David J. Dow

5.6k total citations · 1 hit paper
15 papers, 1.1k citations indexed

About

David J. Dow is a scholar working on Molecular Biology, Genetics and Oncology. According to data from OpenAlex, David J. Dow has authored 15 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 6 papers in Genetics and 3 papers in Oncology. Recurrent topics in David J. Dow's work include CRISPR and Genetic Engineering (4 papers), Virus-based gene therapy research (2 papers) and CAR-T cell therapy research (2 papers). David J. Dow is often cited by papers focused on CRISPR and Genetic Engineering (4 papers), Virus-based gene therapy research (2 papers) and CAR-T cell therapy research (2 papers). David J. Dow collaborates with scholars based in United Kingdom, United States and Germany. David J. Dow's co-authors include Allen D. Roses, Linda M. Thurmond, Katherine L. Baker-Neblett, Denise Shortino, Michael Mosteller, Eric Lai, Seth Hetherington, Arlene R. Hughes, Michael Stocum and William Spreen and has published in prestigious journals such as The Lancet, Nature Communications and Human Molecular Genetics.

In The Last Decade

David J. Dow

15 papers receiving 1.1k citations

Hit Papers

align trajectories

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.

Genetic variations in HLA-B region and hypersensitivity reactions to abacavir

2002 583 citations Seth Hetherington, Arlene R. Hughes et al. The Lancet profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
David J. Dow United Kingdom	11	399	327	185	173	136	15	1.1k
María Isidoro‐García Spain	18	310 0.8×	68 0.2×	87 0.5×	57 0.3×	185 1.4×	90	1.1k
Shaomin Yang China	18	316 0.8×	52 0.2×	54 0.3×	47 0.3×	60 0.4×	56	816
Roscoe D. Atkinson United States	12	259 0.6×	46 0.1×	52 0.3×	38 0.2×	249 1.8×	18	1.1k
V Rossi Italy	12	487 1.2×	25 0.1×	57 0.3×	37 0.2×	197 1.4×	18	1.4k
Paul Frohna United States	17	403 1.0×	57 0.2×	318 1.7×	128 0.7×	263 1.9×	47	1.3k
Dan Lehmann Israel	19	169 0.4×	70 0.2×	158 0.9×	45 0.3×	598 4.4×	36	1.2k
Eiichi Suematsu Japan	19	630 1.6×	29 0.1×	35 0.2×	156 0.9×	139 1.0×	79	1.3k
Asim Diab Sweden	15	472 1.2×	73 0.2×	36 0.2×	74 0.4×	530 3.9×	26	1.1k
Joon Seol Bae South Korea	23	573 1.4×	204 0.6×	463 2.5×	69 0.4×	245 1.8×	111	1.7k
María Eugenia Sáez Spain	21	455 1.1×	30 0.1×	239 1.3×	61 0.4×	201 1.5×	67	1.3k

Countries citing papers authored by David J. Dow

Since Specialization

Citations

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

Fields of papers citing papers by David J. Dow

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David J. Dow

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

All Works

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15 of 15 papers shown

Picco, Gabriele, Elisabeth Chen, Luz García‐Alonso, et al.. (2019). Functional linkage of gene fusions to cancer cell fitness assessed by pharmacological and CRISPR-Cas9 screening. Nature Communications. 10(1). 2198–2198. 78 indexed citations

Rittié, Laure, Takis Athanasopoulos, Marie Davies, et al.. (2019). The Landscape of Early Clinical Gene Therapies outside of Oncology. Molecular Therapy. 27(10). 1706–1717. 21 indexed citations

Lu, Quinn, et al.. (2017). Applications of CRISPR genome editing technology in drug target identification and validation. Expert Opinion on Drug Discovery. 12(6). 541–552. 12 indexed citations

Woollard, Peter, Nalini Mehta, Jessica Vamathevan, et al.. (2011). The application of next-generation sequencing technologies to drug discovery and development. Drug Discovery Today. 16(11-12). 512–519. 31 indexed citations

Dow, David J., Julie Huxley‐Jones, Clyde Francks, et al.. (2011). ADAMTSL3 as a candidate gene for schizophrenia: Gene sequencing and ultra-high density association analysis by imputation. Schizophrenia Research. 127(1-3). 28–34. 38 indexed citations

Dow, David J., Alex D. McMahon, Ian C. Gray, Chris J. Packard, & Pieter H.E. Groot. (2010). CCR2 and coronary artery disease: a woscops substudy. BMC Research Notes. 3(1). 31–31. 6 indexed citations

Parry, David, et al.. (2006). Improved management in threatened preterm labour with rapid fetal fibronectin testing. Australian and New Zealand Journal of Obstetrics and Gynaecology. 46(3). 240–241. 6 indexed citations

Spraggs, Colin F., Sreekumar Pillai, David J. Dow, et al.. (2005). Pharmacogenetics and obesity: common gene variants influence weight loss response of the norepinephrine/dopamine transporter inhibitor GW320659 in obese subjects. Pharmacogenetics and Genomics. 15(12). 883–889. 11 indexed citations

Hetherington, Seth, Arlene R. Hughes, Michael Mosteller, et al.. (2002). Genetic variations in HLA-B region and hypersensitivity reactions to abacavir. The Lancet. 359(9312). 1121–1122. 583 indexed citations breakdown →

10.

Farndon, Peter, et al.. (1999). Prenatal diagnosis of tuberous sclerosis with intracerebral signs at 14 weeks' gestation. Prenatal Diagnosis. 19(6). 575–579. 11 indexed citations

11.

Camacho, Nancy P., David J. Dow, Joseph M. Gertner, et al.. (1998). Identification of the oim mutation by dye terminator chemistry combined with automated direct DNA sequencing. Journal of Orthopaedic Research®. 16(1). 38–42. 8 indexed citations

12.

Dow, David J., David C. Rubinsztein, John R.W. Yates, David Barton, & M.A. Ferguson‐Smith. (1997). Instability of normal (CTG)n alleles in the DM kinase gene.. Journal of Medical Genetics. 34(10). 871–873. 4 indexed citations

13.

Knight, Samantha J.L., Rachael J. Ritchie, Lisa Chakrabarti, et al.. (1996). A study of FRAXE in mentally retarded individuals referred for fragile X syndrome (FRAXA) testing in the United Kingdom.. PubMed. 58(5). 906–13. 37 indexed citations

14.

Warner, Jon, et al.. (1996). A general method for the detection of large CAG repeat expansions by fluorescent PCR.. Journal of Medical Genetics. 33(12). 1022–1026. 208 indexed citations

15.

Sargent, Carole A., N. Affara, Elizabeth Bentley, et al.. (1993). Cloning of the X-linked glycerol kinase deficiency gene and its identification by sequence comparison to the Bacillus subtilis homologue. Human Molecular Genetics. 2(2). 97–106. 31 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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