Matteo Turetta

670 total citations
17 papers, 496 citations indexed

About

Matteo Turetta is a scholar working on Oncology, Cancer Research and Biomedical Engineering. According to data from OpenAlex, Matteo Turetta has authored 17 papers receiving a total of 496 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Oncology, 5 papers in Cancer Research and 5 papers in Biomedical Engineering. Recurrent topics in Matteo Turetta's work include Cancer Cells and Metastasis (7 papers), Cancer Genomics and Diagnostics (4 papers) and Innovative Microfluidic and Catalytic Techniques Innovation (3 papers). Matteo Turetta is often cited by papers focused on Cancer Cells and Metastasis (7 papers), Cancer Genomics and Diagnostics (4 papers) and Innovative Microfluidic and Catalytic Techniques Innovation (3 papers). Matteo Turetta collaborates with scholars based in Italy, Netherlands and Australia. Matteo Turetta's co-authors include Fabio Del Ben, Michela Bulfoni, Daniela Cesselli, G. Scoles, Carla Di Loreto, Antonio Paolo Beltrami, Aigars Piruska, Wilhelm T. S. Huck, Giorgia Celetti and Stefania Marzinotto and has published in prestigious journals such as Angewandte Chemie International Edition, Scientific Reports and International Journal of Molecular Sciences.

In The Last Decade

Matteo Turetta

17 papers receiving 494 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matteo Turetta Italy 10 237 185 175 138 73 17 496
Fabio Del Ben Italy 10 240 1.0× 185 1.0× 175 1.0× 153 1.1× 70 1.0× 35 522
Si-Hong Lu Taiwan 9 325 1.4× 126 0.7× 254 1.5× 263 1.9× 113 1.5× 10 677
Yiping Gong China 11 176 0.7× 224 1.2× 84 0.5× 273 2.0× 29 0.4× 18 562
Huangpin B. Hsieh United States 8 437 1.8× 271 1.5× 283 1.6× 145 1.1× 136 1.9× 16 653
Oliver Böcher Germany 9 343 1.4× 162 0.9× 215 1.2× 129 0.9× 103 1.4× 11 507
Shoujie Zhao China 10 66 0.3× 76 0.4× 118 0.7× 202 1.5× 56 0.8× 27 502
Francisco G. Ortega Spain 19 339 1.4× 309 1.7× 521 3.0× 643 4.7× 143 2.0× 33 1.1k
Jia Huang China 13 121 0.5× 184 1.0× 44 0.3× 245 1.8× 50 0.7× 25 500
Bin Hong United States 8 184 0.8× 308 1.7× 120 0.7× 215 1.6× 58 0.8× 14 608
Udara Dharmasiri United States 8 212 0.9× 505 2.7× 85 0.5× 160 1.2× 19 0.3× 8 651

Countries citing papers authored by Matteo Turetta

Since Specialization
Citations

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

Fields of papers citing papers by Matteo Turetta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matteo Turetta

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

All Works

17 of 17 papers shown
1.
Matrone, Fabio, Fabio Del Ben, Marcella Montico, et al.. (2024). Prognostic value of circulating tumor cells in oligorecurrent hormone‐sensitive prostate cancer patients undergoing stereotactic body radiation therapy. The Prostate. 84(16). 1468–1478. 2 indexed citations
2.
Brisotto, Giulia, Marcella Montico, Matteo Turetta, et al.. (2023). Integration of Cellular and Humoral Immune Responses as an Immunomonitoring Tool for SARS-CoV-2 Vaccination in Healthy and Fragile Subjects. Viruses. 15(6). 1276–1276. 2 indexed citations
3.
Ben, Fabio Del, et al.. (2023). A fully interpretable machine learning model for increasing the effectiveness of urine screening. American Journal of Clinical Pathology. 160(6). 620–632. 3 indexed citations
4.
Ben, Fabio Del, Michela Bulfoni, Matteo Turetta, et al.. (2022). Image Analysis of Circulating Tumor Cells and Leukocytes Predicts Survival and Metastatic Pattern in Breast Cancer Patients. Frontiers in Oncology. 12. 725318–725318. 6 indexed citations
5.
Muraro, Elena, Fabio Del Ben, Matteo Turetta, et al.. (2022). Clinical relevance of the combined analysis of circulating tumor cells and anti-tumor T-cell immunity in metastatic breast cancer patients. Frontiers in Oncology. 12. 983887–983887. 7 indexed citations
6.
Turetta, Matteo, et al.. (2022). An antivenin resistant, IVIg-corticosteroids responsive viper induced thrombocytopenia. Toxicology Reports. 9. 636–639. 1 indexed citations
7.
Brisotto, Giulia, Elena Muraro, Marcella Montico, et al.. (2021). IgG antibodies against SARS-CoV-2 decay but persist 4 months after vaccination in a cohort of healthcare workers. Clinica Chimica Acta. 523. 476–482. 29 indexed citations
8.
Brisotto, Giulia, Elisabetta Rossi, Michela Bulfoni, et al.. (2020). Dysmetabolic Circulating Tumor Cells Are Prognostic in Metastatic Breast Cancer. Cancers. 12(4). 1005–1005. 9 indexed citations
9.
Cesselli, Daniela, Tamara Ius, Miriam Isola, et al.. (2019). Application of an Artificial Intelligence Algorithm to Prognostically Stratify Grade II Gliomas. Cancers. 12(1). 50–50. 14 indexed citations
10.
Turetta, Matteo, Fabio Del Ben, Giulia Brisotto, et al.. (2018). Emerging Technologies for Cancer Research: Towards Personalized Medicine with Microfluidic Platforms and 3D Tumor Models. Current Medicinal Chemistry. 25(35). 4616–4637. 29 indexed citations
11.
Turetta, Matteo, Michela Bulfoni, Giulia Brisotto, et al.. (2018). Assessment of the Mutational Status of NSCLC Using Hypermetabolic Circulating Tumor Cells. Cancers. 10(8). 270–270. 13 indexed citations
12.
Ben, Fabio Del, Giulia Brisotto, Michela Bulfoni, et al.. (2018). Microfluidic droplets content classification and analysis through convolutional neural networks in a liquid biopsy workflow.. PubMed. 10(12). 4004–4016. 8 indexed citations
13.
Bulfoni, Michela, Lorenzo Gerratana, Fabio Del Ben, et al.. (2016). In patients with metastatic breast cancer the identification of circulating tumor cells in epithelial-to-mesenchymal transition is associated with a poor prognosis. Breast Cancer Research. 18(1). 30–30. 128 indexed citations
14.
Venturelli, Leonardo, Silvia Nappini, Michela Bulfoni, et al.. (2016). Glucose is a key driver for GLUT1-mediated nanoparticles internalization in breast cancer cells. Scientific Reports. 6(1). 21629–21629. 61 indexed citations
15.
Bulfoni, Michela, Matteo Turetta, Fabio Del Ben, et al.. (2016). Dissecting the Heterogeneity of Circulating Tumor Cells in Metastatic Breast Cancer: Going Far Beyond the Needle in the Haystack. International Journal of Molecular Sciences. 17(10). 1775–1775. 52 indexed citations
16.
Ben, Fabio Del, Matteo Turetta, Giorgia Celetti, et al.. (2016). A Method for Detecting Circulating Tumor Cells Based on the Measurement of Single‐Cell Metabolism in Droplet‐Based Microfluidics. Angewandte Chemie. 128(30). 8723–8726. 26 indexed citations
17.
Ben, Fabio Del, Matteo Turetta, Giorgia Celetti, et al.. (2016). A Method for Detecting Circulating Tumor Cells Based on the Measurement of Single‐Cell Metabolism in Droplet‐Based Microfluidics. Angewandte Chemie International Edition. 55(30). 8581–8584. 106 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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