Shelly Gunn

1.3k total citations
28 papers, 814 citations indexed

About

Shelly Gunn is a scholar working on Genetics, Molecular Biology and Cancer Research. According to data from OpenAlex, Shelly Gunn has authored 28 papers receiving a total of 814 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Genetics, 13 papers in Molecular Biology and 7 papers in Cancer Research. Recurrent topics in Shelly Gunn's work include Genomic variations and chromosomal abnormalities (14 papers), Cancer Genomics and Diagnostics (7 papers) and Chronic Lymphocytic Leukemia Research (5 papers). Shelly Gunn is often cited by papers focused on Genomic variations and chromosomal abnormalities (14 papers), Cancer Genomics and Diagnostics (7 papers) and Chronic Lymphocytic Leukemia Research (5 papers). Shelly Gunn collaborates with scholars based in United States, Netherlands and Lebanon. Shelly Gunn's co-authors include Ryan S. Robetorye, Drew Rasco, Anthony W. Tolcher, Theresa A. Mays, Brianne Kaiser, Leslie Smetzer, M. Gorre, Amita Patnaik, Kyriakos P. Papadopoulos and G. Mangold and has published in prestigious journals such as Journal of Clinical Oncology, Blood and Cancer Research.

In The Last Decade

Shelly Gunn

27 papers receiving 775 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shelly Gunn United States 12 445 298 162 154 148 28 814
Archontoula Stoffel United States 12 548 1.2× 259 0.9× 166 1.0× 101 0.7× 56 0.4× 15 826
Rachel V. Pearline United States 5 756 1.7× 343 1.2× 168 1.0× 95 0.6× 103 0.7× 7 976
Alessandra Gentile Italy 16 618 1.4× 316 1.1× 140 0.9× 168 1.1× 38 0.3× 28 1.0k
S Romain France 17 348 0.8× 611 2.1× 316 2.0× 128 0.8× 82 0.6× 43 965
David E. MacCallum United Kingdom 11 739 1.7× 472 1.6× 96 0.6× 58 0.4× 96 0.6× 21 1.1k
Barbara Hutter Germany 16 413 0.9× 160 0.5× 172 1.1× 180 1.2× 80 0.5× 33 751
Changxian Shen United States 17 684 1.5× 296 1.0× 288 1.8× 116 0.8× 44 0.3× 38 1.2k
Hakim El Housni Belgium 15 334 0.8× 257 0.9× 195 1.2× 58 0.4× 103 0.7× 31 711
Xuhui Bao United States 14 475 1.1× 357 1.2× 240 1.5× 58 0.4× 82 0.6× 32 1.1k
Christopher Schroeder Germany 17 249 0.6× 308 1.0× 153 0.9× 43 0.3× 60 0.4× 53 740

Countries citing papers authored by Shelly Gunn

Since Specialization
Citations

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

Fields of papers citing papers by Shelly Gunn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shelly Gunn

This figure shows the co-authorship network connecting the top 25 collaborators of Shelly Gunn. A scholar is included among the top collaborators of Shelly Gunn 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 Shelly Gunn. Shelly Gunn 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
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Gunn, Shelly. (2017). Commentary—Redefining HER2-Equivocal Breast Cancers: Lessons Learned from Genomic Pathology. 13(5). 1 indexed citations
4.
Gunn, Shelly, Jae‐Weon Kim, Rashmi R. Shah, et al.. (2013). Molecular cytogenetics as a clinical test for prognostic and predictive biomarkers in newly diagnosed ovarian cancer. Journal of Ovarian Research. 6(1). 2–2. 9 indexed citations
5.
O’Malley, Dennis P., Lauren B. Smith, Todd Barry, et al.. (2013). The genetics of interdigitating dendritic cell sarcoma share some changes with Langerhans cell histiocytosis in select cases. Annals of Diagnostic Pathology. 18(1). 18–20. 7 indexed citations
6.
Shimizu, Toshio, Anthony W. Tolcher, Kyriakos P. Papadopoulos, et al.. (2012). The Clinical Effect of the Dual-Targeting Strategy Involving PI3K/AKT/mTOR and RAS/MEK/ERK Pathways in Patients with Advanced Cancer. Clinical Cancer Research. 18(8). 2316–2325. 352 indexed citations
7.
Raslan, Wasim F., et al.. (2011). Education. Modern Pathology. 24. 128–133.
8.
Shimizu, Takashi, A. W. Tolcher, Kyriakos P. Papadopoulos, et al.. (2011). The clinical effect of the dual-targeting strategy involving PI3K/AKT/mTOR and RAS/MEK/ERK pathways in first-in-human phase I study: The START Center experience.. Journal of Clinical Oncology. 29(15_suppl). 2502–2502. 4 indexed citations
9.
Dawson, Angelika J., Ingo Schroedter, Matthew D. Seftel, et al.. (2011). Inversion and deletion of 16q22 defined by array CGH, FISH, and RT-PCR in a patient with AML. Cancer Genetics. 204(6). 344–347. 10 indexed citations
10.
Pescosolido, Matthew F., Jose Bernardo Quintos, Dianne Abuelo, et al.. (2011). A novel familial 11p15.4 microduplication associated with intellectual disability, dysmorphic features, and obesity with involvement of the ZNF214 gene. American Journal of Medical Genetics Part A. 158A(1). 50–58. 11 indexed citations
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Yeh, I‐Tien, et al.. (2009). Clinical validation of an array CGH test for HER2 status in breast cancer reveals that polysomy 17 is a rare event. Modern Pathology. 22(9). 1169–1175. 105 indexed citations
13.
Higgins, Russell A., Shelly Gunn, & Ryan S. Robetorye. (2008). Clinical Application of Array-Based Comparative Genomic Hybridization for the Identification of Prognostically Important Genetic Alterations in Chronic Lymphocytic Leukemia. Molecular Diagnosis & Therapy. 12(5). 271–280. 12 indexed citations
14.
Gunn, Shelly, M.H. Afif, M. Gorre, et al.. (2008). Whole-Genome Scanning by Array Comparative Genomic Hybridization as a Clinical Tool for Risk Assessment in Chronic Lymphocytic Leukemia. Journal of Molecular Diagnostics. 10(5). 442–451. 56 indexed citations
15.
Horbinski, Craig, Patricia Heard, Malini Sathanoori, et al.. (2008). Molecular and clinical characterization of a recurrent cryptic unbalanced t(4q;18q) resulting in an 18q deletion and 4q duplication. American Journal of Medical Genetics Part A. 146A(22). 2898–2904. 18 indexed citations
16.
Gunn, Shelly, Lynn L. Barron, M. Gorre, et al.. (2008). Array CGH Analysis of Chronic Lymphocytic Leukemia Reveals Frequent Cryptic Monoallelic and Biallelic Deletions of Chromosome 22q11.. Blood. 112(11). 1050–1050. 2 indexed citations
17.
Gunn, Shelly, et al.. (2008). The HemeScan test for genomic prognostic marker assessment in chronic lymphocytic leukemia. Expert Opinion on Medical Diagnostics. 2(6). 731–740. 2 indexed citations
18.
Gunn, Shelly, Lynn L. Barron, M. Gorre, et al.. (2008). Array CGH analysis of chronic lymphocytic leukemia reveals frequent cryptic monoallelic and biallelic deletions of chromosome 22q11 that include the PRAME gene. Leukemia Research. 33(9). 1276–1281. 42 indexed citations
19.
Gunn, Shelly, Ryan S. Robetorye, & M.H. Afif. (2007). Comparative Genomic Hybridization Arrays in Clinical Pathology. Molecular Diagnosis & Therapy. 11(2). 73–77. 15 indexed citations
20.
Gunn, Shelly, David Viskochil, Janice C. Palumbos, et al.. (2003). Molecular characterization of a patient with central nervous system dysmyelination and cryptic unbalanced translocation between chromosomes 4q and 18q. American Journal of Medical Genetics Part A. 120A(1). 127–135. 46 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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