Gabriele Cruciani

13.8k total citations
223 papers, 10.5k citations indexed

About

Gabriele Cruciani is a scholar working on Molecular Biology, Computational Theory and Mathematics and Organic Chemistry. According to data from OpenAlex, Gabriele Cruciani has authored 223 papers receiving a total of 10.5k indexed citations (citations by other indexed papers that have themselves been cited), including 113 papers in Molecular Biology, 79 papers in Computational Theory and Mathematics and 43 papers in Organic Chemistry. Recurrent topics in Gabriele Cruciani's work include Computational Drug Discovery Methods (79 papers), Analytical Chemistry and Chromatography (35 papers) and Spectroscopy and Chemometric Analyses (22 papers). Gabriele Cruciani is often cited by papers focused on Computational Drug Discovery Methods (79 papers), Analytical Chemistry and Chromatography (35 papers) and Spectroscopy and Chemometric Analyses (22 papers). Gabriele Cruciani collaborates with scholars based in Italy, United Kingdom and United States. Gabriele Cruciani's co-authors include Manuel Pastor, Massimo Baroni, Sérgio Clementi, Laura Goracci, Emanuele Carosati, Pierre‐Alain Carrupt, Bernard Testa, Patrizia Crivori, Simone Sciabola and Loriano Storchi and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Blood.

In The Last Decade

Gabriele Cruciani

217 papers receiving 10.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gabriele Cruciani Italy 55 5.0k 3.6k 2.4k 1.4k 1.1k 223 10.5k
Weiliang Zhu China 52 5.2k 1.0× 2.2k 0.6× 2.6k 1.1× 878 0.6× 844 0.7× 404 11.3k
Bernd Kuhn Switzerland 43 6.9k 1.4× 2.6k 0.7× 3.5k 1.5× 889 0.6× 1.3k 1.1× 109 12.7k
Kaixian Chen China 58 7.5k 1.5× 3.5k 1.0× 2.9k 1.2× 804 0.6× 932 0.8× 437 13.9k
Peter Ertl Switzerland 36 4.3k 0.9× 4.1k 1.2× 3.4k 1.4× 993 0.7× 616 0.5× 134 10.0k
Yun Tang China 48 5.2k 1.1× 5.1k 1.4× 2.0k 0.8× 650 0.5× 728 0.6× 347 11.3k
Jeremy R. Greenwood United States 27 6.8k 1.4× 3.2k 0.9× 2.9k 1.2× 493 0.3× 1.2k 1.1× 67 12.1k
Weihua Li China 47 5.1k 1.0× 5.1k 1.4× 1.5k 0.6× 583 0.4× 853 0.8× 251 10.8k
Anne Hersey United Kingdom 31 6.6k 1.3× 6.3k 1.8× 1.8k 0.8× 1.4k 1.0× 896 0.8× 49 11.7k
Tudor I. Oprea United States 68 9.4k 1.9× 6.6k 1.9× 2.3k 1.0× 1.3k 0.9× 1.7k 1.5× 244 18.6k
Sunghwan Kim United States 28 6.0k 1.2× 4.3k 1.2× 1.2k 0.5× 747 0.5× 602 0.5× 139 13.2k

Countries citing papers authored by Gabriele Cruciani

Since Specialization
Citations

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

Fields of papers citing papers by Gabriele Cruciani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gabriele Cruciani

This figure shows the co-authorship network connecting the top 25 collaborators of Gabriele Cruciani. A scholar is included among the top collaborators of Gabriele Cruciani 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 Gabriele Cruciani. Gabriele Cruciani 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.
Desantis, Jenny, et al.. (2024). Between Theory and Practice: Computational/Experimental Integrated Approaches to Understand the Solubility and Lipophilicity of PROTACs. Journal of Medicinal Chemistry. 67(18). 16355–16380. 2 indexed citations
2.
Cruciani, Gabriele, et al.. (2023). VHL-Modified PROteolysis TArgeting Chimeras (PROTACs) as a Strategy to Evade Metabolic Degradation in In Vitro Applications. Journal of Medicinal Chemistry. 66(18). 13148–13171. 7 indexed citations
3.
Gianquinto, Eleonora, Massimo Baroni, Gabriele Cruciani, et al.. (2023). Structure-Based Optimization of 1,2,4-Triazole-3-Thione Derivatives: Improving Inhibition of NDM-/VIM-Type Metallo-β-Lactamases and Synergistic Activity on Resistant Bacteria. Pharmaceuticals. 16(12). 1682–1682. 2 indexed citations
4.
Gianni’, Maurizio, Laura Goracci, Alessandra Di Veroli, et al.. (2022). Role of cardiolipins, mitochondria, and autophagy in the differentiation process activated by all-trans retinoic acid in acute promyelocytic leukemia. Cell Death and Disease. 13(1). 30–30. 4 indexed citations
5.
Criscuolo, Angela, Palina Nepachalovich, Mike Lange, et al.. (2022). Analytical and computational workflow for in-depth analysis of oxidized complex lipids in blood plasma. Nature Communications. 13(1). 6547–6547. 38 indexed citations
6.
Gaudio, Nunzio Del, Lucia Altucci, Lydia Siragusa, et al.. (2022). Discovery of a new class of triazole based inhibitors of acetyl transferase KAT2A. Journal of Enzyme Inhibition and Medicinal Chemistry. 37(1). 1987–1994. 1 indexed citations
7.
Vink, Pim J. de, et al.. (2022). Cooperativity as quantification and optimization paradigm for nuclear receptor modulators. Chemical Science. 13(9). 2744–2752. 11 indexed citations
8.
Gianquinto, Eleonora, et al.. (2021). Binding of Androgen- and Estrogen-Like Flavonoids to Their Cognate (Non)Nuclear Receptors: A Comparison by Computational Prediction. Molecules. 26(6). 1613–1613. 35 indexed citations
9.
Desantis, Jenny, Beatrice Mercorelli, Marta Celegato, et al.. (2021). Indomethacin-based PROTACs as pan-coronavirus antiviral agents. European Journal of Medicinal Chemistry. 226. 113814–113814. 72 indexed citations
10.
Bartolini, Desirée, Anna Maria Stabile, Carmine Vacca, et al.. (2021). Endoplasmic reticulum stress and NF‐kB activation in SARS‐CoV‐2 infected cells and their response to antiviral therapy. IUBMB Life. 74(1). 93–100. 36 indexed citations
11.
Gidari, Anna, Samuele Sabbatini, Sabrina Bastianelli, et al.. (2021). SARS-CoV-2 Survival on Surfaces and the Effect of UV-C Light. Viruses. 13(3). 408–408. 86 indexed citations
12.
Goracci, Laura, et al.. (2020). Understanding the Metabolism of Proteolysis Targeting Chimeras (PROTACs): The Next Step toward Pharmaceutical Applications. Journal of Medicinal Chemistry. 63(20). 11615–11638. 99 indexed citations
13.
Lee, Geun Taek, Jenny Desantis, Kiran Madura, et al.. (2020). Effects of MTX-23, a Novel PROTAC of Androgen Receptor Splice Variant-7 and Androgen Receptor, on CRPC Resistant to Second-Line Antiandrogen Therapy. Molecular Cancer Therapeutics. 20(3). 490–499. 73 indexed citations
14.
Terao, Mineko, Laura Goracci, Mami Kurosaki, et al.. (2019). Role of mitochondria and cardiolipins in growth inhibition of breast cancer cells by retinoic acid. Journal of Experimental & Clinical Cancer Research. 38(1). 436–436. 12 indexed citations
15.
Sciabola, Simone, Paolo Benedetti, Rubben Torella, et al.. (2018). Discovering New Casein Kinase 1d Inhibitors with an Innovative Molecular Dynamics Enabled Virtual Screening Workflow. ACS Medicinal Chemistry Letters. 10(4). 487–492. 9 indexed citations
16.
Russo, Angelo, Desirée Bartolini, Emanuela Mensa’, et al.. (2018). Physical Activity Modulates the Overexpression of the Inflammatory miR‐146a‐5p in Obese Patients. IUBMB Life. 70(10). 1012–1022. 29 indexed citations
17.
Barbera, Giorgia La, Michela Antonelli, Chiara Cavaliere, et al.. (2018). Delving into the Polar Lipidome by Optimized Chromatographic Separation, High-Resolution Mass Spectrometry, and Comprehensive Identification with Lipostar: Microalgae as Case Study. Analytical Chemistry. 90(20). 12230–12238. 18 indexed citations
18.
Sandomenico, Annamaria, Andrea Caporale, Nunzianna Doti, et al.. (2018). Synthetic Peptide Libraries: From Random Mixtures to In Vivo Testing. Current Medicinal Chemistry. 27(6). 997–1016. 10 indexed citations
19.
Cruciani, Gabriele, Paolo Benedetti, Susan Lepri, et al.. (2017). From Experiments to a Fast Easy-to-Use Computational Methodology to Predict Human Aldehyde Oxidase Selectivity and Metabolic Reactions. Journal of Medicinal Chemistry. 61(1). 360–371. 26 indexed citations
20.
Clementi, Sérgio, et al.. (1989). Comparison of chemometric methods in toxicology. 7(3). 57–61. 5 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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