Virginia Urquidi

3.5k total citations · 1 hit paper
56 papers, 2.8k citations indexed

About

Virginia Urquidi is a scholar working on Molecular Biology, Surgery and Oncology. According to data from OpenAlex, Virginia Urquidi has authored 56 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Molecular Biology, 20 papers in Surgery and 12 papers in Oncology. Recurrent topics in Virginia Urquidi's work include Bladder and Urothelial Cancer Treatments (17 papers), Advanced Proteomics Techniques and Applications (11 papers) and Telomeres, Telomerase, and Senescence (5 papers). Virginia Urquidi is often cited by papers focused on Bladder and Urothelial Cancer Treatments (17 papers), Advanced Proteomics Techniques and Applications (11 papers) and Telomeres, Telomerase, and Senescence (5 papers). Virginia Urquidi collaborates with scholars based in United States, United Kingdom and Slovakia. Virginia Urquidi's co-authors include Steve Goodison, Charles J. Rosser, David G. Jackson, Yunfeng Dai, Myron Chang, David M. Lubman, Jeong-Soon Kim, Makito Miyake, Derek D. Sloan and Kanji Kawai and has published in prestigious journals such as Journal of Clinical Oncology, PLoS ONE and Cancer Research.

In The Last Decade

Virginia Urquidi

56 papers receiving 2.7k citations

Hit Papers

CD44 cell adhesion molecules. 1999 2026 2008 2017 1999 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
Virginia Urquidi United States 29 1.5k 779 651 560 334 56 2.8k
Christian Schwager Germany 29 2.1k 1.4× 624 0.8× 808 1.2× 558 1.0× 251 0.8× 76 3.8k
Masanobu Komatsu United States 28 1.7k 1.1× 752 1.0× 264 0.4× 251 0.4× 457 1.4× 66 2.9k
George P. Tuszynski United States 44 3.1k 2.1× 804 1.0× 273 0.4× 1.4k 2.5× 549 1.6× 104 4.9k
Ariana Celis Denmark 23 1.6k 1.1× 314 0.4× 208 0.3× 227 0.4× 320 1.0× 36 2.4k
Eric R. Lechman Canada 25 2.2k 1.5× 673 0.9× 236 0.4× 737 1.3× 799 2.4× 55 3.8k
Oliver M.T. Pearce United Kingdom 23 1.3k 0.9× 623 0.8× 193 0.3× 218 0.4× 923 2.8× 43 2.5k
Maurizio Mongiat Italy 29 1.3k 0.9× 559 0.7× 224 0.3× 550 1.0× 337 1.0× 65 2.6k
Susumu Kagawa Japan 25 1.6k 1.1× 660 0.8× 418 0.6× 663 1.2× 570 1.7× 118 2.8k
Hidetaro Yasumitsu Japan 36 1.4k 0.9× 827 1.1× 240 0.4× 1.2k 2.1× 579 1.7× 75 3.4k
Juhani Saarinen Finland 25 1.1k 0.7× 271 0.3× 281 0.4× 209 0.4× 682 2.0× 37 2.4k

Countries citing papers authored by Virginia Urquidi

Since Specialization
Citations

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

Fields of papers citing papers by Virginia Urquidi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Virginia Urquidi

This figure shows the co-authorship network connecting the top 25 collaborators of Virginia Urquidi. A scholar is included among the top collaborators of Virginia Urquidi 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 Virginia Urquidi. Virginia Urquidi 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.
Urquidi, Virginia, Evan Gomes-Giacoia, Daniel Serie, et al.. (2016). A microRNA biomarker panel for the non-invasive detection of bladder cancer. Oncotarget. 7(52). 86290–86299. 60 indexed citations
2.
Urquidi, Virginia, Evan Gomes-Giacoia, Daniel Serie, et al.. (2016). Urinary mRNA biomarker panel for the detection of urothelial carcinoma. Oncotarget. 7(25). 38731–38740. 27 indexed citations
3.
Urquidi, Virginia, Charles J. Rosser, & Steve Goodison. (2013). Multiplex Urinary Tests for Bladder Cancer Diagnosis. 70–73. 1 indexed citations
4.
Goodison, Steve, Charles J. Rosser, & Virginia Urquidi. (2013). Bladder Cancer Detection and Monitoring: Assessment of Urine- and Blood-Based Marker Tests. Molecular Diagnosis & Therapy. 17(2). 71–84. 98 indexed citations
5.
Miyake, Makito, et al.. (2013). Expression of CXCL1 in human endothelial cells induces angiogenesis through the CXCR2 receptor and the ERK1/2 and EGF pathways. Laboratory Investigation. 93(7). 768–778. 110 indexed citations
6.
Miyake, Makito, Adrienne Lawton, Steve Goodison, Virginia Urquidi, & Charles J. Rosser. (2013). Chemokine (C-X-C motif) ligand 1 (CXCL1) protein expression is increased in high-grade prostate cancer. Pathology - Research and Practice. 210(2). 74–78. 47 indexed citations
7.
Li, Chen-Zhong, Xuena Zhu, Shanti Ross, et al.. (2013). Immuno strip based point-of-care testing for bladder cancer biomarkers detection. 1 indexed citations
8.
Urquidi, Virginia, Steve Goodison, Yunpeng Cai, Yijun Sun, & Charles J. Rosser. (2012). A Candidate Molecular Biomarker Panel for the Detection of Bladder Cancer. Cancer Epidemiology Biomarkers & Prevention. 21(12). 2149–2158. 72 indexed citations
9.
Goodison, Steve & Virginia Urquidi. (2012). The Cancer Testis Antigen PRAME As a Biomarker for Solid Tumor Cancer Management. Biomarkers in Medicine. 6(5). 629–632. 37 indexed citations
10.
Urquidi, Virginia, Charles J. Rosser, & Steven Goodison. (2012). Molecular Diagnostic Trends in Urological Cancer: Biomarkers for Non-Invasive Diagnosis. Current Medicinal Chemistry. 19(22). 3653–3663. 41 indexed citations
11.
Urquidi, Virginia, Jeong-Soon Kim, Myron Chang, et al.. (2012). CCL18 in a Multiplex Urine-Based Assay for the Detection of Bladder Cancer. PLoS ONE. 7(5). e37797–e37797. 73 indexed citations
12.
Sun, Yijun, Virginia Urquidi, & Steve Goodison. (2009). Derivation of molecular signatures for breast cancer recurrence prediction using a two-way validation approach. Breast Cancer Research and Treatment. 119(3). 593–599. 11 indexed citations
13.
Goodison, Steve & Virginia Urquidi. (2008). Breast tumor metastasis: analysis via proteomic profiling. Expert Review of Proteomics. 5(3). 457–467. 6 indexed citations
14.
Urquidi, Virginia & Steve Goodison. (2007). Genomic signatures of breast cancer metastasis. Cytogenetic and Genome Research. 118(2-4). 116–129. 9 indexed citations
15.
Agarwal, Dianne, Steve Goodison, Benjamin Nicholson, David G. Jackson, & Virginia Urquidi. (2003). Expression of matrix metalloproteinase 8 (MMP-8) and tyrosinase-related protein-1 (TYRP-1) correlates with the absence of metastasis in an isogenic human breast cancer model. Differentiation. 71(2). 114–125. 94 indexed citations
16.
Kawai, Kanji, Carrie S. Viars, Karen C. Arden, et al.. (2002). Comprehensive karyotyping of the HT‐29 colon adenocarcinoma cell line. Genes Chromosomes and Cancer. 34(1). 1–8. 41 indexed citations
17.
Aogi, Kenjiro, et al.. (1999). Comparison of telomerase and CD44 expression as diagnostic tumor markers in lesions of the thyroid.. PubMed. 5(10). 2790–7. 21 indexed citations
18.
Tian, Ya, Virginia Urquidi, & S. J. H. Ashcroft. (1996). Protein kinase C in beta-cells: expression of multiple isoforms and involvement in cholinergic stimulation of insulin secretion. Molecular and Cellular Endocrinology. 119(2). 185–193. 67 indexed citations
20.
Urquidi, Virginia & D. H. L. Bishop. (1992). Non-random reassortment between the tripartite RNA genomes of La Crosse and snowshoe hare viruses. Journal of General Virology. 73(9). 2255–2265. 45 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026