ryan M. Lanning, Timothy P. Padera et al. profile →
  7. Improving cancer immunotherapy using nanomedicines: progress, opportunities and challenges
    2020 535 citations John D. Martin, Horacio Cabral et al. profile →
  8. Reengineering the Physical Microenvironment of Tumors to Improve Drug Delivery and Efficacy: From Mathematical Modeling to Bench to Bedside
    2018 425 citations Triantafyllos Stylianopoulos, Lance L. Munn et al. Trends in cancer profile →
  9. The Role of Tumor Microenvironment in Cancer Metastasis: Molecular Mechanisms and Therapeutic Opportunities
    2021 286 citations Myrofora Panagi, Triantafyllos Stylianopoulos et al. Cancers profile →
  10. Losartan treatment enhances chemotherapy efficacy and reduces ascites in ovarian cancer models by normalizing the tumor stroma
    2019 198 citations Triantafyllos Stylianopoulos, Fotios Mpekris et al. Proceedings of the National Academy of Sciences profile →
  11. Using mathematical modelling and AI to improve delivery and efficacy of therapies in cancer
    2025 19 citations Chrysovalantis Voutouri, Triantafyllos Stylianopoulos et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Triantafyllos Stylianopoulos Cyprus 51 7.3k 4.7k 4.3k 3.5k 2.6k 167 14.9k
Linda G. Griffith United States 71 11.2k 1.5× 5.4k 1.1× 5.4k 1.3× 2.2k 0.6× 2.4k 0.9× 221 21.0k
Yves Boucher United States 59 5.4k 0.7× 2.8k 0.6× 6.8k 1.6× 5.9k 1.7× 2.5k 1.0× 111 17.0k
Paolo A. Netti Italy 68 8.6k 1.2× 4.7k 1.0× 3.3k 0.8× 1.6k 0.4× 2.3k 0.9× 494 17.9k
Lance L. Munn United States 67 5.2k 0.7× 1.6k 0.3× 6.9k 1.6× 5.6k 1.6× 2.7k 1.0× 178 17.7k
Mauro Ferrari United States 62 9.6k 1.3× 8.2k 1.7× 7.4k 1.7× 1.7k 0.5× 616 0.2× 260 20.7k
Fan Yuan United States 47 4.3k 0.6× 3.4k 0.7× 5.0k 1.1× 1.5k 0.4× 589 0.2× 149 11.4k
John D. Martin United States 37 3.2k 0.4× 1.8k 0.4× 2.9k 0.7× 2.5k 0.7× 1.2k 0.4× 171 10.0k
Renata Pasqualini United States 69 2.4k 0.3× 2.4k 0.5× 12.0k 2.8× 4.4k 1.2× 1.5k 0.6× 243 20.5k
Wadih Arap United States 66 2.2k 0.3× 2.1k 0.4× 10.4k 2.4× 4.3k 1.2× 1.2k 0.4× 234 18.3k
Twan Lammers Germany 85 12.1k 1.7× 10.5k 2.2× 7.3k 1.7× 2.2k 0.6× 408 0.2× 332 24.8k

Countries citing papers authored by Triantafyllos Stylianopoulos

Since Specialization
Citations

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

Fields of papers citing papers by Triantafyllos Stylianopoulos

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Triantafyllos Stylianopoulos

This figure shows the co-authorship network connecting the top 25 collaborators of Triantafyllos Stylianopoulos. A scholar is included among the top collaborators of Triantafyllos Stylianopoulos 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 Triantafyllos Stylianopoulos. Triantafyllos Stylianopoulos 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.
Mishra, Aditya K., Golnaz Morad, Sarah B. Johnson, et al.. (2025). Mathematical Modeling and Association Analysis Decipher the Impact of the Gut Microbiome on Cancer Immunotherapy. Cancer Research. 85(16). 3139–3155.
2.
Kalli, Maria, Fotios Mpekris, Christina Michael, et al.. (2024). Mechanical forces inducing oxaliplatin resistance in pancreatic cancer can be targeted by autophagy inhibition. Communications Biology. 7(1). 1581–1581. 12 indexed citations
3.
Mpekris, Fotios, Myrofora Panagi, Chrysovalantis Voutouri, et al.. (2024). Tumor Microenvironment Reprogramming Improves Nanomedicine-Based Chemo-Immunotherapy in Sarcomas. Molecular Cancer Therapeutics. 23(11). 1555–1567. 6 indexed citations
4.
Voutouri, Chrysovalantis, et al.. (2024). A convolutional attention model for predicting response to chemo-immunotherapy from ultrasound elastography in mouse tumor models. SHILAP Revista de lepidopterología. 4(1). 203–203. 6 indexed citations
5.
Tomazou, Marios, Chrysovalantis Voutouri, Christina Michael, et al.. (2024). Oct4 is a gatekeeper of epithelial identity by regulating cytoskeletal organization in skin keratinocytes. Cell Reports. 43(3). 113859–113859. 1 indexed citations
6.
Theodorou, Ioannis G., Fotios Mpekris, Paris Papagiorgis, et al.. (2023). Gold Nanobipyramids for Near-Infrared Fluorescence-Enhanced Imaging and Treatment of Triple-Negative Breast Cancer. Cancers. 15(14). 3693–3693. 6 indexed citations
7.
Stylianou, Andreas, Chrysovalantis Voutouri, Fotios Mpekris, & Triantafyllos Stylianopoulos. (2023). Pancreatic Cancer Presents Distinct Nanomechanical Properties During Progression. Annals of Biomedical Engineering. 51(7). 1602–1615. 21 indexed citations
8.
Tzirakis, Konstantinos, Vangelis Sakkalis, Eleftheria Tzamali, et al.. (2023). An adaptive semi‐implicit finite element solver for brain cancer progression modeling. International Journal for Numerical Methods in Biomedical Engineering. 39(7). e3734–e3734. 1 indexed citations
9.
Kojima, Motohiro, Toshiyuki Suzuki, Genichiro Ishii, et al.. (2023). Relationships between physical and immunological tumor microenvironment in pancreatic ductal adenocarcinoma. Cancer Science. 114(9). 3783–3792. 3 indexed citations
10.
Kalli, Maria, et al.. (2023). Beyond matrix stiffness: targeting force-induced cancer drug resistance. Trends in cancer. 9(11). 937–954. 82 indexed citations
11.
Martin, John D., Ryan M. Lanning, Vikash P. Chauhan, et al.. (2022). Multiphoton Phosphorescence Quenching Microscopy Reveals Kinetics of Tumor Oxygenation during Antiangiogenesis and Angiotensin Signaling Inhibition. Clinical Cancer Research. 28(14). 3076–3090. 8 indexed citations
12.
Voutouri, Chrysovalantis, Mohammad R. Nikmaneshi, C. Corey Hardin, et al.. (2021). In silico dynamics of COVID-19 phenotypes for optimizing clinical management. Proceedings of the National Academy of Sciences. 118(3). 34 indexed citations
13.
Voutouri, Chrysovalantis, et al.. (2020). Biomechanical modelling of spinal tumour anisotropic growth. Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences. 476(2238). 20190364–20190364. 14 indexed citations
14.
Emblem, Kyrre E., et al.. (2018). Towards patient-specific modeling of brain tumor growth and formation of secondary nodes guided by DTI-MRI. NeuroImage Clinical. 20. 664–673. 37 indexed citations
15.
Voutouri, Chrysovalantis, Vasiliki Gkretsi, Ivo Šafařı́k, et al.. (2018). Tuning the Mechanical Properties of BIEE‐Crosslinked Semi‐Interpenetrating, Double‐Hydrophilic Hydrogels. Macromolecular Materials and Engineering. 303(6). 3 indexed citations
16.
Wijeratne, P. A., John H. Hipwell, David J. Hawkes, Triantafyllos Stylianopoulos, & Vasileios Vavourakis. (2017). Multiscale biphasic modelling of peritumoural collagen microstructure: The effect of tumour growth on permeability and fluid flow. PLoS ONE. 12(9). e0184511–e0184511. 11 indexed citations
17.
Stylianopoulos, Triantafyllos, John D. Martin, Matija Snuderl, et al.. (2013). Coevolution of Solid Stress and Interstitial Fluid Pressure in Tumors During Progression: Implications for Vascular Collapse. Cancer Research. 73(13). 3833–3841. 352 indexed citations
18.
Baish, James W., Triantafyllos Stylianopoulos, Ryan M. Lanning, et al.. (2011). Scaling rules for diffusive drug delivery in tumor and normal tissues. Proceedings of the National Academy of Sciences. 108(5). 1799–1803. 142 indexed citations
19.
Stylianopoulos, Triantafyllos, et al.. (2009). Mathematical Modeling of Herpes Simplex Virus Distribution in Solid Tumors: Implications for Cancer Gene Therapy. Clinical Cancer Research. 15(7). 2352–2360. 73 indexed citations
20.
Sander, Edward A., Triantafyllos Stylianopoulos, Robert T. Tranquillo, & Victor H. Barocas. (2009). Image-based biomechanics of collagen-based tissue equivalents. IEEE Engineering in Medicine and Biology Magazine. 28(3). 10–18. 42 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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