Rareş Buiga

1.3k total citations
58 papers, 889 citations indexed

About

Rareş Buiga is a scholar working on Oncology, Cancer Research and Molecular Biology. According to data from OpenAlex, Rareş Buiga has authored 58 papers receiving a total of 889 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Oncology, 16 papers in Cancer Research and 15 papers in Molecular Biology. Recurrent topics in Rareş Buiga's work include Cancer Cells and Metastasis (8 papers), Genetic factors in colorectal cancer (7 papers) and MicroRNA in disease regulation (6 papers). Rareş Buiga is often cited by papers focused on Cancer Cells and Metastasis (8 papers), Genetic factors in colorectal cancer (7 papers) and MicroRNA in disease regulation (6 papers). Rareş Buiga collaborates with scholars based in Romania, United States and India. Rareş Buiga's co-authors include Ioana Berindan‐Neagoe, Alexandru Irimie, Ancuța Jurj, Cornelia Braicu, Laura Pop, Lorand Magdo, Liviuţa Budişan, Oana Tudoran, Călin Ionescu and Diana Gulei and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and International Journal of Molecular Sciences.

In The Last Decade

Rareş Buiga

56 papers receiving 873 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rareş Buiga Romania 14 524 428 203 93 77 58 889
Jiaming Huang China 17 518 1.0× 433 1.0× 216 1.1× 130 1.4× 89 1.2× 51 932
Huilian Hou China 16 845 1.6× 650 1.5× 147 0.7× 73 0.8× 76 1.0× 32 1.1k
Jianjun Han China 16 405 0.8× 275 0.6× 281 1.4× 128 1.4× 175 2.3× 61 936
Hanzi Xu China 20 948 1.8× 804 1.9× 91 0.4× 74 0.8× 53 0.7× 42 1.2k
Qianlan Yao China 20 546 1.0× 306 0.7× 119 0.6× 118 1.3× 35 0.5× 60 809
Gianmaria Miolo Italy 17 423 0.8× 196 0.5× 399 2.0× 166 1.8× 111 1.4× 86 996
Angela Kueck United States 11 425 0.8× 229 0.5× 415 2.0× 35 0.4× 41 0.5× 14 895
Xiaojun Yang China 13 539 1.0× 406 0.9× 403 2.0× 77 0.8× 71 0.9× 28 944
Yiqun Zhang United States 17 288 0.5× 143 0.3× 346 1.7× 138 1.5× 66 0.9× 36 805

Countries citing papers authored by Rareş Buiga

Since Specialization
Citations

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

Fields of papers citing papers by Rareş Buiga

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rareş Buiga

This figure shows the co-authorship network connecting the top 25 collaborators of Rareş Buiga. A scholar is included among the top collaborators of Rareş Buiga 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 Rareş Buiga. Rareş Buiga 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.
Fodor, Liviu A., Andrei Roman, Adrian P. Trifa, et al.. (2025). Predicting Pathogenic Variants of Breast Cancer Using Ultrasound-Derived Machine Learning Models. Cancers. 17(6). 1019–1019. 2 indexed citations
2.
3.
Zănoagă, Oana, Lajos Ráduly, Rareş Buiga, et al.. (2022). Dysregulation of miR-21-5p, miR-93-5p, miR-200c-3p and miR-205-5p in Oral Squamous Cell Carcinoma: A Potential Biomarkers Panel?. Current Issues in Molecular Biology. 44(4). 1754–1767. 11 indexed citations
4.
Cainap, Călin, Zsolt Fekete, Andrei Roman, et al.. (2022). Signet ring cell gastric carcinoma with breast and leptomeningeal metastases: a case report. Medicine and Pharmacy Reports. 95(1). 88–91. 3 indexed citations
5.
Gâta, Vlad Alexandru, et al.. (2021). The value of tumor infiltrating lymphocytes as prognostic factor for lymph node status and survival amongst patients with cutaneous malignant melanoma.. PubMed. 25(6). 2700–2707. 6 indexed citations
6.
Sur, Daniel, Loredana Bălăcescu, Simona Căinap, et al.. (2021). Predictive Efficacy of MiR-125b-5p, MiR-17-5p, and MiR-185-5p in Liver Metastasis and Chemotherapy Response Among Advanced Stage Colorectal Cancer Patients. Frontiers in Oncology. 11. 651380–651380. 18 indexed citations
7.
Burz, Claudia, Rareş Buiga, Cornel Aldea, et al.. (2019). Liquid biopsy challenge and hope in colorectal cancer. Expert Review of Molecular Diagnostics. 19(4). 341–348. 9 indexed citations
8.
Eniu, Dan, et al.. (2019). The decrease of some serum free amino acids can predict breast cancer diagnosis and progression. Scandinavian Journal of Clinical and Laboratory Investigation. 79(1-2). 17–24. 32 indexed citations
9.
Boca, Sanda, Diana Gulei, Alina‐Andreea Zimța, et al.. (2019). Nanoscale delivery systems for microRNAs in cancer therapy. Cellular and Molecular Life Sciences. 77(6). 1059–1086. 79 indexed citations
10.
Braicu, Cornelia, Rareş Buiga, Roxana Cojocneanu, et al.. (2019). Connecting the dots between different networks: miRNAs associated with bladder cancer risk and progression. Journal of Experimental & Clinical Cancer Research. 38(1). 433–433. 41 indexed citations
11.
Seicean, Andrada, et al.. (2019). Interleukin-6 correlated with neutrophil-to-lymphocyte ratio in pancreatic cancer. Annals of Oncology. 30. iv15–iv16. 4 indexed citations
12.
13.
Şoriţău, Olga, et al.. (2018). Automatic detection of circulating tumor cells in darkfield microscopic images of unstained blood using boosting techniques. PLoS ONE. 13(12). e0208385–e0208385. 13 indexed citations
14.
Gulei, Diana, Lorand Magdo, Ancuța Jurj, et al.. (2018). The silent healer: miR-205-5p up-regulation inhibits epithelial to mesenchymal transition in colon cancer cells by indirectly up-regulating E-cadherin expression. Cell Death and Disease. 9(2). 66–66. 70 indexed citations
15.
Buiga, Rareş, et al.. (2016). Solid pseudopapillary tumor of the pancreas: clinical-pathological features and management of 13 cases. Medicine and Pharmacy Reports. 90(2). 171–178. 10 indexed citations
16.
Pop, Laura, Valentina Pileczki, Roxana Cojocneanu, et al.. (2016). Normalization of gene expression measurement of tissue samples obtained by transurethral resection of bladder tumors. OncoTargets and Therapy. 9. 3369–3369. 3 indexed citations
17.
Cebotaru, C., et al.. (2015). Circulating tumor cells in germ cell tumors: are those biomarkers of real prognostic value? A review. Medicine and Pharmacy Reports. 89(2). 203–211. 5 indexed citations
18.
Chiorean, Liliana, Adrian Bartoş, Daniela Iancu, et al.. (2014). Neuroendocrine tumor of gallbladder with liver and retroperitoneal metastases and a good response to the chemotherapeutical treatment. Journal of Medical Ultrasonics. 42(2). 271–276. 9 indexed citations
19.
Piciu, Doina, Alexandru Irimie, George Kontogeorgos, Andra Piciu, & Rareş Buiga. (2013). Highly aggressive pathology of non-functional parathyroid carcinoma. Orphanet Journal of Rare Diseases. 8(1). 115–115. 18 indexed citations
20.
Vlad, Mariana, Ovidiu Bălăcescu, Loredana Bălăcescu, et al.. (2011). Risk Factors in a Sample of Patients with Advanced Cervical Cancer. SHILAP Revista de lepidopterología. 2 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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