David Jackson

4.5k total citations
89 papers, 1.9k citations indexed

About

David Jackson is a scholar working on Molecular Biology, Computational Theory and Mathematics and Oncology. According to data from OpenAlex, David Jackson has authored 89 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Molecular Biology, 14 papers in Computational Theory and Mathematics and 12 papers in Oncology. Recurrent topics in David Jackson's work include Computational Drug Discovery Methods (13 papers), Evolutionary Algorithms and Applications (9 papers) and Metaheuristic Optimization Algorithms Research (9 papers). David Jackson is often cited by papers focused on Computational Drug Discovery Methods (13 papers), Evolutionary Algorithms and Applications (9 papers) and Metaheuristic Optimization Algorithms Research (9 papers). David Jackson collaborates with scholars based in United Kingdom, United States and Germany. David Jackson's co-authors include Theodoros Soldatos, Richard E. Randall, Saad M. S. Mukras, Nam Ho Kim, W. Gregory Sawyer, Brett Bode, Rupert J. Russell, Georg Casari, David Halstead and Ricky A. Kendall and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Genes & Development and SHILAP Revista de lepidopterología.

In The Last Decade

David Jackson

88 papers receiving 1.8k 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 Jackson United Kingdom 23 599 349 250 241 172 89 1.9k
Chun Chen China 23 631 1.1× 144 0.4× 101 0.4× 161 0.7× 98 0.6× 75 1.8k
Jorng‐Tzong Horng Taiwan 28 1.4k 2.3× 141 0.4× 171 0.7× 150 0.6× 47 0.3× 135 2.6k
R. Sujatha India 23 283 0.5× 346 1.0× 155 0.6× 224 0.9× 165 1.0× 93 2.3k
Fernando Gómez Spain 20 343 0.6× 165 0.5× 173 0.7× 357 1.5× 230 1.3× 106 1.8k
Wenbin Liu China 27 828 1.4× 160 0.5× 257 1.0× 103 0.4× 50 0.3× 147 2.4k
Chan‐Il Park South Korea 23 652 1.1× 165 0.5× 126 0.5× 893 3.7× 129 0.8× 179 1.9k
Joshua W. K. Ho Australia 36 2.6k 4.3× 312 0.9× 224 0.9× 281 1.2× 80 0.5× 141 4.4k
Reinhard Laubenbacher United States 31 1.4k 2.4× 202 0.6× 130 0.5× 159 0.7× 54 0.3× 150 3.0k
Geir Kjetil Sandve Norway 23 1.1k 1.9× 125 0.4× 156 0.6× 390 1.6× 47 0.3× 82 2.0k
Ivan Merelli Italy 22 1.3k 2.1× 241 0.7× 115 0.5× 208 0.9× 25 0.1× 144 2.0k

Countries citing papers authored by David Jackson

Since Specialization
Citations

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

Fields of papers citing papers by David Jackson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Jackson

This figure shows the co-authorship network connecting the top 25 collaborators of David Jackson. A scholar is included among the top collaborators of David Jackson 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 Jackson. David Jackson 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.
Jennings, Victoria A., G Migneco, Nicola Ingram, et al.. (2024). Enhancing oncolytic virotherapy by extracellular vesicle mediated microRNA reprogramming of the tumour microenvironment. Frontiers in Immunology. 15. 1500570–1500570. 1 indexed citations
2.
Mustea, Alexander, Damian J. Ralser, Eva K. Egger, et al.. (2024). Determination of endometrial cancer molecular subtypes using a whole exome-sequencing based single-method approach. Journal of Cancer Research and Clinical Oncology. 150(7). 367–367. 2 indexed citations
3.
Jackson, David, et al.. (2023). Rewiring Drug Research and Development through Human Data-Driven Discovery (HD3). Pharmaceutics. 15(6). 1673–1673. 1 indexed citations
4.
Mustea, Alexander, Damian J. Ralser, Eva K. Egger, et al.. (2023). Determination of the Cancer Genome Atlas (TCGA) Endometrial Cancer Molecular Subtypes Using the Variant Interpretation and Clinical Decision Support Software MH Guide. Cancers. 15(7). 2053–2053. 6 indexed citations
5.
Soldatos, Theodoros, David Jackson, Francesca Diella, et al.. (2022). The COVID-19 explorer—An integrated, whole patient knowledge model of COVID-19 disease. SHILAP Revista de lepidopterología. 2. 1035215–1035215. 3 indexed citations
6.
Hirotsu, Yosuke, Hiroshi Nakagomi, Ikuko Sakamoto, et al.. (2020). Consolidated BRCA1/2 Variant Interpretation by MH BRCA Correlates with Predicted PARP Inhibitor Efficacy Association by MH Guide. International Journal of Molecular Sciences. 21(11). 3895–3895. 4 indexed citations
7.
Hacker, Christian, Christos Pliotas, Lee Sherry, et al.. (2016). Nanoparticle suspensions enclosed in methylcellulose: a new approach for quantifying nanoparticles in transmission electron microscopy. Scientific Reports. 6(1). 25275–25275. 19 indexed citations
8.
Jackson, David, et al.. (2016). Use of “big data” in drug discovery and clinical trials. Gynecologic Oncology. 141(1). 17–23. 17 indexed citations
9.
Nemunaitis, John, et al.. (2015). Relationships of clinical response to relevant molecular signal during Phase I testing of Aurora Kinase A inhibitor: Retrospective assessment. Integrative Molecular Medicine. 2(5). 1 indexed citations
10.
Burkhart, Keith, et al.. (2015). Data Mining FAERS to Analyze Molecular Targets of Drugs Highly Associated with Stevens-Johnson Syndrome. Journal of Medical Toxicology. 11(2). 265–273. 10 indexed citations
11.
Jackson, David & Anil K. Sood. (2011). Personalized cancer medicine—advances and socio-economic challenges. Nature Reviews Clinical Oncology. 8(12). 735–741. 23 indexed citations
12.
Soldatos, Theodoros, et al.. (2011). Abstract 56: MASE: A system for the molecular analysis of side effect information and its application to marketed cancer therapeutics. Cancer Research. 71(8_Supplement). 56–56. 2 indexed citations
13.
14.
Jackson, David. (2009). Self-adaptive focusing of evolutionary effort in hierarchical genetic programming. 1821–1828. 5 indexed citations
15.
Hale, Benjamin G., Axel Knebel, Catherine H. Botting, et al.. (2008). CDK/ERK-mediated phosphorylation of the human influenza A virus NS1 protein at threonine-215. Virology. 383(1). 6–11. 68 indexed citations
16.
Jackson, David, Martin Stein, Alejandro Merino, & Roland Eils. (2006). Microarrays meet the Voltaire challenge: Drug discovery on a chip?. Drug Discovery Today Technologies. 3(2). 153–161. 4 indexed citations
17.
Gagneur, Julien, David Jackson, & Georg Casari. (2003). Hierarchical analysis of dependency in metabolic networks. Bioinformatics. 19(8). 1027–1034. 43 indexed citations
18.
Jackson, David, et al.. (2000). Computer systems for distributed and distance learning. Journal of Computer Assisted Learning. 16(3). 213–228. 19 indexed citations
19.
Jackson, David, et al.. (1989). Bioequivalence (bioavailability) of generic topical corticosteroids. Journal of the American Academy of Dermatology. 20(5). 791–796. 24 indexed citations
20.
Guin, Jere D., et al.. (1987). Wandering fixed drug eruption: A mucocutaneous reaction to acetaminophen. Journal of the American Academy of Dermatology. 17(3). 399–402. 22 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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