Lorenza A. D’Alessandro

589 total citations
15 papers, 412 citations indexed

About

Lorenza A. D’Alessandro is a scholar working on Molecular Biology, Hepatology and Cell Biology. According to data from OpenAlex, Lorenza A. D’Alessandro has authored 15 papers receiving a total of 412 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 6 papers in Hepatology and 3 papers in Cell Biology. Recurrent topics in Lorenza A. D’Alessandro's work include Liver physiology and pathology (5 papers), PI3K/AKT/mTOR signaling in cancer (3 papers) and Viral Infectious Diseases and Gene Expression in Insects (2 papers). Lorenza A. D’Alessandro is often cited by papers focused on Liver physiology and pathology (5 papers), PI3K/AKT/mTOR signaling in cancer (3 papers) and Viral Infectious Diseases and Gene Expression in Insects (2 papers). Lorenza A. D’Alessandro collaborates with scholars based in Germany, United States and Italy. Lorenza A. D’Alessandro's co-authors include Ursula Klingmüller, Matthias W. Hentze, Martina U. Muckenthaler, Maja Vujić Spasić, M. Castoldi, Sandro Altamura, Hermann Joseph Gröne, Jens Stolte, Robert E. Fleming and Vladimı́r Beneš and has published in prestigious journals such as Journal of Clinical Investigation, Blood and Cancer Research.

In The Last Decade

Lorenza A. D’Alessandro

15 papers receiving 409 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lorenza A. D’Alessandro Germany 9 239 159 101 63 48 15 412
Suk Mei Wang Singapore 6 223 0.9× 133 0.8× 25 0.2× 10 0.2× 44 0.9× 6 403
Aaron M. Domina United States 6 353 1.5× 51 0.3× 54 0.5× 23 0.4× 27 0.6× 9 429
Donna Hewitt Canada 5 194 0.8× 63 0.4× 13 0.1× 40 0.6× 9 0.2× 12 351
Lara M. Cullen Australia 8 375 1.6× 206 1.3× 336 3.3× 273 4.3× 13 0.3× 15 794
Langzhu Tan United States 8 252 1.1× 53 0.3× 17 0.2× 10 0.2× 18 0.4× 9 362
Meletios Verras United States 8 413 1.7× 98 0.6× 12 0.1× 11 0.2× 27 0.6× 11 605
Masumi Yoshie Japan 8 191 0.8× 108 0.7× 19 0.2× 13 0.2× 51 1.1× 15 392
Sandrine Cariou France 7 257 1.1× 44 0.3× 29 0.3× 25 0.4× 123 2.6× 7 538
N Wong Hong Kong 7 179 0.7× 83 0.5× 11 0.1× 25 0.4× 22 0.5× 12 336
Valentina Doneddu Italy 11 175 0.7× 110 0.7× 27 0.3× 16 0.3× 20 0.4× 17 336

Countries citing papers authored by Lorenza A. D’Alessandro

Since Specialization
Citations

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

Fields of papers citing papers by Lorenza A. D’Alessandro

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lorenza A. D’Alessandro. 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 Lorenza A. D’Alessandro. The network helps show where Lorenza A. D’Alessandro may publish in the future.

Co-authorship network of co-authors of Lorenza A. D’Alessandro

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

All Works

15 of 15 papers shown
1.
Laue, Hendrik, Nick Weiss, Uta Dahmen, et al.. (2022). Automated Detection of Portal Fields and Central Veins in Whole-Slide Images of Liver Tissue. Journal of Pathology Informatics. 13. 100001–100001. 2 indexed citations
2.
D’Alessandro, Lorenza A., Ursula Klingmüller, & Marcel Schilling. (2022). Deciphering signal transduction networks in the liver by mechanistic mathematical modelling. Biochemical Journal. 479(12). 1361–1374. 2 indexed citations
3.
D’Alessandro, Lorenza A., Sofia Depner, Philippe Lucarelli, et al.. (2016). Context-specific flow through the MEK/ERK module produces cell- and ligand-specific patterns of ERK single and double phosphorylation. Science Signaling. 9(413). ra13–ra13. 18 indexed citations
4.
D’Alessandro, Lorenza A., Regina Samaga, Tim Maiwald, et al.. (2015). Disentangling the Complexity of HGF Signaling by Combining Qualitative and Quantitative Modeling. PLoS Computational Biology. 11(4). e1004192–e1004192. 14 indexed citations
5.
Mueller, Stephanie K., Xiaoyun Huang, Lorenza A. D’Alessandro, et al.. (2015). T160‐phosphorylated CDK 2 defines threshold for HGF ‐dependent proliferation in primary hepatocytes. Molecular Systems Biology. 11(3). 795–795. 15 indexed citations
6.
Mleczko‐Sanecka, Katarzyna, Flavia D’Alessio, Anan Ragab, et al.. (2014). Unbiased RNAi screen for hepcidin regulators links hepcidin suppression to proliferative Ras/RAF and nutrient-dependent mTOR signaling. Blood. 123(10). 1574–1585. 59 indexed citations
7.
Jong, Lenneke M., Ulrike Wittig, Philippe Lucarelli, et al.. (2013). Excemplify: A Flexible Template Based Solution, Parsing and Managing Data in Spreadsheets for Experimentalists. Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics. 10(2). 58–70. 5 indexed citations
8.
D’Alessandro, Lorenza A., René Meyer, & Ursula Klingmüller. (2013). Hepatocellular carcinoma: a systems biology perspective. Frontiers in Physiology. 4. 28–28. 12 indexed citations
9.
Pinna, Federico, Sven Sahle, Michaela Bissinger, et al.. (2013). Abstract 5235: A model for TNFα-mediated NFκB signalling: A systems biology study on hepatocytes and liver cancer cells.. Cancer Research. 73(8_Supplement). 5235–5235. 2 indexed citations
10.
Shi, Lei, Lenneke M. Jong, Ulrike Wittig, et al.. (2013). Excemplify: A Flexible Template Based Solution, Parsing and Managing Data in Spreadsheets for Experimentalists. PubMed. 10(2). 220–220. 4 indexed citations
11.
Meyer, René, Lorenza A. D’Alessandro, Sandip Kar, et al.. (2012). Heterogeneous kinetics of AKT signaling in individual cells are accounted for by variable protein concentration. Frontiers in Physiology. 3. 451–451. 33 indexed citations
12.
D’Alessandro, Lorenza A., Sofia Depner, Martin E. Boehm, et al.. (2012). Cellular ERK Phospho-Form Profiles with Conserved Preference for a Switch-Like Pattern. Journal of Proteome Research. 12(2). 637–646. 14 indexed citations
13.
Castoldi, M., Maja Vujić Spasić, Sandro Altamura, et al.. (2011). The liver-specific microRNA miR-122 controls systemic iron homeostasis in mice. Journal of Clinical Investigation. 121(4). 1386–1396. 209 indexed citations
14.
D’Alessandro, Lorenza A., et al.. (2006). Hepatocyte growth factor installs a survival platform for colorectal cancer cell invasive growth and overcomes p38 MAPK-mediated apoptosis. Cellular Signalling. 18(11). 1967–1976. 22 indexed citations
15.
Gentile, Alessandra, Lorenza A. D’Alessandro, & Enzo Médico. (2003). Gene Trapping: a Multi-Purpose Tool for Functional Genomics. Biotechnology and Genetic Engineering Reviews. 20(1). 77–100. 1 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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