David Oakes

419 total citations
11 papers, 328 citations indexed

About

David Oakes is a scholar working on Immunology, Epidemiology and Management Science and Operations Research. According to data from OpenAlex, David Oakes has authored 11 papers receiving a total of 328 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Immunology, 3 papers in Epidemiology and 2 papers in Management Science and Operations Research. Recurrent topics in David Oakes's work include Immune Cell Function and Interaction (3 papers), Microscopic Colitis (2 papers) and Immunotherapy and Immune Responses (2 papers). David Oakes is often cited by papers focused on Immune Cell Function and Interaction (3 papers), Microscopic Colitis (2 papers) and Immunotherapy and Immune Responses (2 papers). David Oakes collaborates with scholars based in United Kingdom, United States and Ireland. David Oakes's co-authors include L K Trejdosiewicz, C J Smart, Arthur W. Boylston, Jacob N. Finkelstein, Gloria Pryhuber, Linlin Chen, P D Howdle, M S Losowsky, F. Lancaster and Jean E. Crabtree and has published in prestigious journals such as Journal of the American Statistical Association, Biometrika and British journal of surgery.

In The Last Decade

David Oakes

11 papers receiving 321 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 Oakes United Kingdom 8 168 77 49 48 47 11 328
Martina Wiesner Netherlands 9 160 1.0× 159 2.1× 63 1.3× 68 1.4× 155 3.3× 9 365
N. Hmida Tunisia 7 249 1.5× 113 1.5× 48 1.0× 27 0.6× 109 2.3× 13 374
Lene S. Høydahl Norway 10 167 1.0× 75 1.0× 36 0.7× 31 0.6× 115 2.4× 20 312
Anne Israelsson Sweden 10 103 0.6× 95 1.2× 69 1.4× 31 0.6× 115 2.4× 12 358
Bishnudeo Roy India 9 217 1.3× 48 0.6× 22 0.4× 14 0.3× 53 1.1× 17 321
V.C. Suraj India 4 297 1.8× 36 0.5× 33 0.7× 125 2.6× 11 0.2× 5 424
Tokurou Uesu Japan 12 226 1.3× 22 0.3× 83 1.7× 49 1.0× 11 0.2× 15 343
Shigeru Yamaga Japan 8 163 1.0× 79 1.0× 21 0.4× 31 0.6× 8 0.2× 13 390
Tatsuhiko Hayashi Japan 8 160 1.0× 88 1.1× 78 1.6× 99 2.1× 17 0.4× 26 418
Koji Ishii Japan 8 81 0.5× 29 0.4× 60 1.2× 57 1.2× 7 0.1× 18 279

Countries citing papers authored by David Oakes

Since Specialization
Citations

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

Fields of papers citing papers by David Oakes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Oakes

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

All Works

11 of 11 papers shown
1.
Chen, Linlin, et al.. (2009). IL-1β Augments TNF-α–Mediated Inflammatory Responses from Lung Epithelial Cells. Journal of Interferon & Cytokine Research. 29(5). 273–284. 89 indexed citations
2.
Oakes, David. (2003). Copula model generated by Dabrowska's association measure. Biometrika. 90(2). 478–481. 7 indexed citations
3.
Oakes, David. (2000). Survival Analysis. Journal of the American Statistical Association. 95(449). 282–282. 1 indexed citations
4.
Oakes, David & Jong‐Hyeon Jeong. (1998). Frailty Models and Rank Tests. Lifetime Data Analysis. 4(3). 209–228. 14 indexed citations
5.
Smart, C J, et al.. (1991). Expression of the LFA‐1 β2 Integrin (CD11a/CD18) and ICAM‐1 (CD54) in Normal and Coeliac Small Bowel Mucosa. Scandinavian Journal of Immunology. 34(3). 299–305. 24 indexed citations
6.
Trejdosiewicz, L K, C J Smart, David Oakes, et al.. (1991). Gamma delta T cell receptor-positive cells of the human gastrointestinal mucosa: occurrence and V region gene expression in Heliobacter pylori-associated gastritis, coeliac disease and inflammatory bowel disease.. PubMed. 84(3). 440–4. 80 indexed citations
7.
Trejdosiewicz, L K, et al.. (1990). Expression of T cell receptors TcR1 (gamma/delta) and TcR2 (alpha/beta) in the human intestinal mucosa. PubMed. 68(1). 69–70. 58 indexed citations
8.
Trejdosiewicz, L K, Shaimaa M. Badr-Eldin, Giuseppe Malizia, et al.. (1989). Colonic mucosal T lymphocytes in ulcerative colitis: Expression of CD7 antigen in relation to MHC class II (HLA-D) antigens. Digestive Diseases and Sciences. 34(9). 1449–1456. 18 indexed citations
9.
Trejdosiewicz, L K, Giuseppe Malizia, Shaimaa M. Badr-Eldin, et al.. (1987). T Cell and Mononuclear Phagocyte Populations of the Human Small and Large Intestine. Advances in experimental medicine and biology. 216A. 465–473. 21 indexed citations
10.
Oakes, David. (1985). Self-Calibrating Priors Do Not Exist. Journal of the American Statistical Association. 80(390). 339–339. 12 indexed citations
11.
Higley, B, et al.. (1982). Urinary pseudouridine/creatinine ratio as an indicator of gastrointestinal cancer. British journal of surgery. 69(12). 699–701. 4 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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