David Cebrián

1.0k total citations
16 papers, 599 citations indexed

About

David Cebrián is a scholar working on Molecular Biology, Organic Chemistry and Pathology and Forensic Medicine. According to data from OpenAlex, David Cebrián has authored 16 papers receiving a total of 599 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 6 papers in Organic Chemistry and 4 papers in Pathology and Forensic Medicine. Recurrent topics in David Cebrián's work include PI3K/AKT/mTOR signaling in cancer (5 papers), Cancer Mechanisms and Therapy (4 papers) and Quinazolinone synthesis and applications (4 papers). David Cebrián is often cited by papers focused on PI3K/AKT/mTOR signaling in cancer (5 papers), Cancer Mechanisms and Therapy (4 papers) and Quinazolinone synthesis and applications (4 papers). David Cebrián collaborates with scholars based in Spain, Belgium and Sweden. David Cebrián's co-authors include Peter Bartenstein, Irene Miranda‐Lorenzo, Raúl Torres, Christopher Heeschen, Anamaria Balic, Juan Carlos Ramírez, Alexandra Aicher, Patrick Hermann, Sladjana Zagorac and Sonia Alcalá and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Cell Metabolism and Trends in Plant Science.

In The Last Decade

David Cebrián

15 papers receiving 588 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David Cebrián Spain 10 371 280 77 77 59 16 599
Muriel Quaranta France 18 643 1.7× 281 1.0× 97 1.3× 50 0.6× 23 0.4× 23 894
Shuyun Rao United States 13 526 1.4× 157 0.6× 44 0.6× 124 1.6× 40 0.7× 24 722
Peter Sicinski United States 9 457 1.2× 262 0.9× 22 0.3× 112 1.5× 46 0.8× 9 680
Ze-Yan Zhang China 13 444 1.2× 158 0.6× 43 0.6× 86 1.1× 67 1.1× 33 618
Feng Xing China 12 492 1.3× 199 0.7× 34 0.4× 124 1.6× 83 1.4× 20 644
Merav Yoeli-Lerner United States 7 637 1.7× 182 0.7× 42 0.5× 125 1.6× 80 1.4× 7 814
Lucas B. Murray United States 7 770 2.1× 232 0.8× 45 0.6× 83 1.1× 34 0.6× 7 946
Shaojie Jiang China 11 562 1.5× 239 0.9× 26 0.3× 196 2.5× 60 1.0× 16 840
Minhong Tang Ireland 9 339 0.9× 256 0.9× 33 0.4× 74 1.0× 25 0.4× 14 563
Christin L. Hanigan United States 11 597 1.6× 104 0.4× 52 0.7× 139 1.8× 21 0.4× 11 726

Countries citing papers authored by David Cebrián

Since Specialization
Citations

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

Fields of papers citing papers by David Cebrián

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Cebrián

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

All Works

16 of 16 papers shown
1.
Esposito, Simone & David Cebrián. (2025). Translational PBPK/PD modeling in drug discovery: A CRO perspective. Drug Discovery Today. 30(8). 104427–104427.
2.
MacLeod, Annette, Frederick R. C. Simeons, Jennifer Riley, et al.. (2024). Acceleration of infectious disease drug discovery and development using a humanized model of drug metabolism. Proceedings of the National Academy of Sciences. 121(7). e2315069121–e2315069121. 9 indexed citations
3.
Cambronero, M. Emilia, M. Martínez, José Luis de la Vara, David Cebrián, & Valentín Valero. (2022). GDPRValidator: a tool to enable companies using cloud services to be GDPR compliant. PeerJ Computer Science. 8. e1171–e1171. 6 indexed citations
4.
Martı́nez, Sonia, Rosa M. Álvarez, J. I. Martı́n, et al.. (2021). Macrocyclization as a Source of Desired Polypharmacology. Discovery of Triple PI3K/mTOR/PIM Inhibitors. ACS Medicinal Chemistry Letters. 12(11). 1794–1801. 10 indexed citations
5.
Álvarez, Rosa M., Ana Belén Garcı́a, J. I. Martı́n, et al.. (2020). Omipalisib inspired macrocycles as dual PI3K/mTOR inhibitors. European Journal of Medicinal Chemistry. 211. 113109–113109. 18 indexed citations
6.
Martı́nez, Sonia, Ana Isabel Hernández, Ana Belén Garcı́a, et al.. (2019). Discovery of novel triazolo[4,3-b]pyridazin-3-yl-quinoline derivatives as PIM inhibitors. European Journal of Medicinal Chemistry. 168. 87–109. 26 indexed citations
7.
Rodrı́guez, Marta, et al.. (2018). Comparing the influence of two immunosuppressants (fingolimod, azathioprine) on wound healing in a rat model of primary and secondary intention wound closure. Wound Repair and Regeneration. 27(1). 59–68. 9 indexed citations
8.
Martı́nez, Sonia, Ana Isabel Hernández, Rosa M. Álvarez, et al.. (2017). Identification of novel PI3K inhibitors through a scaffold hopping strategy. Bioorganic & Medicinal Chemistry Letters. 27(21). 4794–4799. 6 indexed citations
9.
Martı́nez, Sonia, Ana Isabel Hernández, Rosa M. Álvarez, et al.. (2017). Generation of tricyclic imidazo[1,2-a]pyrazines as novel PI3K inhibitors by application of a conformational restriction strategy. Bioorganic & Medicinal Chemistry Letters. 27(11). 2536–2543. 7 indexed citations
10.
Ortega-Molina, Ana, Elena Lopez-Guadamillas, Julie A. Mattison, et al.. (2015). Pharmacological Inhibition of PI3K Reduces Adiposity and Metabolic Syndrome in Obese Mice and Rhesus Monkeys. Cell Metabolism. 21(4). 558–570. 77 indexed citations
11.
Sabalza, Maite, Raviraj Banakar, David Cebrián, et al.. (2013). Paradoxical EU agricultural policies on genetically engineered crops. Trends in Plant Science. 18(6). 312–324. 43 indexed citations
12.
Blanco‐Aparicio, Carmen, Oliver Renner, Elena Gómez‐Casero, et al.. (2013). Abstract A275: Co-targeting PIM and PI3K/mTOR pathways with a single molecule: Novel orally available combined PIM/PI3K and PIM/PI3K/mTOR kinase inhibitors.. Molecular Cancer Therapeutics. 12(11_Supplement). A275–A275. 2 indexed citations
13.
Lonardo, Enza, Patrick Hermann, M Mueller, et al.. (2012). Nodal/Activin Signaling Drives Self-Renewal and Tumorigenicity of Pancreatic Cancer Stem Cells and Provides a Target for Combined Drug Therapy. Cell stem cell. 10(1). 104–104. 15 indexed citations
14.
Pastor, Joaquı́n, Julen Oyarzábal, Rosa M. Álvarez, et al.. (2012). Hit to lead evaluation of 1,2,3-triazolo[4,5-b]pyridines as PIM kinase inhibitors. Bioorganic & Medicinal Chemistry Letters. 22(4). 1591–1597. 35 indexed citations
15.
Granda, Teresa G., David Cebrián, Sonia Martı́nez, et al.. (2012). Biological characterization of ETP-46321 a selective and efficacious inhibitor of phosphoinositide-3-kinases. Investigational New Drugs. 31(1). 66–76. 15 indexed citations
16.
Lonardo, Enza, Patrick Hermann, M Mueller, et al.. (2011). Nodal/Activin Signaling Drives Self-Renewal and Tumorigenicity of Pancreatic Cancer Stem Cells and Provides a Target for Combined Drug Therapy. Cell stem cell. 9(5). 433–446. 321 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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