David G. Cox

15.3k total citations
69 papers, 2.3k citations indexed

About

David G. Cox is a scholar working on Molecular Biology, Genetics and Oncology. According to data from OpenAlex, David G. Cox has authored 69 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 27 papers in Genetics and 20 papers in Oncology. Recurrent topics in David G. Cox's work include Genetic Associations and Epidemiology (14 papers), BRCA gene mutations in cancer (11 papers) and DNA Repair Mechanisms (7 papers). David G. Cox is often cited by papers focused on Genetic Associations and Epidemiology (14 papers), BRCA gene mutations in cancer (11 papers) and DNA Repair Mechanisms (7 papers). David G. Cox collaborates with scholars based in United States, France and United Kingdom. David G. Cox's co-authors include David J. Hunter, Peter Kraft, Susan E. Hankinson, Federico Canzian, Janet Hall, P. Romestaing, Norman Moullan, Sandra Angèle, Susan E. Hankinson and Rulla M. Tamimi and has published in prestigious journals such as The Lancet, Bioinformatics and PLoS ONE.

In The Last Decade

David G. Cox

68 papers receiving 2.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David G. Cox United States 28 1.2k 634 575 517 248 69 2.3k
Atanas Ignatov Germany 29 842 0.7× 534 0.8× 763 1.3× 670 1.3× 292 1.2× 133 2.5k
Alastair M. Thompson United States 19 1.4k 1.1× 540 0.9× 285 0.5× 684 1.3× 173 0.7× 37 2.8k
Carl E. Freter United States 20 1.0k 0.8× 465 0.7× 347 0.6× 514 1.0× 224 0.9× 52 2.2k
Yoko Omoto Japan 29 1.1k 0.9× 553 0.9× 1.2k 2.1× 870 1.7× 353 1.4× 49 2.5k
Khalil Helou Sweden 27 1.2k 1.0× 514 0.8× 348 0.6× 508 1.0× 296 1.2× 114 2.2k
Paola Ferrari Italy 28 957 0.8× 496 0.8× 380 0.7× 837 1.6× 340 1.4× 103 2.6k
Michele De Bortoli Italy 32 2.0k 1.6× 808 1.3× 614 1.1× 1.0k 1.9× 218 0.9× 97 3.2k
Shunzo Kobayashi Japan 28 1.1k 0.9× 786 1.2× 716 1.2× 1.2k 2.2× 250 1.0× 74 2.3k
Francesca Pentimalli Italy 38 2.3k 1.8× 922 1.5× 444 0.8× 1.1k 2.1× 429 1.7× 120 3.8k
Abdul K. Siraj Saudi Arabia 29 1.5k 1.2× 577 0.9× 293 0.5× 812 1.6× 278 1.1× 121 2.7k

Countries citing papers authored by David G. Cox

Since Specialization
Citations

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

Fields of papers citing papers by David G. Cox

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David G. Cox. 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 David G. Cox. The network helps show where David G. Cox may publish in the future.

Co-authorship network of co-authors of David G. Cox

This figure shows the co-authorship network connecting the top 25 collaborators of David G. Cox. A scholar is included among the top collaborators of David G. Cox 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 David G. Cox. David G. Cox 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.
Pivot, Xavier, Alexey Manikhas, Hwoei Fen Soo Hoo, et al.. (2023). Final analysis of the phase 3 randomized clinical trial comparing HD201 vs. referent trastuzumab in patients with ERBB2-positive breast cancer treated in the neoadjuvant setting. BMC Cancer. 23(1). 112–112. 2 indexed citations
2.
3.
Pivot, Xavier, Hwoei Fen Soo Hoo, Fausto Petrelli, et al.. (2022). Efficacy of HD201 vs Referent Trastuzumab in Patients With ERBB2-Positive Breast Cancer Treated in the Neoadjuvant Setting. JAMA Oncology. 8(5). 698–698. 11 indexed citations
4.
Cox, David G., et al.. (2018). Transmission of breast cancer polygenic risk based on single nucleotide polymorphisms. The Breast. 41. 14–18. 5 indexed citations
5.
Blein, Sophie, Laure Barjhoux, Francesca Damiola, et al.. (2015). Targeted Sequencing of the Mitochondrial Genome of Women at High Risk of Breast Cancer without Detectable Mutations in BRCA1/2. PLoS ONE. 10(9). e0136192–e0136192. 9 indexed citations
6.
Sagné, Corinne, Virginie Marcel, Maria Bota, et al.. (2013). Age at cancer onset in germline TP53 mutation carriers: association with polymorphisms in predicted G-quadruplex structures. Carcinogenesis. 35(4). 807–815. 30 indexed citations
7.
Lee, Hae‐Jeung, Kana Wu, David G. Cox, et al.. (2013). Polymorphisms in Xenobiotic Metabolizing Genes, Intakes of Heterocyclic Amines and Red Meat, and Postmenopausal Breast Cancer. Nutrition and Cancer. 65(8). 1122–1131. 15 indexed citations
8.
Cox, David G., Laure Barjhoux, Daniel R. Barnes, et al.. (2011). The rs2910164:G>C SNP in the MIR146A gene is not associated with breast cancer risk in BRCA1 and BRCA2 mutation carriers. Human Mutation. 32(9). 1004–1007. 39 indexed citations
9.
Teo, Mark, Debora Landi, Claire Taylor, et al.. (2011). The role of microRNA-binding site polymorphisms in DNA repair genes as risk factors for bladder cancer and breast cancer and their impact on radiotherapy outcomes. Carcinogenesis. 33(3). 581–586. 91 indexed citations
10.
Voirin, Nicolas, David G. Cox, Sylvie Chabaud, et al.. (2009). Prognostic value of Dicer expression in human breast cancers and association with the mesenchymal phenotype. British Journal of Cancer. 101(4). 673–683. 165 indexed citations
11.
Tamimi, Rulla M., David G. Cox, Peter Kraft, et al.. (2008). Breast cancer susceptibility loci and mammographic density. Breast Cancer Research. 10(4). R66–R66. 24 indexed citations
12.
Kraft, Peter & David G. Cox. (2008). Study Designs for Genome‐Wide Association Studies. Advances in genetics. 60. 465–504. 40 indexed citations
13.
Forman, John P., et al.. (2008). Renin‐Angiotensin System Polymorphisms and Risk of Hypertension: Influence of Environmental Factors. Journal of Clinical Hypertension. 10(6). 459–466. 7 indexed citations
14.
Cox, David G., Kathryn L. Penney, Qun Guo, Susan E. Hankinson, & David J. Hunter. (2007). TGFB1 and TGFBR1 polymorphisms and breast cancer risk in the Nurses' Health Study. BMC Cancer. 7(1). 175–175. 50 indexed citations
15.
Han, Jiali, David G. Cox, Graham A. Colditz, & David J. Hunter. (2006). The p53 codon 72 polymorphism, sunburns, and risk of skin cancer in US caucasian women. Molecular Carcinogenesis. 45(9). 694–700. 39 indexed citations
16.
Cox, David G., Susan E. Hankinson, & David J. Hunter. (2006). Polymorphisms of the AURKA (STK15/Aurora Kinase) Gene and Breast Cancer Risk (United States). Cancer Causes & Control. 17(1). 81–83. 68 indexed citations
17.
Cox, David G. & Peter Kraft. (2006). Quantification of the Power of Hardy-Weinberg Equilibrium Testing to Detect Genotyping Error. Human Heredity. 61(1). 10–14. 65 indexed citations
18.
Cox, David G.. (2005). A haplotype of prostaglandin synthase 2/cyclooxygenase 2 is involved in the susceptibility to inflammatory bowel disease. World Journal of Gastroenterology. 11(38). 6003–6003. 26 indexed citations
19.
20.
Barron, Karyl S., Daniel J. Murphy, Earl D. Silverman, et al.. (1990). Treatment of Kawasaki syndrome: A comparison of two dosage regimens of intravenously administered immune globulin. The Journal of Pediatrics. 117(4). 638–644. 53 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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