David L. Aylor

2.3k total citations
28 papers, 912 citations indexed

About

David L. Aylor is a scholar working on Genetics, Molecular Biology and Immunology. According to data from OpenAlex, David L. Aylor has authored 28 papers receiving a total of 912 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Genetics, 11 papers in Molecular Biology and 5 papers in Immunology. Recurrent topics in David L. Aylor's work include Genetic Mapping and Diversity in Plants and Animals (13 papers), Genetic and phenotypic traits in livestock (4 papers) and Effects and risks of endocrine disrupting chemicals (3 papers). David L. Aylor is often cited by papers focused on Genetic Mapping and Diversity in Plants and Animals (13 papers), Genetic and phenotypic traits in livestock (4 papers) and Effects and risks of endocrine disrupting chemicals (3 papers). David L. Aylor collaborates with scholars based in United States. David L. Aylor's co-authors include David W. Threadgill, Ignazio Carbone, Eric W. Price, Darla R. Miller, Gary A. Churchill, Fernando Pardo‐Manuel de Villena, Heather B. Patisaul, Zhao‐Bang Zeng, Elissa J. Chesler and Fernando Pardo-Manuel de Villena and has published in prestigious journals such as Genes & Development, Bioinformatics and Scientific Reports.

In The Last Decade

David L. Aylor

28 papers receiving 901 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 L. Aylor United States 17 383 334 158 105 101 28 912
Aiqing Li China 16 280 0.7× 577 1.7× 84 0.5× 78 0.7× 35 0.3× 50 1.4k
Nicola Wrobel United Kingdom 11 151 0.4× 579 1.7× 140 0.9× 71 0.7× 27 0.3× 16 1.1k
Hongshan Jiang China 8 186 0.5× 648 1.9× 264 1.7× 113 1.1× 14 0.1× 16 1.2k
Catherine E. Welsh United States 7 469 1.2× 379 1.1× 101 0.6× 84 0.8× 13 0.1× 11 862
Penny K. Riggs United States 18 421 1.1× 323 1.0× 131 0.8× 121 1.2× 22 0.2× 76 987
Federica Franciosi Italy 25 269 0.7× 835 2.5× 65 0.4× 163 1.6× 42 0.4× 68 2.0k
Véronique Duranthon France 25 620 1.6× 1.2k 3.6× 107 0.7× 173 1.6× 62 0.6× 75 2.1k
Kathrin A. Dunlap United States 23 326 0.9× 506 1.5× 107 0.7× 699 6.7× 29 0.3× 54 1.7k
Brigitte Mourot France 17 501 1.3× 254 0.8× 24 0.2× 130 1.2× 72 0.7× 35 1.1k

Countries citing papers authored by David L. Aylor

Since Specialization
Citations

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

Fields of papers citing papers by David L. Aylor

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David L. Aylor

This figure shows the co-authorship network connecting the top 25 collaborators of David L. Aylor. A scholar is included among the top collaborators of David L. Aylor 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 L. Aylor. David L. Aylor 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.
2.
Horman, Brian, et al.. (2022). Impacts of Gestational FireMaster 550 Exposure on the Neonatal Cortex Are Sex Specific and Largely Attributable to the Organophosphate Esters. Neuroendocrinology. 113(12). 1262–1282. 11 indexed citations
3.
Kwon, Do Hoon, et al.. (2022). A cross-species approach using an in vivo evaluation platform in mice demonstrates that sequence variation in human RABEP2 modulates ischemic stroke outcomes. The American Journal of Human Genetics. 109(10). 1814–1827. 4 indexed citations
4.
Aylor, David L., et al.. (2021). A Neuroprotective Locus Modulates Ischemic Stroke Infarction Independent of Collateral Vessel Anatomy. Frontiers in Neuroscience. 15. 705160–705160. 3 indexed citations
5.
Handel, Mary Ann, et al.. (2020). Age and Genetic Background Modify Hybrid Male Sterility in House Mice. Genetics. 216(2). 585–597. 14 indexed citations
6.
Patisaul, Heather B., Suzanne E. Fenton, & David L. Aylor. (2018). Animal models of endocrine disruption. Best Practice & Research Clinical Endocrinology & Metabolism. 32(3). 283–297. 38 indexed citations
7.
House, John S., Kranti Konganti, David W. Threadgill, et al.. (2018). Population-based dose–response analysis of liver transcriptional response to trichloroethylene in mouse. Mammalian Genome. 29(1-2). 168–181. 12 indexed citations
8.
Konganti, Kranti, Andrew Hillhouse, Alexis Jones, et al.. (2018). Permissiveness to form pluripotent stem cells may be an evolutionarily derived characteristic in Mus musculus. Scientific Reports. 8(1). 14706–14706. 9 indexed citations
9.
Robinson, Matthew C., et al.. (2016). Genetic Background, Maternal Age, and Interaction Effects Mediate Rates of Crossing Over inDrosophila melanogasterFemales. G3 Genes Genomes Genetics. 6(5). 1409–1416. 10 indexed citations
10.
Rebuli, Meghan E., et al.. (2015). Impact of Low-Dose Oral Exposure to Bisphenol A (BPA) on Juvenile and Adult Rat Exploratory and Anxiety Behavior: A CLARITY-BPA Consortium Study. Toxicological Sciences. 148(2). 341–354. 50 indexed citations
11.
Gralinski, Lisa E., Martin T. Ferris, David L. Aylor, et al.. (2015). Genome Wide Identification of SARS-CoV Susceptibility Loci Using the Collaborative Cross. PLoS Genetics. 11(10). e1005504–e1005504. 101 indexed citations
12.
Kelada, Samir N. P., David L. Aylor, Peter S. Chines, et al.. (2014). Integrative Genetic Analysis of Allergic Inflammation in the Murine Lung. American Journal of Respiratory Cell and Molecular Biology. 51(3). 436–445. 25 indexed citations
13.
Aylor, David L., Bailey C. E. Peck, Peter S. Chines, et al.. (2014). Genetic Regulation ofZfp30, CXCL1, and Neutrophilic Inflammation in Murine Lung. Genetics. 198(2). 735–745. 33 indexed citations
14.
Xiao, Hong, Dominic J. Ciavatta, David L. Aylor, et al.. (2013). Genetically Determined Severity of Anti-Myeloperoxidase Glomerulonephritis. American Journal Of Pathology. 182(4). 1219–1226. 18 indexed citations
15.
Xie, Yuying, Darla R. Miller, Timothy A. Bell, et al.. (2013). Using the emerging Collaborative Cross to probe the immune system. Genes and Immunity. 15(1). 38–46. 66 indexed citations
16.
Bottomly, Daniel, Martin T. Ferris, Lauri D. Aicher, et al.. (2012). Expression Quantitative Trait Loci for Extreme Host Response to Influenza A in Pre-Collaborative Cross Mice. G3 Genes Genomes Genetics. 2(2). 213–221. 68 indexed citations
17.
Yang, Ivana V., Laura A. Warg, Elizabeth Davidson, et al.. (2010). INNATE IMMUNE GENE DISCOVERY USING MACROPHAGE RESPONSE TO PATHOGEN-ASSOCIATED MOLECULAR PATTERNS (PAMPS). A1273–A1273. 1 indexed citations
18.
Munger, Steven C., et al.. (2009). Elucidation of the transcription network governing mammalian sex determination by exploiting strain-specific susceptibility to sex reversal. Genes & Development. 23(21). 2521–2536. 59 indexed citations
19.
Aylor, David L. & Zhao‐Bang Zeng. (2008). From Classical Genetics to Quantitative Genetics to Systems Biology: Modeling Epistasis. PLoS Genetics. 4(3). e1000029–e1000029. 26 indexed citations
20.
Zou, Wei, David L. Aylor, & Zhao‐Bang Zeng. (2007). eQTL Viewer: visualizing how sequence variation affects genome-wide transcription. BMC Bioinformatics. 8(1). 7–7. 21 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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