Laura Gribaldo

4.3k total citations
107 papers, 2.7k citations indexed

About

Laura Gribaldo is a scholar working on Molecular Biology, Health, Toxicology and Mutagenesis and Cancer Research. According to data from OpenAlex, Laura Gribaldo has authored 107 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Molecular Biology, 22 papers in Health, Toxicology and Mutagenesis and 18 papers in Cancer Research. Recurrent topics in Laura Gribaldo's work include Animal testing and alternatives (17 papers), 3D Printing in Biomedical Research (14 papers) and Heavy Metal Exposure and Toxicity (12 papers). Laura Gribaldo is often cited by papers focused on Animal testing and alternatives (17 papers), 3D Printing in Biomedical Research (14 papers) and Heavy Metal Exposure and Toxicity (12 papers). Laura Gribaldo collaborates with scholars based in Italy, Belgium and United States. Laura Gribaldo's co-authors include Augusto Pessina, Thomas Härtung, Marco Fabbri, Cristina Croera, Pasquale Melchioretto, Chiara Urani, Gerard Bowe, Silvia Casati, Raffaella Corvi and Sebastian Hoffmann and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Applied and Environmental Microbiology and Scientific Reports.

In The Last Decade

Laura Gribaldo

107 papers receiving 2.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Laura Gribaldo Italy 31 835 748 377 361 337 107 2.7k
Sandra Coecke Italy 36 1.1k 1.3× 730 1.0× 701 1.9× 339 0.9× 309 0.9× 114 3.5k
Susan Hester United States 29 1.2k 1.4× 633 0.8× 81 0.2× 415 1.1× 316 0.9× 72 2.8k
Robert C. Sills United States 30 1.1k 1.3× 471 0.6× 218 0.6× 817 2.3× 287 0.9× 137 2.8k
Tamara Vanhaecke Belgium 39 2.9k 3.4× 299 0.4× 148 0.4× 429 1.2× 183 0.5× 232 5.2k
Heidrun Ellinger‐Ziegelbauer Germany 27 1.5k 1.9× 278 0.4× 107 0.3× 720 2.0× 199 0.6× 66 2.6k
Takayoshi Suzuki Japan 33 1.7k 2.0× 572 0.8× 84 0.2× 1.6k 4.5× 200 0.6× 177 3.8k
Vera Bianchi Italy 39 2.6k 3.1× 696 0.9× 67 0.2× 648 1.8× 245 0.7× 129 4.4k
Marilyn J. Aardema United States 40 1.8k 2.2× 1.6k 2.2× 699 1.9× 2.6k 7.1× 157 0.5× 98 5.0k
Clive Meredith United Kingdom 24 424 0.5× 622 0.8× 136 0.4× 536 1.5× 150 0.4× 80 1.7k
Martha M. Moore United States 40 2.0k 2.3× 967 1.3× 213 0.6× 2.2k 6.2× 112 0.3× 144 4.4k

Countries citing papers authored by Laura Gribaldo

Since Specialization
Citations

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

Fields of papers citing papers by Laura Gribaldo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Laura Gribaldo

This figure shows the co-authorship network connecting the top 25 collaborators of Laura Gribaldo. A scholar is included among the top collaborators of Laura Gribaldo 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 Laura Gribaldo. Laura Gribaldo 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.
Fischer, Dagmar, Georg Fluegen, Nassim Ghaffari‐Tabrizi‐Wizsy, et al.. (2022). The CAM Model—Q&A with Experts. Cancers. 15(1). 191–191. 38 indexed citations
2.
Gribaldo, Laura, et al.. (2021). EURL ECVAM Review of non-animal models in biomedical research - Immuno-oncology. Open MIND. 1 indexed citations
3.
Gribaldo, Laura, et al.. (2021). EURL ECVAM Review of non-animal models in biomedical research - Neurodegenerative Diseases. Open MIND. 1 indexed citations
4.
Campia, Ivana, et al.. (2020). EURL ECVAM Review of non-animal models in biomedical research - Respiratory tract diseases. Open MIND. 2 indexed citations
5.
Lacroix, Ghislaine, Wolfgang Koch, Detlef Ritter, et al.. (2018). Air–Liquid Interface In Vitro Models for Respiratory Toxicology Research: Consensus Workshop and Recommendations. PubMed. 4(2). 91–106. 160 indexed citations
6.
Urani, Chiara, Pasquale Melchioretto, Maurizio Bruschi, et al.. (2015). Impact of Cadmium on Intracellular Zinc Levels in HepG2 Cells: Quantitative Evaluations and Molecular Effects. BioMed Research International. 2015. 1–10. 30 indexed citations
7.
Pallocca, Giorgia, Marco Fabbri, Maria Grazia Sacco, et al.. (2013). miRNA expression profiling in a human stem cell-based model as a tool for developmental neurotoxicity testing. Cell Biology and Toxicology. 29(4). 239–257. 53 indexed citations
8.
Nerini‐Molteni, Silvia, Milena Mennecozzi, Marco Fabbri, et al.. (2012). MicroRNA Profiling as a Tool for Pathway Analysis in a Human In Vitro Model for Neural Development. Current Medicinal Chemistry. 19(36). 6214–6223. 14 indexed citations
9.
Coccini, Teresa, E. Roda, Marco Fabbri, et al.. (2012). Gene expression profiling in rat kidney after intratracheal exposure to cadmium-doped nanoparticles. Journal of Nanoparticle Research. 14(8). 13 indexed citations
10.
Pessina, Augusto, Arianna Bonomi, Francesca Sisto, et al.. (2010). CD45+/CD133+ positive cells expanded from umbilical cord blood expressing PDX‐1 and markers of pluripotency. Cell Biology International. 34(8). 783–790. 5 indexed citations
11.
Pessina, Augusto, et al.. (2009). Refinement and Optimisation of the Rat CFU-GM Assay to Incorporate the Use of Cryopreserved Bone-marrow Cells for In Vitro Toxicology Applications. Alternatives to Laboratory Animals. 37(4). 417–425. 4 indexed citations
12.
Pessina, Augusto, Arianna Bonomi, Loredana Cavicchini, et al.. (2008). Microbiological Risk Assessment in Stem Cell Manipulation. Critical Reviews in Microbiology. 34(1). 1–12. 5 indexed citations
13.
14.
Pessina, Augusto & Laura Gribaldo. (2006). The key role of adult stem cells: therapeutic perspectives. Current Medical Research and Opinion. 22(11). 2287–2300. 53 indexed citations
15.
Gribaldo, Laura, et al.. (2005). Induction of apoptosis and inhibition of telomerase activity in human bone marrow and HL-60 p53 null cells treated with anti-cancer drugs. Toxicology in Vitro. 19(4). 523–532. 11 indexed citations
16.
17.
Gribaldo, Laura, Silvia Casati, Anna Federica Castoldi, & Augusto Pessina. (1999). Comparison of in vitro drug-sensitivity of human granulocyte-macrophage progenitors from two different origins. Experimental Hematology. 27(11). 1593–1598. 21 indexed citations
18.
Spielmann, Horst, Н. П. Бочков, Lucio G. Costa, et al.. (1998). 13th Meeting of the Scientific Group on Methodologies for the Safety Evaluation of Chemicals (SGOMSEC): alternative testing methodologies for organ toxicity.. Environmental Health Perspectives. 106(suppl 2). 427–439. 26 indexed citations
19.
Gribaldo, Laura, et al.. (1998). Drug Sensitivity of Granulocyte-Macrophage Precursors (CFU-GM) from Fresh Murine Bone Marrow and from Long-Term Bone Marrow Cultures.. Toxicology in Vitro. 12(1). 39–45. 8 indexed citations
20.
Sacco, Maria Grazia, Laura Gribaldo, Ottavia Barbieri, et al.. (1998). Establishment and characterization of a new mammary adenocarcinoma cell line derived from MMTV neu transgenic mice. Breast Cancer Research and Treatment. 47(2). 171–180. 25 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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