Melissa C. Southey

67.0k total citations · 2 hit papers
318 papers, 10.0k citations indexed

About

Melissa C. Southey is a scholar working on Genetics, Molecular Biology and Oncology. According to data from OpenAlex, Melissa C. Southey has authored 318 papers receiving a total of 10.0k indexed citations (citations by other indexed papers that have themselves been cited), including 145 papers in Genetics, 134 papers in Molecular Biology and 81 papers in Oncology. Recurrent topics in Melissa C. Southey's work include BRCA gene mutations in cancer (109 papers), Epigenetics and DNA Methylation (72 papers) and Cancer Genomics and Diagnostics (61 papers). Melissa C. Southey is often cited by papers focused on BRCA gene mutations in cancer (109 papers), Epigenetics and DNA Methylation (72 papers) and Cancer Genomics and Diagnostics (61 papers). Melissa C. Southey collaborates with scholars based in Australia, United States and United Kingdom. Melissa C. Southey's co-authors include John L. Hopper, Graham G. Giles, Deon J. Venter, Gillian S. Dite, Dallas R. English, Mark A. Jenkins, Margaret McCredie, Roger L. Milne, Ee Ming Wong and Gianluca Severi and has published in prestigious journals such as New England Journal of Medicine, Nature Communications and Nature Genetics.

In The Last Decade

Melissa C. Southey

305 papers receiving 9.8k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Gene-Panel Sequencing and the Prediction of Breast-Cancer Risk

2015 579 citations Marc Tischkowitz, Sean V. Tavtigian et al. New England Journal of Medicine profile →
Iron-Overload–Related Disease inHFEHereditary Hemochromatosis

2008 494 citations Katrina J. Allen, Lyle C. Gurrin et al. New England Journal of Medicine profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Melissa C. Southey Australia	53	4.2k	3.9k	2.8k	2.5k	2.0k	318	10.0k
Margaret A. Tucker United States	65	3.4k 0.8×	4.7k 1.2×	7.3k 2.6×	2.9k 1.1×	1.9k 0.9×	230	16.0k
Sharon E. Plon United States	50	3.4k 0.8×	3.8k 1.0×	1.3k 0.5×	1.6k 0.6×	1.1k 0.5×	187	8.4k
David Malkin Canada	54	2.2k 0.5×	5.6k 1.4×	4.6k 1.6×	3.1k 1.2×	1.3k 0.6×	226	11.5k
Jeffrey N. Weitzel United States	49	5.1k 1.2×	4.1k 1.0×	4.7k 1.7×	3.0k 1.2×	1.6k 0.8×	222	10.3k
Julie M. Cunningham United States	54	2.3k 0.6×	4.4k 1.1×	3.6k 1.3×	2.9k 1.1×	3.4k 1.7×	215	10.9k
Jaya M. Satagopan United States	44	3.1k 0.7×	3.0k 0.7×	1.7k 0.6×	1.6k 0.6×	1.0k 0.5×	96	7.9k
Bruce A.J. Ponder United Kingdom	65	5.1k 1.2×	8.2k 2.1×	3.5k 1.2×	2.3k 0.9×	1.7k 0.8×	180	15.7k
Jan Lubiński Poland	56	5.8k 1.4×	4.8k 1.2×	4.9k 1.7×	3.6k 1.4×	2.6k 1.3×	452	13.0k
Banu Arun United States	52	3.5k 0.8×	3.3k 0.9×	6.1k 2.1×	3.9k 1.6×	1.4k 0.7×	260	11.5k
Nathan A. Ellis United States	57	3.1k 0.7×	6.5k 1.6×	2.4k 0.9×	2.1k 0.8×	1.8k 0.9×	131	10.3k

Countries citing papers authored by Melissa C. Southey

Since Specialization

Citations

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

Fields of papers citing papers by Melissa C. Southey

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Melissa C. Southey. 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 Melissa C. Southey. The network helps show where Melissa C. Southey may publish in the future.

Co-authorship network of co-authors of Melissa C. Southey

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Mukhtar, Toqir K, Leila Dorling, Xin Yang, et al.. (2025). Associations between ATM c.7271T>G and cancer risk: analysis of Breast Cancer Association Consortium and UK Biobank data. Journal of Medical Genetics. 62(9). 547–550.

Jiao, Yue, Laetitia Fuhrmann, Marie‐Gabrielle Dondon, et al.. (2025). Breast tumors from ATM pathogenic variant carriers display a specific genome-wide DNA methylation profile. Breast Cancer Research. 27(1). 36–36.

Joo, Jihoon E., C. Elizabeth Caldon, Pierre‐Antoine Dugué, et al.. (2024). SAM-DNMT3A, a strategy for induction of genome-wide DNA methylation, identifies DNA methylation as a vulnerability in ER-positive breast cancers. Nature Communications. 15(1). 10449–10449.

Li, Shuai, Gillian S. Dite, Robert J. MacInnis, et al.. (2024). Causation and familial confounding as explanations for the associations of polygenic risk scores with breast cancer: Evidence from innovative ICE FALCON and ICE CRISTAL analyses. Genetic Epidemiology. 48(8). 401–413. 3 indexed citations

Steinberg, Julia, Mark M. Iles, Xiaochuan Wang, et al.. (2021). Independent evaluation of melanoma polygenic risk scores in UK and Australian prospective cohorts*. British Journal of Dermatology. 186(5). 823–834. 12 indexed citations

Dugué, Pierre‐Antoine, Julie K. Bassett, Ee Ming Wong, et al.. (2020). Biological Aging Measures Based on Blood DNA Methylation and Risk of Cancer: A Prospective Study. JNCI Cancer Spectrum. 5(1). 47 indexed citations

Li, Shuai, Tuong L. Nguyen, Ee Ming Wong, et al.. (2020). Genetic and environmental causes of variation in epigenetic aging across the lifespan. Clinical Epigenetics. 12(1). 158–158. 34 indexed citations

Dugué, Pierre‐Antoine, Julie K. Bassett, Roger L. Milne, et al.. (2020). DNA Methylation in Peripheral Blood and Risk of Gastric Cancer: A Prospective Nested Case–control Study. Cancer Prevention Research. 14(2). 233–240. 2 indexed citations

Fettke, Heidi, Edmond M. Kwan, Patricia Bukczynska, et al.. (2020). Prognostic Impact of Total Plasma Cell-free DNA Concentration in Androgen Receptor Pathway Inhibitor–treated Metastatic Castration-resistant Prostate Cancer. European Urology Focus. 7(6). 1287–1291. 13 indexed citations

10.

Wong, Ee Ming, Ji-Hoon Eric Joo, Pierre‐Antoine Dugué, et al.. (2018). Genome-wide DNA methylation assessment of ‘BRCA1-like’ early-onset breast cancer: Data from the Australian Breast Cancer Family Registry. Experimental and Molecular Pathology. 105(3). 404–410. 16 indexed citations

11.

Wang, Fan, Robert W. Rapkins, Robyn L. Ward, et al.. (2016). SNP rs16906252C>T Is an Expression and Methylation Quantitative Trait Locus Associated with an Increased Risk of Developing MGMT -Methylated Colorectal Cancer. Clinical Cancer Research. 22(24). 6266–6277. 20 indexed citations

12.

MacInnis, Robert J., Daniel F. Schmidt, Enes Makalic, et al.. (2016). Use of a Novel Nonparametric Version of DEPTH to Identify Genomic Regions Associated with Prostate Cancer Risk. Cancer Epidemiology Biomarkers & Prevention. 25(12). 1619–1624. 3 indexed citations

13.

Lowe, Adrian J., Caroline Lodge, Katrina J. Allen, et al.. (2016). Cohort Profile: Melbourne Atopy Cohort study (MACS). International Journal of Epidemiology. 46(1). dyw011–dyw011. 27 indexed citations

14.

Li, Shuai, Ee Ming Wong, Ji-Hoon Eric Joo, et al.. (2015). Genetic and Environmental Causes of Variation in the Difference Between Biological Age Based on DNA Methylation and Chronological Age for Middle-Aged Women. Twin Research and Human Genetics. 18(6). 720–726. 35 indexed citations

15.

Chew, Grace, D. Huang, Tony Blick, et al.. (2014). Effects of Tamoxifen and oestrogen on histology and radiographic density in high and low mammographic density human breast tissues maintained in murine tissue engineering chambers. Breast Cancer Research and Treatment. 148(2). 303–314. 15 indexed citations

16.

Dite, Gillian S., Enes Makalic, Daniel F. Schmidt, et al.. (2012). Tumour morphology of early-onset breast cancers predicts breast cancer risk for first-degree relatives: the Australian Breast Cancer Family Registry. Breast Cancer Research. 14(4). R122–R122. 6 indexed citations

17.

Pereira, Emílio Marcelo, Lucien Frappart, Mathieu Boniol, et al.. (2010). Molecular characterization of breast cancer in young Brazilian women. Revista da Associação Médica Brasileira. 56(3). 278–87. 14 indexed citations

18.

Wong, Ee Ming, Melissa C. Southey, Stephen B. Fox, et al.. (2010). Constitutional Methylation of the BRCA1 Promoter Is Specifically Associated with BRCA1 Mutation-Associated Pathology in Early-Onset Breast Cancer. Cancer Prevention Research. 4(1). 23–33. 120 indexed citations

19.

Allen, Katrina J., Lyle C. Gurrin, Clare C. Constantine, et al.. (2008). Iron-Overload–Related Disease inHFEHereditary Hemochromatosis. New England Journal of Medicine. 358(3). 221–230. 494 indexed citations breakdown →

20.

Smith, Letitia, Andrea Tesoriero, Susan J. Ramus, et al.. (2007). BRCA1 promoter deletions in young women with breast cancer and a strong family history: A population-based study. European Journal of Cancer. 43(5). 823–827. 14 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.

Explore authors with similar magnitude of impact