Rosa Peracaula

2.8k total citations
55 papers, 2.3k citations indexed

About

Rosa Peracaula is a scholar working on Molecular Biology, Immunology and Spectroscopy. According to data from OpenAlex, Rosa Peracaula has authored 55 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Molecular Biology, 16 papers in Immunology and 11 papers in Spectroscopy. Recurrent topics in Rosa Peracaula's work include Glycosylation and Glycoproteins Research (38 papers), Galectins and Cancer Biology (12 papers) and Advanced Proteomics Techniques and Applications (7 papers). Rosa Peracaula is often cited by papers focused on Glycosylation and Glycoproteins Research (38 papers), Galectins and Cancer Biology (12 papers) and Advanced Proteomics Techniques and Applications (7 papers). Rosa Peracaula collaborates with scholars based in Spain, Ireland and United Kingdom. Rosa Peracaula's co-authors include Rafael de Llorens, Pauline M. Rudd, Sílvia Barrabés, Ariadna Sarrats, Esther Llop, Radka Saldova, Marta Pérez-Garay, Esther Fort, Carme de Bolós and Rosa Núria Aleixandre and has published in prestigious journals such as PLoS ONE, Journal of Molecular Biology and Cancer.

In The Last Decade

Rosa Peracaula

54 papers receiving 2.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rosa Peracaula Spain 30 1.8k 770 402 354 338 55 2.3k
Rafael de Llorens Spain 32 1.7k 0.9× 475 0.6× 257 0.6× 690 1.9× 316 0.9× 61 2.4k
Katrine T. Schjoldager Denmark 24 2.0k 1.1× 671 0.9× 266 0.7× 202 0.6× 260 0.8× 35 2.4k
Catarina Gomes Portugal 20 1.4k 0.7× 610 0.8× 110 0.3× 232 0.7× 225 0.7× 55 1.7k
Naseruddin Höti United States 20 1.4k 0.7× 319 0.4× 304 0.8× 328 0.9× 99 0.3× 47 1.7k
Dale A. Cumming Canada 24 1.8k 1.0× 764 1.0× 165 0.4× 286 0.8× 357 1.1× 32 2.9k
Richard I. Christopherson Australia 28 1.7k 0.9× 300 0.4× 141 0.4× 296 0.8× 224 0.7× 131 2.4k
Carol Waghorne Canada 16 1.3k 0.7× 413 0.5× 100 0.2× 528 1.5× 187 0.6× 29 2.1k
Mark M. Fuster United States 23 1.9k 1.0× 639 0.8× 84 0.2× 467 1.3× 294 0.9× 49 3.1k
Oi Lian Kon Singapore 28 1.4k 0.8× 632 0.8× 134 0.3× 336 0.9× 90 0.3× 72 2.5k
Katherine R. Kozak United States 24 965 0.5× 342 0.4× 258 0.6× 760 2.1× 674 2.0× 39 2.0k

Countries citing papers authored by Rosa Peracaula

Since Specialization
Citations

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

Fields of papers citing papers by Rosa Peracaula

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rosa Peracaula

This figure shows the co-authorship network connecting the top 25 collaborators of Rosa Peracaula. A scholar is included among the top collaborators of Rosa Peracaula 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 Rosa Peracaula. Rosa Peracaula 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.
Guerrero, Pedro Enrique, Neus Martínez‐Bosch, Mireia Moreno, et al.. (2022). Sialyltransferase Inhibitor Ac53FaxNeu5Ac Reverts the Malignant Phenotype of Pancreatic Cancer Cells, and Reduces Tumor Volume and Favors T-Cell Infiltrates in Mice. Cancers. 14(24). 6133–6133. 9 indexed citations
2.
Guerrero, Pedro Enrique, María Ortiz, Dúnia Pérez del Campo, et al.. (2022). Characterization of Mesothelin Glycosylation in Pancreatic Cancer: Decreased Core Fucosylated Glycoforms in Pancreatic Cancer Patients’ Sera. Biomedicines. 10(8). 1942–1942. 2 indexed citations
3.
Llop, Esther, Jane Howard, Stephen F. Madden, et al.. (2021). 5-AZA-dC induces epigenetic changes associated with modified glycosylation of secreted glycoproteins and increased EMT and migration in chemo-sensitive cancer cells. Clinical Epigenetics. 13(1). 34–34. 19 indexed citations
4.
Guerrero, Pedro Enrique, Bin Sheng Wong, Anna Massaguer, et al.. (2020). Knockdown of α2,3-Sialyltransferases Impairs Pancreatic Cancer Cell Migration, Invasion and E-selectin-Dependent Adhesion. International Journal of Molecular Sciences. 21(17). 6239–6239. 36 indexed citations
5.
Llop, Esther, Jack Creagh-Flynn, Stephanie Pfister, et al.. (2020). Hypoxia Alters Epigenetic and N-Glycosylation Profiles of Ovarian and Breast Cancer Cell Lines in-vitro. Frontiers in Oncology. 10. 1218–1218. 29 indexed citations
6.
Giménez, Estela, Meritxell Balmaña, Sílvia Barrabés, et al.. (2019). Multivariate data analysis for the detection of human alpha-acid glycoprotein aberrant glycosylation in pancreatic ductal adenocarcinoma. Journal of Proteomics. 195. 76–87. 8 indexed citations
7.
Balmaña, Meritxell, Catarina Gomes, Esther Llop, et al.. (2018). Analysis of sialyl-Lewis x on MUC5AC and MUC1 mucins in pancreatic cancer tissues. International Journal of Biological Macromolecules. 112. 33–45. 18 indexed citations
8.
Barrabés, Sílvia, Esther Llop, Manel Ramírez, et al.. (2017). Analysis of urinary PSA glycosylation is not indicative of high-risk prostate cancer. Clinica Chimica Acta. 470. 97–102. 14 indexed citations
9.
10.
Balmaña, Meritxell, Ariadna Sarrats, Esther Llop, et al.. (2015). Identification of potential pancreatic cancer serum markers: Increased sialyl-Lewis X on ceruloplasmin. Clinica Chimica Acta. 442. 56–62. 47 indexed citations
11.
Peracaula, Rosa. (2015). Altered glycosylation in cancer.
12.
13.
14.
Balmaña, Meritxell, Estela Giménez, Ángel Puerta, et al.. (2015). Increased α1-3 fucosylation of α-1-acid glycoprotein (AGP) in pancreatic cancer. Journal of Proteomics. 132. 144–154. 45 indexed citations
15.
Pérez-Garay, Marta, Beatriz Arteta, Esther Llop, et al.. (2013). α2,3-Sialyltransferase ST3Gal IV promotes migration and metastasis in pancreatic adenocarcinoma cells and tends to be highly expressed in pancreatic adenocarcinoma tissues. The International Journal of Biochemistry & Cell Biology. 45(8). 1748–1757. 74 indexed citations
16.
Padró, Mercè, Raquel Mejías‐Luque, Marta Garrido, et al.. (2011). Regulation of glycosyltransferases and Lewis antigens expression by IL-1β and IL-6 in human gastric cancer cells. Glycoconjugate Journal. 28(2). 99–110. 35 indexed citations
17.
Peracaula, Rosa, Ariadna Sarrats, & Pauline M. Rudd. (2010). Liver proteins as sensor of human malignancies and inflammation. PROTEOMICS - CLINICAL APPLICATIONS. 4(4). 426–431. 39 indexed citations
18.
Sarrats, Ariadna, Josep Comet, Glòria Tabarés, et al.. (2009). Differential percentage of serum prostate‐specific antigen subforms suggests a new way to improve prostate cancer diagnosis. The Prostate. 70(1). 1–9. 34 indexed citations
19.
Peracaula, Rosa. (2007). Altered glycosylation in tumour proteins: biological implications. Afinidad. 64(529). 346–355. 3 indexed citations
20.
Gómez-Jiménez, J, et al.. (1995). Interleukin-10 and the Monocyte/Macrophage-Induced Inflammatory Response in Septic Shock. The Journal of Infectious Diseases. 171(2). 472–475. 75 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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