Nicola Tinari

7.7k total citations · 1 hit paper
120 papers, 5.1k citations indexed

About

Nicola Tinari is a scholar working on Oncology, Molecular Biology and Immunology. According to data from OpenAlex, Nicola Tinari has authored 120 papers receiving a total of 5.1k indexed citations (citations by other indexed papers that have themselves been cited), including 59 papers in Oncology, 52 papers in Molecular Biology and 45 papers in Immunology. Recurrent topics in Nicola Tinari's work include Galectins and Cancer Biology (36 papers), Glycosylation and Glycoproteins Research (21 papers) and Toxin Mechanisms and Immunotoxins (15 papers). Nicola Tinari is often cited by papers focused on Galectins and Cancer Biology (36 papers), Glycosylation and Glycoproteins Research (21 papers) and Toxin Mechanisms and Immunotoxins (15 papers). Nicola Tinari collaborates with scholars based in Italy, United States and United Kingdom. Nicola Tinari's co-authors include Stefano Iacobelli, Clara Natoli, Gabriel A. Rabinovich, Fu‐Tong Liu, Antonino Grassadonia, Albana Cumashi, Ida Iurisci, Nikolay E. Nifantiev, Linda G. Baum and Roberto Paganelli and has published in prestigious journals such as Nature Communications, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Nicola Tinari

116 papers receiving 5.0k citations

Hit Papers

A comparative study of the anti-inflammatory, anticoagula... 2007 2026 2013 2019 2007 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nicola Tinari Italy 35 2.2k 2.0k 1.5k 809 420 120 5.1k
Manish S. Patankar United States 35 1.5k 0.7× 1.9k 0.9× 798 0.5× 339 0.4× 386 0.9× 99 4.6k
Masahiro Kizaki Japan 47 739 0.3× 3.1k 1.5× 1.3k 0.8× 206 0.3× 422 1.0× 230 5.8k
Jian Liu China 43 1.4k 0.6× 3.4k 1.7× 1.3k 0.8× 187 0.2× 1.5k 3.5× 307 6.9k
Xiao Liang China 34 1.0k 0.5× 1.7k 0.8× 1.1k 0.8× 89 0.1× 581 1.4× 143 4.2k
Antonino Bruno Italy 29 1.4k 0.6× 1.3k 0.6× 1.0k 0.7× 79 0.1× 546 1.3× 90 3.6k
Bård Smedsrød Norway 44 1.3k 0.6× 2.1k 1.0× 712 0.5× 150 0.2× 600 1.4× 132 6.5k
Dominique Lombardo France 38 683 0.3× 2.7k 1.3× 1.0k 0.7× 178 0.2× 640 1.5× 130 5.1k
Melchiorre Cervello Italy 44 555 0.3× 3.4k 1.7× 1.3k 0.8× 93 0.1× 1.1k 2.5× 137 6.0k
Tianfu Wu United States 33 1.5k 0.7× 966 0.5× 298 0.2× 121 0.1× 155 0.4× 98 3.4k
Roger Chammas Brazil 41 1.8k 0.8× 3.2k 1.6× 896 0.6× 43 0.1× 852 2.0× 256 5.5k

Countries citing papers authored by Nicola Tinari

Since Specialization
Citations

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

Fields of papers citing papers by Nicola Tinari

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nicola Tinari

This figure shows the co-authorship network connecting the top 25 collaborators of Nicola Tinari. A scholar is included among the top collaborators of Nicola Tinari 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 Nicola Tinari. Nicola Tinari 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.
Pellegrino, Raffaello, David Perpetuini, Roberto Paganelli, et al.. (2025). Galectin-3-binding protein is a risk factor for diabetes, metabolic syndrome, and inflammation. Cross-sectional and longitudinal results from the InCHIANTI study. Mechanisms of Ageing and Development. 226. 112086–112086.
2.
Macchia, Marco, Nicola Tinari, Davide Brocco, et al.. (2025). RECIST progression: Patterns among target, non-target, non-measurable and new lesions progression. European Journal of Radiology. 186. 112038–112038.
3.
Guerra, Emanuela, Marco Trerotola, Valeria Relli, et al.. (2024). Phylogenetic conservation of Trop-2 across species—rodent and primate genomics model anti-Trop-2 therapy for pre-clinical benchmarks. Frontiers in Genetics. 14. 1297367–1297367. 1 indexed citations
5.
Guerra, Emanuela, Marco Trerotola, Rossano Lattanzio, et al.. (2023). 3D-Informed Targeting of the Trop-2 Signal-Activation Site Drives Selective Cancer Vulnerability. Molecular Cancer Therapeutics. 22(6). 790–804. 12 indexed citations
6.
Brocco, Davide, Pasquale Simeone, Simone Vespa, et al.. (2022). Flow Cytometry Detection of Anthracycline-Treated Breast Cancer Cells: An Optimized Protocol. Current Issues in Molecular Biology. 45(1). 164–174. 7 indexed citations
7.
Brocco, Davide, Pasquale Simeone, Pietro Di Marino, et al.. (2022). Blood Circulating CD133+ Extracellular Vesicles Predict Clinical Outcomes in Patients with Metastatic Colorectal Cancer. Cancers. 14(5). 1357–1357. 24 indexed citations
8.
Brocco, Davide, Paola Lanuti, Damiana Pieragostino, et al.. (2021). Phenotypic and Proteomic Analysis Identifies Hallmarks of Blood Circulating Extracellular Vesicles in NSCLC Responders to Immune Checkpoint Inhibitors. Cancers. 13(4). 585–585. 31 indexed citations
9.
Pagotto, Sara, Annalisa Nicotra, Tiziana Apuzzo, et al.. (2021). A perspective analysis: microRNAs, glucose metabolism, and drug resistance in colon cancer stem cells. Cancer Gene Therapy. 29(1). 4–9. 8 indexed citations
10.
Grassadonia, Antonino, Vincenzo Graziano, Laura Iezzi, et al.. (2021). Prognostic Relevance of Neutrophil to Lymphocyte Ratio (NLR) in Luminal Breast Cancer: A Retrospective Analysis in the Neoadjuvant Setting. Cells. 10(7). 1685–1685. 28 indexed citations
11.
Grassadonia, Antonino, et al.. (2020). Alectinib Induced Regression of Renal and Hepatic Cysts Caused by Crizotinib. SHILAP Revista de lepidopterología. 2 indexed citations
15.
Traini, Sara, Enza Piccolo, Nicola Tinari, et al.. (2014). Inhibition of Tumor Growth and Angiogenesis by SP-2, an Anti–Lectin, Galactoside-Binding Soluble 3 Binding Protein (LGALS3BP) Antibody. Molecular Cancer Therapeutics. 13(4). 916–925. 28 indexed citations
16.
Angelucci, Domenico, Nicola Tinari, Antonino Grassadonia, et al.. (2012). Long-term outcome of neoadjuvant systemic therapy for locally advanced breast cancer in routine clinical practice. Journal of Cancer Research and Clinical Oncology. 139(2). 269–280. 19 indexed citations
17.
Grassadonia, Antonino, Nicola Tinari, Ida Iurisci, et al.. (2002). 90K (Mac-2 BP) and galectins in tumor progression and metastasis. Glycoconjugate Journal. 19(7-9). 551–556. 147 indexed citations
18.
Tinari, Nicola, et al.. (2001). Glycoprotein 90K/MAC‐2BP interacts with galectin‐1 and mediates galectin‐1–induced cell aggregation. International Journal of Cancer. 91(2). 167–172. 86 indexed citations
19.
Briggs, Nathaniel C., Clara Natoli, Nicola Tinari, et al.. (1993). A 90-kDa Protein Serum Marker for the Prediction of Progression to AIDS in a Cohort of HIV-1 + Homosexual Men. AIDS Research and Human Retroviruses. 9(9). 811–816. 30 indexed citations
20.
Giuliani, Cesidio, et al.. (1992). Immunological effects of alternative weekly interferon-alpha-2b and low dose interleukin-2 in patients with cancer. British Journal of Cancer. 66(5). 981–983. 6 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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