Diana Iliev

5.3k total citations · 1 hit paper
8 papers, 1.2k citations indexed

About

Diana Iliev is a scholar working on Molecular Biology, Genetics and Oncology. According to data from OpenAlex, Diana Iliev has authored 8 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 4 papers in Genetics and 2 papers in Oncology. Recurrent topics in Diana Iliev's work include DNA Repair Mechanisms (2 papers), BRCA gene mutations in cancer (2 papers) and PARP inhibition in cancer therapy (2 papers). Diana Iliev is often cited by papers focused on DNA Repair Mechanisms (2 papers), BRCA gene mutations in cancer (2 papers) and PARP inhibition in cancer therapy (2 papers). Diana Iliev collaborates with scholars based in United States, Germany and Ireland. Diana Iliev's co-authors include Victor Abkevich, Alexander Gutin, Kirsten M. Timms, Jennifer Potter, Srikanth Jammulapati, Bryan T. Hennessy, Thomas C. Krivak, K.H. Lu, Liesel M. FitzGerald and Thuan Van Tran and has published in prestigious journals such as SHILAP Revista de lepidopterología, Human Molecular Genetics and British Journal of Cancer.

In The Last Decade

Diana Iliev

8 papers receiving 1.2k citations

Hit Papers

Patterns of genomic loss of heterozygosity predict homolo... 2012 2026 2016 2021 2012 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Diana Iliev United States 5 901 660 279 274 189 8 1.2k
Virginie Caux‐Moncoutier France 11 653 0.7× 495 0.8× 234 0.8× 346 1.3× 81 0.4× 12 1.0k
Andrew Berchuck United States 10 560 0.6× 375 0.6× 203 0.7× 149 0.5× 249 1.3× 11 1.1k
Barbara Wappenschmidt Germany 27 1.1k 1.2× 364 0.6× 536 1.9× 732 2.7× 233 1.2× 62 1.7k
Vítor Trovisco Portugal 13 694 0.8× 723 1.1× 107 0.4× 289 1.1× 307 1.6× 16 1.8k
M. L. Carcangiu United States 11 585 0.6× 340 0.5× 159 0.6× 310 1.1× 172 0.9× 13 1.4k
Sean Young Canada 13 261 0.3× 285 0.4× 143 0.5× 201 0.7× 155 0.8× 27 736
Tsutomu Imai Japan 8 595 0.7× 330 0.5× 316 1.1× 91 0.3× 56 0.3× 15 900
Gnana P. Krishnamoorthy United States 12 457 0.5× 449 0.7× 137 0.5× 283 1.0× 204 1.1× 16 1.3k
Nayanta Sodha United Kingdom 13 692 0.8× 521 0.8× 257 0.9× 341 1.2× 175 0.9× 21 1.1k
Slamon Dj United States 9 449 0.5× 589 0.9× 210 0.8× 292 1.1× 53 0.3× 10 948

Countries citing papers authored by Diana Iliev

Since Specialization
Citations

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

Fields of papers citing papers by Diana Iliev

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Diana Iliev

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

All Works

8 of 8 papers shown
1.
Iliev, Diana, Chelsea R. Kasten, Howard Korman, et al.. (2024). Active surveillance selection and 3-year durability in intermediate-risk prostate cancer following genomic testing. Prostate Cancer and Prostatic Diseases. 28(2). 427–434. 2 indexed citations
2.
Shore, Neal D., Elizabeth S. Cogan, Diana Iliev, et al.. (2022). Hereditary cancer risk assessment and genetic testing in the community urology practice setting. The Prostate. 82(7). 850–857. 2 indexed citations
3.
Timms, Kirsten M., Victor Abkevich, Elisha Hughes, et al.. (2014). Association of BRCA1/2defects with genomic scores predictive of DNA damage repair deficiency among breast cancer subtypes. Breast Cancer Research. 16(6). 475–475. 273 indexed citations
4.
Abkevich, Victor, Kirsten M. Timms, Bryan T. Hennessy, et al.. (2012). Patterns of genomic loss of heterozygosity predict homologous recombination repair defects in epithelial ovarian cancer. British Journal of Cancer. 107(10). 1776–1782. 494 indexed citations breakdown →
5.
Abkevich, Victor, Diana Iliev, Kirsten M. Timms, et al.. (2010). Computational Method for Estimating DNA Copy Numbers in Normal Samples, Cancer Cell Lines, and Solid Tumors Using Array Comparative Genomic Hybridization. SHILAP Revista de lepidopterología. 2010. 1–12. 3 indexed citations
6.
Stone, Steven, Victor Abkevich, Deanna L. Russell, et al.. (2006). TBC1D1 is a candidate for a severe obesity gene and evidence for a gene/gene interaction in obesity predisposition. Human Molecular Genetics. 15(18). 2709–2720. 119 indexed citations
7.
Wong, Andrew, Fergus Shanahan, Joseph C. Y. Chen, et al.. (2000). BRG1, a component of the SWI-SNF complex, is mutated in multiple human tumor cell lines.. PubMed. 60(21). 6171–7. 286 indexed citations
8.
Fults, Dan, et al.. (1998). Microsatellite deletion mapping on chromosome 10q and mutation analysis of MMAC1, FAS, and MXI1 in human glioblastoma multiforme.. International Journal of Oncology. 12(4). 905–10. 51 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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