Monica D’Arcy

2.2k total citations
24 papers, 839 citations indexed

About

Monica D’Arcy is a scholar working on Oncology, Molecular Biology and Cancer Research. According to data from OpenAlex, Monica D’Arcy has authored 24 papers receiving a total of 839 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Oncology, 8 papers in Molecular Biology and 7 papers in Cancer Research. Recurrent topics in Monica D’Arcy's work include Cancer Cells and Metastasis (6 papers), Polyomavirus and related diseases (4 papers) and Breast Cancer Treatment Studies (4 papers). Monica D’Arcy is often cited by papers focused on Cancer Cells and Metastasis (6 papers), Polyomavirus and related diseases (4 papers) and Breast Cancer Treatment Studies (4 papers). Monica D’Arcy collaborates with scholars based in United States, Netherlands and Japan. Monica D’Arcy's co-authors include Melissa A. Troester, Xiaowu Gai, Patricia Casbas-Hernández, Charles M. Perou, Liza Makowski, Erick Romàn-Pèrez, Eric A. Engels, Katherine A. Hoadley, Til Stürmer‎ and Deborah Ferriola and has published in prestigious journals such as Nature Communications, Bioinformatics and JNCI Journal of the National Cancer Institute.

In The Last Decade

Monica D’Arcy

23 papers receiving 828 citations

Peers

Monica D’Arcy

ONCOL

GENET

IMMUN

I. Buyse United States

Charlotte A. Brown United States

Minyi Shi United States

Claudia Haftmann Germany

Mathieu Bourgey Canada

Hui Hu United States

Marı́a Fedetz Spain

Scott M. Krummey United States

Hongye Liu United States

Donatella Malanga Italy

I. Buyse United States

Monica D’Arcy

731 ×2.1

87 ×0.4

185 ×0.9

ONCOL

304 ×1.7

GENET

297 ×2.2

IMMUN

Citations per year, relative to Monica D’Arcy Monica D’Arcy (= 1×) peers I. Buyse

Countries citing papers authored by Monica D’Arcy

Since Specialization

Citations

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

Fields of papers citing papers by Monica D’Arcy

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Monica D’Arcy. 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 Monica D’Arcy. The network helps show where Monica D’Arcy may publish in the future.

Co-authorship network of co-authors of Monica D’Arcy

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

All Works

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20 of 20 papers shown

D’Arcy, Monica, Ruth M. Pfeiffer, Marie C. Bradley, et al.. (2025). Inflammatory diseases and risk of lung cancer among individuals who have never smoked. Nature Communications. 16(1). 5095–5095.

D’Arcy, Monica, Til Stürmer‎, Robert S. Sandler, et al.. (2022). Healthcare system engagement and algorithm‐identified cancer incidence following initiation of a new medication. Pharmacoepidemiology and Drug Safety. 32(3). 321–329. 2 indexed citations

D’Arcy, Monica, David Castenson, Charles F. Lynch, et al.. (2020). Risk of Rare Cancers Among Solid Organ Transplant Recipients. JNCI Journal of the National Cancer Institute. 113(2). 199–207. 23 indexed citations

Jayaraman, Pushkala, Timothy L. Mosbruger, Taishan Hu, et al.. (2020). AnthOligo: automating the design of oligonucleotides for capture/enrichment technologies. Bioinformatics. 36(15). 4353–4356. 7 indexed citations

D’Arcy, Monica, Ruth M. Pfeiffer, Donna R. Rivera, et al.. (2020). Voriconazole and the Risk of Keratinocyte Carcinomas Among Lung Transplant Recipients in the United States. JAMA Dermatology. 156(7). 772–772. 22 indexed citations

Troester, Melissa A., Jodie M. Fleming, Erin L. Kirk, et al.. (2020). Race-associated biological differences among Luminal A breast tumors. UNC Libraries. 1 indexed citations

D’Arcy, Monica, Anna E. Coghill, Charles F. Lynch, et al.. (2019). Survival after a cancer diagnosis among solid organ transplant recipients in the United States. Cancer. 125(6). 933–942. 57 indexed citations

D’Arcy, Monica, et al.. (2019). Allergies and the Subsequent Risk of Cancer among Elderly Adults in the United States. Cancer Epidemiology Biomarkers & Prevention. 28(4). 741–750. 14 indexed citations

D’Arcy, Monica, Til Stürmer‎, & Jennifer L. Lund. (2018). The importance and implications of comparator selection in pharmacoepidemiologic research. Current Epidemiology Reports. 5(3). 272–283. 40 indexed citations

10.

Dapprich, Johannes, Deborah Ferriola, Kate Mackiewicz, et al.. (2016). The next generation of target capture technologies - large DNA fragment enrichment and sequencing determines regional genomic variation of high complexity. BMC Genomics. 17(1). 486–486. 52 indexed citations

11.

Casbas-Hernández, Patricia, Xuezheng Sun, Erick Romàn-Pèrez, et al.. (2014). Tumor Intrinsic Subtype Is Reflected in Cancer-Adjacent Tissue. Cancer Epidemiology Biomarkers & Prevention. 24(2). 406–414. 68 indexed citations

12.

Brauer, Heather Ann, Monica D’Arcy, Tanya Libby, et al.. (2014). Dermcidin expression is associated with disease progression and survival among breast cancer patients. Breast Cancer Research and Treatment. 144(2). 299–306. 15 indexed citations

13.

Sandhu, Rupninder, et al.. (2014). Overexpression of miR-146a in basal-like breast cancer cells confers enhanced tumorigenic potential in association with altered p53 status. Carcinogenesis. 35(11). 2567–2575. 44 indexed citations

14.

Pirone, Jason R., Monica D’Arcy, Delisha A. Stewart, et al.. (2012). Age-Associated Gene Expression in Normal Breast Tissue Mirrors Qualitative Age-at-Incidence Patterns for Breast Cancer. Cancer Epidemiology Biomarkers & Prevention. 21(10). 1735–1744. 35 indexed citations

15.

Brauer, Heather Ann, Liza Makowski, Katherine A. Hoadley, et al.. (2012). Impact of Tumor Microenvironment and Epithelial Phenotypes on Metabolism in Breast Cancer. Clinical Cancer Research. 19(3). 571–585. 78 indexed citations

16.

Casbas-Hernández, Patricia, et al.. (2012). Abstract LB-501: Role of HGF in epithelial-stromal cell interactions during progression from benign breast disease to ductal carcinoma in situ. Cancer Research. 72(8_Supplement). LB–501. 1 indexed citations

17.

Gai, Xiaowu, Hongbo Xie, Juan C. Perín, et al.. (2011). Rare structural variation of synapse and neurotransmission genes in autism. Molecular Psychiatry. 17(4). 402–411. 118 indexed citations

18.

Lind, Curt, Deborah Ferriola, Kate Mackiewicz, et al.. (2010). Next-generation sequencing: the solution for high-resolution, unambiguous human leukocyte antigen typing. Human Immunology. 71(10). 1033–1042. 113 indexed citations

19.

Gai, Xiaowu, Juan C. Perín, Kevin J. Murphy, et al.. (2010). CNV Workshop: an integrated platform for high-throughput copy number variation discovery and clinical diagnostics. BMC Bioinformatics. 11(1). 74–74. 42 indexed citations

20.

Ferriola, Deborah, Curt Lind, Xiaowu Gai, et al.. (2010). 52-OR: Targeted Enrichment for Complete Characterization of 1.4Mb of the MHC With Next Generation Sequencing. Human Immunology. 71. S144–S144. 1 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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