David A. Landry

588 total citations
19 papers, 456 citations indexed

About

David A. Landry is a scholar working on Pharmacology, Microbiology and Reproductive Medicine. According to data from OpenAlex, David A. Landry has authored 19 papers receiving a total of 456 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Pharmacology, 5 papers in Microbiology and 5 papers in Reproductive Medicine. Recurrent topics in David A. Landry's work include Antibiotics Pharmacokinetics and Efficacy (5 papers), Microbial infections and disease research (5 papers) and Ovarian cancer diagnosis and treatment (3 papers). David A. Landry is often cited by papers focused on Antibiotics Pharmacokinetics and Efficacy (5 papers), Microbial infections and disease research (5 papers) and Ovarian cancer diagnosis and treatment (3 papers). David A. Landry collaborates with scholars based in Canada, United States and Tanzania. David A. Landry's co-authors include Luc J. Martin, Frank Cloutier, Ellen P. Guthrie, Barbara C. Vanderhyden, David P. Cook, Jeremy Upham, Mark G. Papich, Gary O. Korsrud, James D. MacNeil and Joe O. Boison and has published in prestigious journals such as International Journal of Molecular Sciences, Science Advances and Journal of Dairy Science.

In The Last Decade

David A. Landry

19 papers receiving 438 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 A. Landry Canada 10 135 105 76 69 66 19 456
A. Di Franco Italy 16 202 1.5× 84 0.8× 39 0.5× 67 1.0× 98 1.5× 48 805
Ping Xue China 17 125 0.9× 120 1.1× 23 0.3× 320 4.6× 48 0.7× 47 990
Yoshihiro Futamura Japan 12 135 1.0× 71 0.7× 37 0.5× 53 0.8× 57 0.9× 37 568
John Coley United Kingdom 14 234 1.7× 100 1.0× 41 0.5× 110 1.6× 30 0.5× 24 603
Haibo Chang China 11 328 2.4× 115 1.1× 14 0.2× 40 0.6× 82 1.2× 12 494
Yanxia Liu China 14 222 1.6× 21 0.2× 80 1.1× 53 0.8× 21 0.3× 36 627
James C. Cornette United States 13 126 0.9× 130 1.2× 121 1.6× 108 1.6× 33 0.5× 32 638
George Alexiades Stamatiades United States 7 91 0.7× 106 1.0× 13 0.2× 70 1.0× 13 0.2× 14 408
D. Beerens Belgium 12 146 1.1× 55 0.5× 40 0.5× 29 0.4× 10 0.2× 19 530
Lun Hua China 11 142 1.1× 21 0.2× 11 0.1× 39 0.6× 125 1.9× 52 442

Countries citing papers authored by David A. Landry

Since Specialization
Citations

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

Fields of papers citing papers by David A. Landry

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David A. Landry

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

All Works

19 of 19 papers shown
1.
Abedini, Atefeh, David A. Landry, Angus D. Macaulay, et al.. (2022). SWI/SNF chromatin remodeling subunitSmarca4/BRG1 is essential for female fertility. Biology of Reproduction. 108(2). 279–291. 6 indexed citations
2.
Landry, David A., et al.. (2022). Metformin prevents age-associated ovarian fibrosis by modulating the immune landscape in female mice. Science Advances. 8(35). eabq1475–eabq1475. 74 indexed citations
3.
Cook, David P., Curtis W. McCloskey, Mélanie Grondin, et al.. (2021). Transcriptional heterogeneity of stemness phenotypes in the ovarian epithelium. Communications Biology. 4(1). 527–527. 7 indexed citations
4.
Landry, David A., et al.. (2020). The significance of ovarian fibrosis. Oncotarget. 11(47). 4366–4370. 36 indexed citations
5.
6.
Landry, David A., et al.. (2017). Steroidogenic genes expressions are repressed by high levels of leptin and the JAK/STAT signaling pathway in MA-10 Leydig cells. Molecular and Cellular Biochemistry. 433(1-2). 79–95. 39 indexed citations
7.
Landry, David A., et al.. (2014). Adiponectin influences progesterone production from MA-10 Leydig cells in a dose-dependent manner. Endocrine. 48(3). 957–967. 21 indexed citations
8.
Landry, David A., Frank Cloutier, & Luc J. Martin. (2013). Implications of leptin in neuroendocrine regulation of male reproduction. Reproductive Biology. 13(1). 1–14. 91 indexed citations
9.
Jean, Stéphanie, et al.. (2012). Influence of the adipose derived hormone resistin on signal transducer and activator of transcription factors, steroidogenesis and proliferation of Leydig cells. Asian Pacific Journal of Reproduction. 1(1). 1–6. 6 indexed citations
10.
Landry, David A., et al.. (2008). Novel endo- -N-acetylgalactosaminidases with broader substrate specificity. Glycobiology. 18(10). 799–805. 82 indexed citations
11.
Dubreuil, P., et al.. (2001). Penicillin concentrations in serum, milk, and urine following intramuscular and subcutaneous administration of increasing doses of procaine penicillin G in lactating dairy cows.. PubMed. 65(3). 173–80. 9 indexed citations
12.
Korsrud, Gary O., Craig D C Salisbury, Carrie Rhodes, et al.. (1998). Depletion of penicillin G residues in tissues, plasma and injection sites of market pigs injected intramuscularly with procaine penicillin G. Food Additives & Contaminants. 15(4). 421–426. 13 indexed citations
13.
Korsrud, Gary O., Joe O. Boison, Mark G. Papich, et al.. (1994). Depletion of penicillin G residues in tissues and injection sites of yearling beef steers dosed with benzathine penicillin G alone or in combination with procaine penicillin G. Food Additives & Contaminants. 11(1). 1–6. 6 indexed citations
14.
Papich, Mark G., Gary O. Korsrud, Joe O. Boison, et al.. (1994). Disposition of penicillin G after administration of benzathine penicillin G, or a combination of benzathine penicillin G and procaine penicillin G in cattle. American Journal of Veterinary Research. 55(6). 825–830. 10 indexed citations
15.
Papich, Mark G., Gary O. Korsrud, Joe O. Boison, et al.. (1993). A study of the disposition of procaine penicillin G in feedlot steers following intramuscular and subcutaneous injection. Journal of Veterinary Pharmacology and Therapeutics. 16(3). 317–327. 24 indexed citations
16.
Korsrud, Gary O., Joe O. Boison, Mark G. Papich, et al.. (1993). Depletion of intramuscularly and subcutaneously injected procaine penicillin G from tissues and plasma of yearling beef steers.. PubMed. 57(4). 223–30. 24 indexed citations
17.
Landry, David A., et al.. (1992). In Vitro Germicidal Activity of Teat Dips Against Nocardia asteroides and Other Udder Pathogens. Journal of Dairy Science. 75(5). 1233–1240. 2 indexed citations
18.
Jankowski, Krzysztof, K. Choi, & David A. Landry. (1989). Computer-assisted clover-leaf like structures of t-RNA. Journal of Molecular Structure THEOCHEM. 188(1-2). 67–77. 2 indexed citations
19.
Goldman, Max & David A. Landry. (1976). The effect of povidone-iodine on thyroid function in rats. Toxicology and Applied Pharmacology. 35(2). 341–346. 2 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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