Alberto Nassi

469 total citations
9 papers, 307 citations indexed

About

Alberto Nassi is a scholar working on Pharmacology, Molecular Biology and Oncology. According to data from OpenAlex, Alberto Nassi has authored 9 papers receiving a total of 307 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Pharmacology, 2 papers in Molecular Biology and 2 papers in Oncology. Recurrent topics in Alberto Nassi's work include Pharmacogenetics and Drug Metabolism (4 papers), Drug-Induced Hepatotoxicity and Protection (3 papers) and Drug Transport and Resistance Mechanisms (2 papers). Alberto Nassi is often cited by papers focused on Pharmacogenetics and Drug Metabolism (4 papers), Drug-Induced Hepatotoxicity and Protection (3 papers) and Drug Transport and Resistance Mechanisms (2 papers). Alberto Nassi collaborates with scholars based in Italy and France. Alberto Nassi's co-authors include Maura Floreani, Luigi Quintieri, Pietro Palatini, Paolo Ruzza, Andrea Cignarella, Chiara Bolego, Alice Toniolo, Serena Tedesco, Gian Paolo Fadini and Massimo Locati and has published in prestigious journals such as Nature Communications, PLoS ONE and Journal of Medicinal Chemistry.

In The Last Decade

Alberto Nassi

9 papers receiving 300 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Alberto Nassi Italy	8	122	71	47	44	31	9	307
Ishtiaq Mahmud Japan	11	113 0.9×	58 0.8×	41 0.9×	26 0.6×	34 1.1×	23	383
Xiangpeng Kong China	11	166 1.4×	46 0.6×	30 0.6×	25 0.6×	30 1.0×	21	361
Sheikh Rayees India	12	187 1.5×	43 0.6×	102 2.2×	70 1.6×	45 1.5×	23	441
Chih‐Chuan Teng Taiwan	16	297 2.4×	104 1.5×	40 0.9×	63 1.4×	24 0.8×	24	542
Ji-Hae Lee South Korea	9	246 2.0×	68 1.0×	37 0.8×	54 1.2×	38 1.2×	11	415
Ying‐Ling Chang Taiwan	12	171 1.4×	66 0.9×	58 1.2×	50 1.1×	57 1.8×	15	376
Yee Jin Yun South Korea	13	221 1.8×	54 0.8×	42 0.9×	67 1.5×	75 2.4×	14	400
Seung Hyo Jung South Korea	11	193 1.6×	28 0.4×	40 0.9×	19 0.4×	47 1.5×	28	387
Mei Jin China	9	176 1.4×	35 0.5×	30 0.6×	32 0.7×	24 0.8×	16	388

Countries citing papers authored by Alberto Nassi

Since Specialization

Citations

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

Fields of papers citing papers by Alberto Nassi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alberto Nassi

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

All Works

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9 of 9 papers shown

Nassi, Alberto, Luigi Quintieri, Roberta Merlanti, et al.. (2020). Midazolam oxidation in cattle liver microsomes: The role of cytochrome P450 3A. Journal of Veterinary Pharmacology and Therapeutics. 43(6). 608–613. 3 indexed citations

Badin, Romina Aron, Aurore Bugi, Susannah Williams, et al.. (2019). MHC matching fails to prevent long-term rejection of iPSC-derived neurons in non-human primates. Nature Communications. 10(1). 4357–4357. 60 indexed citations

Nassi, Alberto, et al.. (2016). Upregulation of inducible NO synthase by exogenous adenosine in vascular smooth muscle cells activated by inflammatory stimuli in experimental diabetes. Cardiovascular Diabetology. 15(1). 32–32. 10 indexed citations

Tedesco, Serena, Chiara Bolego, Alice Toniolo, et al.. (2014). Phenotypic activation and pharmacological outcomes of spontaneously differentiated human monocyte-derived macrophages. Immunobiology. 220(5). 545–554. 73 indexed citations

Toniolo, Alice, et al.. (2013). Regulation of SIRT1 in Vascular Smooth Muscle Cells from Streptozotocin-Diabetic Rats. PLoS ONE. 8(5). e65666–e65666. 19 indexed citations

Floreani, Maura, Sara De Martin, Daniela Gabbia, et al.. (2013). Severe Liver Cirrhosis Markedly Reduces AhR-Mediated Induction of Cytochrome P450 in Rats by Decreasing the Transcription of Target Genes. PLoS ONE. 8(4). e61983–e61983. 12 indexed citations

Quintieri, Luigi, et al.. (2010). Flavonoids Diosmetin and Hesperetin are Potent Inhibitors of Cytochrome P450 2C9-mediated Drug Metabolism in vitro. Drug Metabolism and Pharmacokinetics. 25(5). 466–476. 33 indexed citations

Ruzza, Paolo, Antonio Rosato, Alberto Nassi, et al.. (2009). Synthesis and Preliminary in Vitro Biological Evaluation of 4-[(4-Hydroxyphenyl)sulfanyl]but-3-en-2-one, a 4-Mercaptophenol Derivative Designed As a Novel Bifunctional Antimelanoma Agent. Journal of Medicinal Chemistry. 52(15). 4973–4976. 11 indexed citations

Quintieri, Luigi, Pietro Palatini, Alberto Nassi, Paolo Ruzza, & Maura Floreani. (2007). Flavonoids diosmetin and luteolin inhibit midazolam metabolism by human liver microsomes and recombinant CYP 3A4 and CYP3A5 enzymes. Biochemical Pharmacology. 75(6). 1426–1437. 86 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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