J. Eglītis

727 total citations
21 papers, 514 citations indexed

About

J. Eglītis is a scholar working on Molecular Biology, Oncology and Genetics. According to data from OpenAlex, J. Eglītis has authored 21 papers receiving a total of 514 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 10 papers in Oncology and 5 papers in Genetics. Recurrent topics in J. Eglītis's work include BRCA gene mutations in cancer (5 papers), Extracellular vesicles in disease (4 papers) and DNA Repair Mechanisms (3 papers). J. Eglītis is often cited by papers focused on BRCA gene mutations in cancer (5 papers), Extracellular vesicles in disease (4 papers) and DNA Repair Mechanisms (3 papers). J. Eglītis collaborates with scholars based in Latvia, Ukraine and Poland. J. Eglītis's co-authors include Aija Linē, Signe Tomsone, Т. Yu. Semiglazova, Vahit Özmen, Jacek Jassem, Piotr Zaborek, Damir Vrbanec, Constanta Timcheva, K C Lakshmaiah and Zsuzsanna Kahán and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Cancer Research.

In The Last Decade

J. Eglītis

19 papers receiving 507 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
J. Eglītis Latvia 12 246 213 115 83 64 21 514
Sing‐Huang Tan Singapore 14 279 1.1× 229 1.1× 145 1.3× 114 1.4× 79 1.2× 23 582
Radhika Gogoi United States 13 176 0.7× 185 0.9× 81 0.7× 38 0.5× 52 0.8× 51 554
Lidija Beketić-Orešković Croatia 13 276 1.1× 288 1.4× 102 0.9× 53 0.6× 36 0.6× 37 591
Maria Litwiniuk Poland 10 245 1.0× 117 0.5× 98 0.9× 88 1.1× 74 1.2× 52 442
Enrique Bargalló Mexico 10 325 1.3× 287 1.3× 230 2.0× 128 1.5× 57 0.9× 17 682
Christopher Sistrunk United States 9 352 1.4× 261 1.2× 227 2.0× 82 1.0× 58 0.9× 17 649
Niya Xiong United States 12 256 1.0× 305 1.4× 125 1.1× 34 0.4× 75 1.2× 37 693
Anna Badowska-Kozakiewicz Poland 14 237 1.0× 159 0.7× 135 1.2× 32 0.4× 89 1.4× 67 499
Weiya Z. Wysham United States 12 133 0.5× 222 1.0× 137 1.2× 34 0.4× 38 0.6× 23 467
Claudia Arce-Salinas Mexico 11 241 1.0× 138 0.6× 177 1.5× 64 0.8× 80 1.3× 25 448

Countries citing papers authored by J. Eglītis

Since Specialization
Citations

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

Fields of papers citing papers by J. Eglītis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J. Eglītis

This figure shows the co-authorship network connecting the top 25 collaborators of J. Eglītis. A scholar is included among the top collaborators of J. Eglītis 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 J. Eglītis. J. Eglītis 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.
Zayakin, Pawel, Ilze Radoviča-Spalviņa, Edgars Endzeliņš, et al.. (2023). Extracellular Vesicles—A Source of RNA Biomarkers for the Detection of Breast Cancer in Liquid Biopsies. Cancers. 15(17). 4329–4329. 11 indexed citations
2.
Zayakin, Pawel, Edgars Endzeliņš, Ilze Radoviča-Spalviņa, et al.. (2022). Comprehensive characterization of RNA cargo of extracellular vesicles in breast cancer patients undergoing neoadjuvant chemotherapy. Frontiers in Oncology. 12. 1005812–1005812. 12 indexed citations
3.
4.
5.
Eglītis, J., et al.. (2021). CD63 and Dna Mismatch Repair Protein Expression in Prostate Cancer. Proceedings of the Latvian Academy of Sciences Section B Natural Exact and Applied Sciences. 75(3). 180–185.
6.
Eglītis, J., et al.. (2019). The impact of maximal strength training on quality of life among women with breast cancer undergoing treatment. Experimental Oncology. 41(2). 166–172. 32 indexed citations
7.
Gerashchenko, Bogdan I., Kristīne Salmiņa, J. Eglītis, & Jekaterina Ērenpreisa. (2019). PROBING BREAST CANCER THERAPEUTIC RESPONSES BY DNA CONTENT PROFILING. SHILAP Revista de lepidopterología. 5(1). 47–57. 2 indexed citations
8.
Tomsone, Signe, et al.. (2019). Heavy Resistance Training in Breast Cancer Patients Undergoing Adjuvant Therapy. Medicine & Science in Sports & Exercise. 52(6). 1239–1247. 28 indexed citations
9.
Salmiņa, Kristīne, et al.. (2017). Abstract P3-03-17: Can polyploid tumor cells possessing stem cell features be induced in resistant breast carcinomas?. Cancer Research. 77(4_Supplement). P3–3. 1 indexed citations
10.
Gerashchenko, Bogdan I., et al.. (2016). Disentangling the aneuploidy and senescence paradoxes: a study of triploid breast cancers non-responsive to neoadjuvant therapy. Histochemistry and Cell Biology. 145(4). 497–508. 34 indexed citations
11.
Ābols, Artūrs, et al.. (2015). Trefoil factor 3 is required for differentiation of thyroid follicular cells and acts as a context-dependent tumor suppressor. Neoplasma. 62(6). 914–924. 10 indexed citations
12.
Eglītis, J., et al.. (2015). Extracellular Vesicles as Biomarkers and Therapeutic Targets in Breast Cancer.. PubMed. 35(12). 6379–90. 46 indexed citations
13.
Siliņa, Karīna, Zane Kalniņa, Artūrs Ābols, et al.. (2014). Prognostic relevance of carbonic anhydrase IX expression is distinct in various subtypes of breast cancer and its silencing suppresses self-renewal capacity of breast cancer cells. Cancer Chemotherapy and Pharmacology. 75(2). 235–246. 48 indexed citations
14.
Tihomirova, Laima, Raitis Pečulis, Ilona Mandrika, et al.. (2014). BRCA1 gene-related hereditary susceptibility to breast and ovarian cancer in Latvia. Advances in Medical Sciences. 59(1). 114–119. 4 indexed citations
15.
Bundred, Nigel, Jānis Gardovskis, Janusz Jaśkiewicz, et al.. (2013). Evaluation of the pharmacodynamics and pharmacokinetics of the PARP inhibitor olaparib: a Phase I multicentre trial in patients scheduled for elective breast cancer surgery. Investigational New Drugs. 31(4). 949–958. 71 indexed citations
16.
Jassem, Jacek, Vahit Özmen, J. Eglītis, et al.. (2013). Delays in diagnosis and treatment of breast cancer: a multinational analysis. European Journal of Public Health. 24(5). 761–767. 105 indexed citations
17.
Leja, Mārcis, Dace Rudzīte, Teppo Huttunen, et al.. (2012). Prevalence of Helicobacter pylori infection and atrophic gastritis in Latvia. European Journal of Gastroenterology & Hepatology. 24(12). 1410–1417. 38 indexed citations
18.
Jassem, Jacek, J. Eglītis, Jozef Mardiak, et al.. (2012). Patient-related factors influencing time between first signs of breast cancer (BC) and appointment for medical visit (AMV): An international survey.. Journal of Clinical Oncology. 30(15_suppl). 9046–9046. 2 indexed citations
19.
Eglītis, J., et al.. (2011). Population-based mammography screening program in Latvia: Results of the first round.. Journal of Clinical Oncology. 29(15_suppl). e11038–e11038.
20.
Eglītis, J., et al.. (2005). High prevalence of two BRCA1 mutations, 4154delA and 5382insC, in Latvia. Familial Cancer. 4(2). 77–84. 38 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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