David Barneda

2.2k total citations · 2 hit papers
17 papers, 1.6k citations indexed

About

David Barneda is a scholar working on Molecular Biology, Biochemistry and Cell Biology. According to data from OpenAlex, David Barneda has authored 17 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 7 papers in Biochemistry and 6 papers in Cell Biology. Recurrent topics in David Barneda's work include Lipid metabolism and biosynthesis (7 papers), Adipose Tissue and Metabolism (5 papers) and Cellular transport and secretion (4 papers). David Barneda is often cited by papers focused on Lipid metabolism and biosynthesis (7 papers), Adipose Tissue and Metabolism (5 papers) and Cellular transport and secretion (4 papers). David Barneda collaborates with scholars based in United Kingdom, Spain and Poland. David Barneda's co-authors include Patricia Sancho, Christopher Heeschen, Mark Christian, Petra Jagušt, Matthieu Schoenhals, Emma Burgos‐Ramos, Alejandra Tavera-Tapia, Osvaldo Graña‐Castro, Tony Bou Kheir and Bruno Sáinz and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and Journal of Clinical Oncology.

In The Last Decade

David Barneda

17 papers receiving 1.5k citations

Hit Papers

MYC/PGC-1α Balance Determines the Metabolic Phenotype and... 2015 2026 2018 2022 2015 2016 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David Barneda United Kingdom 13 1.0k 648 413 284 279 17 1.6k
Gary Bellinger United States 11 1.4k 1.4× 749 1.2× 360 0.9× 118 0.4× 208 0.7× 13 1.9k
Tenzin Kunchok United States 11 929 0.9× 412 0.6× 170 0.4× 126 0.4× 212 0.8× 14 1.4k
Evan C. Lien United States 17 1.4k 1.3× 777 1.2× 393 1.0× 123 0.4× 178 0.6× 28 2.0k
Daniele Avanzato Italy 15 996 1.0× 338 0.5× 465 1.1× 178 0.6× 117 0.4× 18 1.8k
Laura M. Shelton United States 17 1.1k 1.1× 831 1.3× 210 0.5× 103 0.4× 369 1.3× 30 1.7k
Lucie Brisson France 21 1.0k 1.0× 632 1.0× 189 0.5× 84 0.3× 104 0.4× 39 1.6k
Ahmad A. Cluntun United States 12 964 0.9× 690 1.1× 165 0.4× 104 0.4× 163 0.6× 20 1.5k
Niantao Deng Australia 18 968 0.9× 676 1.0× 329 0.8× 143 0.5× 74 0.3× 29 1.5k
F. Gregory Buchanan United States 17 877 0.8× 366 0.6× 366 0.9× 165 0.6× 109 0.4× 19 1.8k
Maria Lauda Tomasi United States 27 1.2k 1.2× 387 0.6× 302 0.7× 123 0.4× 51 0.2× 53 1.6k

Countries citing papers authored by David Barneda

Since Specialization
Citations

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

Fields of papers citing papers by David Barneda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Barneda

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

All Works

17 of 17 papers shown
1.
Mascaraque, Marta, Sarah Courtois, David Barneda, et al.. (2024). Fatty acid oxidation is critical for the tumorigenic potential and chemoresistance of pancreatic cancer stem cells. Journal of Translational Medicine. 22(1). 797–797. 16 indexed citations
2.
Collins, D.M., David Barneda, Karen E. Anderson, et al.. (2024). CDS2 expression regulates de novo phosphatidic acid synthesis. Biochemical Journal. 481(20). 1449–1473. 1 indexed citations
3.
Chan, Pui Ying, Victoria Harle, Victoria Offord, et al.. (2023). Genome-wide CRISPR-Cas9 screening to identify CDS2 as an essential gene in uveal melanoma.. Journal of Clinical Oncology. 41(16_suppl). e21585–e21585. 1 indexed citations
4.
Barneda, David, Vincent Brochard, Christophe Royer, et al.. (2022). Dynamic enlargement and mobilization of lipid droplets in pluripotent cells coordinate morphogenesis during mouse peri-implantation development. Nature Communications. 13(1). 3861–3861. 20 indexed citations
5.
Barneda, David, Len Stephens, & Phillip T. Hawkins. (2022). ARFs get the BioID treatment: what have we been missing?. The EMBO Journal. 41(17). e112181–e112181. 1 indexed citations
6.
Barneda, David, Izabella Niewczas, D.M. Collins, et al.. (2022). Acyl chain selection couples the consumption and synthesis of phosphoinositides. The EMBO Journal. 41(18). e110038–e110038. 17 indexed citations
7.
Saunders, Alex M., David Barneda, Vikki Flemington, et al.. (2020). Development of isotope-enriched phosphatidylinositol-4- and 5-phosphate cellular mass spectrometry probes. Chemical Science. 12(7). 2549–2557. 4 indexed citations
8.
Barneda, David, Sabina Cosulich, Len Stephens, & Phillip T. Hawkins. (2019). How is the acyl chain composition of phosphoinositides created and does it matter?. Biochemical Society Transactions. 47(5). 1291–1305. 45 indexed citations
9.
Barneda, David & Mark Christian. (2017). Lipid droplet growth: regulation of a dynamic organelle. Current Opinion in Cell Biology. 47. 9–15. 52 indexed citations
10.
Sancho, Patricia, David Barneda, & Christopher Heeschen. (2016). Hallmarks of cancer stem cell metabolism. British Journal of Cancer. 114(12). 1305–1312. 410 indexed citations breakdown →
11.
Barneda, David, Joan Planas-Iglesias, María L. Gaspar, et al.. (2015). The brown adipocyte protein CIDEA promotes lipid droplet fusion via a phosphatidic acid-binding amphipathic helix. eLife. 4. e07485–e07485. 111 indexed citations
12.
Sancho, Patricia, Emma Burgos‐Ramos, Alejandra Tavera-Tapia, et al.. (2015). MYC/PGC-1α Balance Determines the Metabolic Phenotype and Plasticity of Pancreatic Cancer Stem Cells. Cell Metabolism. 22(4). 590–605. 555 indexed citations breakdown →
13.
Barneda, David, Andrea Frontini, Saverio Cinti, & Mark Christian. (2013). Dynamic changes in lipid droplet-associated proteins in the “browning” of white adipose tissues. Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids. 1831(5). 924–933. 94 indexed citations
14.
Lewis, Alexander M., Albert Gubern, David Barneda, et al.. (2011). NAADP mediates ATP-induced Ca2+ signals in astrocytes. FEBS Letters. 585(14). 2300–2306. 23 indexed citations
15.
Gubern, Albert, Javier Casas, David Barneda, et al.. (2009). Lipid Droplet Biogenesis Induced by Stress Involves Triacylglycerol Synthesis That Depends on Group VIA Phospholipase A2. Journal of Biological Chemistry. 284(9). 5697–5708. 80 indexed citations
16.
Gubern, Albert, David Barneda, José M. López, et al.. (2009). JNK and Ceramide Kinase Govern the Biogenesis of Lipid Droplets through Activation of Group IVA Phospholipase A2. Journal of Biological Chemistry. 284(47). 32359–32369. 47 indexed citations
17.
Gubern, Albert, Javier Casas, David Barneda, et al.. (2008). Group IVA Phospholipase A2 Is Necessary for the Biogenesis of Lipid Droplets. Journal of Biological Chemistry. 283(41). 27369–27382. 82 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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