Malcolm G. Dunlop

36.4k total citations · 7 hit papers
222 papers, 13.9k citations indexed

About

Malcolm G. Dunlop is a scholar working on Pathology and Forensic Medicine, Oncology and Genetics. According to data from OpenAlex, Malcolm G. Dunlop has authored 222 papers receiving a total of 13.9k indexed citations (citations by other indexed papers that have themselves been cited), including 113 papers in Pathology and Forensic Medicine, 86 papers in Oncology and 60 papers in Genetics. Recurrent topics in Malcolm G. Dunlop's work include Genetic factors in colorectal cancer (91 papers), Colorectal Cancer Screening and Detection (52 papers) and Genetic Associations and Epidemiology (35 papers). Malcolm G. Dunlop is often cited by papers focused on Genetic factors in colorectal cancer (91 papers), Colorectal Cancer Screening and Detection (52 papers) and Genetic Associations and Epidemiology (35 papers). Malcolm G. Dunlop collaborates with scholars based in United Kingdom, United States and China. Malcolm G. Dunlop's co-authors include Susan M. Farrington, Albert Tenesa, Harry Campbell, Evropi Τheodoratou, Maureen Dempster, Alastair M. Thompson, Robin C. Allshire, Daryll K. Green, N D Hastie and Mary Porteous and has published in prestigious journals such as Nature, New England Journal of Medicine and Proceedings of the National Academy of Sciences.

In The Last Decade

Malcolm G. Dunlop

214 papers receiving 13.5k citations

Hit Papers

Telomere reduction in hum... 1990 2026 2002 2014 1990 1994 2010 1996 2019 400 800 1.2k
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.

  1. Telomere reduction in human colorectal carcinoma and with ageing
    1990 1.4k citations Malcolm G. Dunlop et al. profile →
  2. Mutations of two P/WS homologues in hereditary nonpolyposis colon cancer
    1994 1.2k citations Malcolm G. Dunlop et al. profile →
  3. Guidelines for colorectal cancer screening and surveillance in moderate and high risk groups (update from 2002)
    2010 816 citations Malcolm G. Dunlop, D. Gareth Evans et al. profile →
  4. Analysis of mismatch repair genes in hereditary non–polyposis colorectal cancer patients
    1996 749 citations Malcolm G. Dunlop et al. profile →
  5. Guidelines for the management of hereditary colorectal cancer from the British Society of Gastroenterology (BSG)/Association of Coloproctology of Great Britain and Ireland (ACPGBI)/United Kingdom Cancer Genetics Group (UKCGG)
    2019 255 citations Malcolm G. Dunlop, Ian Tomlinson et al. profile →
  6. Global trends in incidence, death, burden and risk factors of early-onset cancer from 1990 to 2019
    2023 119 citations Jing Sun, Lijuan Wang et al. profile →
  7. Identification of novel protein biomarkers and drug targets for colorectal cancer by integrating human plasma proteome with genome
    2023 91 citations Jing Sun, Jianhui Zhao et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Malcolm G. Dunlop United Kingdom 57 6.4k 5.6k 4.3k 3.2k 2.7k 222 13.9k
Wendy L. Frankel United States 53 3.9k 0.6× 6.5k 1.2× 4.2k 1.0× 4.4k 1.4× 921 0.3× 273 13.8k
Qiuyin Cai United States 58 2.0k 0.3× 2.5k 0.4× 5.6k 1.3× 2.3k 0.7× 2.7k 1.0× 398 12.8k
Martin Lipkin United States 50 4.7k 0.7× 3.4k 0.6× 3.3k 0.8× 1.4k 0.4× 1.6k 0.6× 158 10.4k
Paul Lochhead United States 41 1.8k 0.3× 3.7k 0.7× 3.2k 0.8× 1.2k 0.4× 1.3k 0.5× 101 8.7k
Hisataka Moriwaki Japan 62 2.0k 0.3× 3.1k 0.5× 5.3k 1.2× 1.8k 0.6× 800 0.3× 511 16.6k
Harvey A. Risch United States 57 1.4k 0.2× 3.4k 0.6× 2.8k 0.6× 2.3k 0.7× 3.0k 1.1× 194 12.9k
Hye Seung Lee South Korea 66 2.1k 0.3× 5.9k 1.1× 4.0k 0.9× 1.8k 0.6× 1.1k 0.4× 452 16.1k
Robert S. Bresalier United States 58 2.1k 0.3× 4.4k 0.8× 4.2k 1.0× 1.2k 0.4× 910 0.3× 253 13.2k
R K Ross United States 54 1.5k 0.2× 3.2k 0.6× 3.1k 0.7× 2.0k 0.6× 2.9k 1.1× 77 10.9k
Nadir Arber Israel 53 1.3k 0.2× 3.0k 0.5× 2.9k 0.7× 1.2k 0.4× 1.6k 0.6× 332 10.5k

Countries citing papers authored by Malcolm G. Dunlop

Since Specialization
Citations

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

Fields of papers citing papers by Malcolm G. Dunlop

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Malcolm G. Dunlop

This figure shows the co-authorship network connecting the top 25 collaborators of Malcolm G. Dunlop. A scholar is included among the top collaborators of Malcolm G. Dunlop 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 Malcolm G. Dunlop. Malcolm G. Dunlop 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.
Xu, Wei, Ines Mesa‐Eguiagaray, David M. Morris, et al.. (2025). Deep learning and genome-wide association meta-analyses of bone marrow adiposity in the UK Biobank. Nature Communications. 16(1). 99–99. 6 indexed citations
2.
3.
Timofeeva, Maria, Cathy Wyse, Jos van Geffen, et al.. (2025). Genome-wide gene-environment interaction study uncovers 162 vitamin D status variants using a precise ambient UVB measure. Nature Communications. 16(1). 10774–10774.
4.
5.
Jiang, Fangyuan, Jianhui Zhao, Jing Sun, et al.. (2024). Impact of ambient air pollution on colorectal cancer risk and survival: insights from a prospective cohort and epigenetic Mendelian randomization study. EBioMedicine. 103. 105126–105126. 28 indexed citations
6.
Law, Philip, James B. Studd, James S. Smith, et al.. (2024). Systematic prioritization of functional variants and effector genes underlying colorectal cancer risk. Nature Genetics. 56(10). 2104–2111. 1 indexed citations
7.
Sun, Yuhao, Shuai Yuan, Xuejie Chen, et al.. (2023). The Contribution of Genetic Risk and Lifestyle Factors in the Development of Adult-Onset Inflammatory Bowel Disease: A Prospective Cohort Study. The American Journal of Gastroenterology. 118(3). 511–522. 62 indexed citations
8.
Boakye, Daniel, Nan Yang, Xuan Zhou, et al.. (2023). Field Synopsis of Environmental and Genetic Risk Factors of Sporadic Early-Onset Colorectal Cancer and Advanced Adenoma. Cancer Epidemiology Biomarkers & Prevention. 32(8). 1048–1060. 7 indexed citations
9.
Miller, J. D., Yasuko Maeda, L. Arlene Porteous, et al.. (2021). Short‐term outcomes of a COVID‐adapted triage pathway for colorectal cancer detection. Colorectal Disease. 23(7). 1639–1648. 11 indexed citations
10.
Li, Xue, Yazhou He, Philip Law, et al.. (2021). Phenome-wide association study (PheWAS) of colorectal cancer risk SNP effects on health outcomes in UK Biobank. British Journal of Cancer. 126(5). 822–830. 7 indexed citations
11.
Dunbar, Karen J., Asta Valančiūtė, Thomas Jamieson, et al.. (2020). Aspirin Rescues Wnt-Driven Stem-like Phenotype in Human Intestinal Organoids and Increases the Wnt Antagonist Dickkopf-1. Cellular and Molecular Gastroenterology and Hepatology. 11(2). 465–489. 19 indexed citations
12.
Benedetti, Elisa, Maja Pučić‐Baković, Toma Keser, et al.. (2020). Systematic Evaluation of Normalization Methods for Glycomics Data Based on Performance of Network Inference. Metabolites. 10(7). 271–271. 15 indexed citations
13.
Thormann, Anja, Mihail Halachev, William McLaren, et al.. (2019). Flexible and scalable diagnostic filtering of genomic variants using G2P with Ensembl VEP. Nature Communications. 10(1). 2373–2373. 53 indexed citations
14.
Vučković, Frano, Evropi Τheodoratou, Maria Timofeeva, et al.. (2016). IgG Glycome in Colorectal Cancer. Clinical Cancer Research. 22(12). 3078–3086. 109 indexed citations
15.
Trbojević‐Akmačić, Irena, Nicholas T. Ventham, Evropi Τheodoratou, et al.. (2015). Inflammatory Bowel Disease Associates with Proinflammatory Potential of the Immunoglobulin G Glycome. Inflammatory Bowel Diseases. 21(6). 1–1. 136 indexed citations
16.
Wang, Jiping, Luis G. Carvajal‐Carmona, J Chu, et al.. (2013). Germline Variants and Advanced Colorectal Adenomas: Adenoma Prevention with Celecoxib Trial Genome-wide Association Study. Clinical Cancer Research. 19(23). 6430–6437. 8 indexed citations
17.
Burn, John, D. Timothy Bishop, Pamela Chapman, et al.. (2011). A Randomized Placebo-Controlled Prevention Trial of Aspirin and/or Resistant Starch in Young People with Familial Adenomatous Polyposis. Cancer Prevention Research. 4(5). 655–665. 151 indexed citations
18.
Loveridge, Carolyn J., et al.. (2010). Nucleolar Targeting of RelA(p65) Is Regulated by COMMD1-Dependent Ubiquitination. Cancer Research. 70(1). 139–149. 56 indexed citations
19.
Farrington, Susan M., Albert Tenesa, Rebecca A. Barnetson, et al.. (2005). Germline Susceptibility to Colorectal Cancer Due to Base-Excision Repair Gene Defects. The American Journal of Human Genetics. 77(1). 112–119. 208 indexed citations
20.
Campbell, Harlan, et al.. (2003). The contribution of DNA mismatch repair gene defects to the burden of gynecological cancer. International Journal of Gynecological Cancer. 13(3). 262–277. 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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