Aaron J. Mackey

9.3k total citations
35 papers, 2.9k citations indexed

About

Aaron J. Mackey is a scholar working on Molecular Biology, Genetics and Epidemiology. According to data from OpenAlex, Aaron J. Mackey has authored 35 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 6 papers in Genetics and 5 papers in Epidemiology. Recurrent topics in Aaron J. Mackey's work include Genomics and Phylogenetic Studies (6 papers), Machine Learning in Bioinformatics (3 papers) and Melanoma and MAPK Pathways (3 papers). Aaron J. Mackey is often cited by papers focused on Genomics and Phylogenetic Studies (6 papers), Machine Learning in Bioinformatics (3 papers) and Melanoma and MAPK Pathways (3 papers). Aaron J. Mackey collaborates with scholars based in United States, United Kingdom and Sweden. Aaron J. Mackey's co-authors include David S. Roos, William R. Pearson, Jeroen K. Vermunt, Feng Chen, Timothy Haystead, Kenneth M. Murphy, James D. Gorham, William F. Dietrich, Mehmet Güler and Chyi‐Song Hsieh and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Aaron J. Mackey

35 papers receiving 2.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Aaron J. Mackey United States 24 1.1k 962 638 443 283 35 2.9k
Hongbin He China 29 854 0.8× 313 0.3× 521 0.8× 378 0.9× 324 1.1× 166 2.7k
Ping Tang Taiwan 28 1.1k 1.0× 315 0.3× 257 0.4× 273 0.6× 105 0.4× 99 2.4k
Asif Mohmmed India 26 1.3k 1.2× 293 0.3× 294 0.5× 382 0.9× 148 0.5× 87 2.6k
Salvatore G. De-Simone Brazil 27 816 0.8× 203 0.2× 467 0.7× 299 0.7× 236 0.8× 143 2.2k
Anna Bartlett United Kingdom 25 2.0k 1.9× 520 0.5× 435 0.7× 285 0.6× 275 1.0× 49 4.2k
Xinwen Chen China 39 2.5k 2.3× 293 0.3× 1.3k 2.0× 720 1.6× 514 1.8× 224 4.9k
Dong Yü United States 33 1.5k 1.4× 581 0.6× 2.2k 3.5× 912 2.1× 423 1.5× 72 3.9k
Marie‐Agnès Dillies France 28 1.9k 1.8× 213 0.2× 342 0.5× 420 0.9× 445 1.6× 48 3.6k
Annette MacLeod United Kingdom 35 1.3k 1.2× 917 1.0× 1.8k 2.8× 235 0.5× 582 2.1× 112 4.0k
Sergio Verjovski‐Almeida Brazil 41 3.0k 2.8× 1.7k 1.8× 370 0.6× 228 0.5× 243 0.9× 157 5.7k

Countries citing papers authored by Aaron J. Mackey

Since Specialization
Citations

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

Fields of papers citing papers by Aaron J. Mackey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aaron J. Mackey

This figure shows the co-authorship network connecting the top 25 collaborators of Aaron J. Mackey. A scholar is included among the top collaborators of Aaron J. Mackey 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 Aaron J. Mackey. Aaron J. Mackey 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.
Gibson, K., et al.. (2025). Does descriptive representation matter more now than in the past? A reexamination of Black faces in the mirror in a most-racial era. Politics Groups and Identities. 13(5). 1085–1103. 2 indexed citations
2.
Dash, Ajit, Robert A. Figler, Svetlana Marukian, et al.. (2016). Pharmacotoxicology of clinically-relevant concentrations of obeticholic acid in an organotypic human hepatocyte system. Toxicology in Vitro. 39. 93–103. 29 indexed citations
3.
Terelius, Ylva, Robert A. Figler, Svetlana Marukian, et al.. (2015). Transcriptional profiling suggests that Nevirapine and Ritonavir cause drug induced liver injury through distinct mechanisms in primary human hepatocytes. Chemico-Biological Interactions. 255. 31–44. 27 indexed citations
4.
Cole, Banumathi K., Michael B. Simmers, Ryan E. Feaver, et al.. (2015). An In Vitro Cynomolgus Vascular Surrogate System for Preclinical Drug Assessment and Human Translation. Arteriosclerosis Thrombosis and Vascular Biology. 35(10). 2185–2195. 9 indexed citations
5.
Capaldo, Brian J., Mark J. Axelrod, Alexander F. Koeppel, et al.. (2015). Systems Analysis of Adaptive Responses to MAP Kinase Pathway Blockade in BRAF Mutant Melanoma. PLoS ONE. 10(9). e0138210–e0138210. 6 indexed citations
6.
Cantarel, Brandi L., et al.. (2014). BAYSIC: a Bayesian method for combining sets of genome variants with improved specificity and sensitivity. BMC Bioinformatics. 15(1). 104–104. 43 indexed citations
7.
Axelrod, Mark J., Brian J. Capaldo, Karin Jensen, et al.. (2012). Synthetic Lethal Screening with Small-Molecule Inhibitors Provides a Pathway to Rational Combination Therapies for Melanoma. Molecular Cancer Therapeutics. 11(11). 2505–2515. 29 indexed citations
8.
9.
Chen, Feng, Aaron J. Mackey, Jeroen K. Vermunt, & David S. Roos. (2007). Assessing Performance of Orthology Detection Strategies Applied to Eukaryotic Genomes. PLoS ONE. 2(4). e383–e383. 289 indexed citations
10.
Gajria, Bindu, Amit Bahl, John Brestelli, et al.. (2007). ToxoDB: an integrated Toxoplasma gondii database resource. Nucleic Acids Research. 36(Database). D553–D556. 365 indexed citations
11.
Elsik, Christine G., Aaron J. Mackey, Justin Reese, et al.. (2007). Creating a honey bee consensus gene set. Genome biology. 8(1). R13–R13. 184 indexed citations
12.
Chi, An, Simón Beard, Aaron J. Mackey, et al.. (2007). Periplasmic Proteins of the Extremophile Acidithiobacillus ferrooxidans. Molecular & Cellular Proteomics. 6(12). 2239–2251. 79 indexed citations
13.
Khan, Asis, S. Taylor, Chunlei Su, et al.. (2005). Composite genome map and recombination parameters derived from three archetypal lineages of Toxoplasma gondii. Nucleic Acids Research. 33(9). 2980–2992. 127 indexed citations
14.
Radke, Jay R., et al.. (2005). The transcriptome of Toxoplasma gondii. BMC Biology. 3(1). 26–26. 130 indexed citations
15.
Ivarsson, Ylva, et al.. (2003). Identification of Residues in Glutathione Transferase Capable of Driving Functional Diversification in Evolution. Journal of Biological Chemistry. 278(10). 8733–8738. 75 indexed citations
16.
Mackey, Aaron J.. (2003). CRP: Cleavage of Radiolabeled Phosphoproteins. Nucleic Acids Research. 31(13). 3859–3861. 9 indexed citations
17.
Beck, David L., Mehmet Tanyüksel, Aaron J. Mackey, et al.. (2002). Entamoeba histolytica: sequence conservation of the Gal/GalNAc lectin from clinical isolates. Experimental Parasitology. 101(2-3). 157–163. 24 indexed citations
18.
MacDonald, Justin A., Aaron J. Mackey, William R. Pearson, & Timothy Haystead. (2002). A Strategy for the Rapid Identification of Phosphorylation Sites in the Phosphoproteome. Molecular & Cellular Proteomics. 1(4). 314–322. 37 indexed citations
19.
Clifford, Raphaël & Aaron J. Mackey. (2000). Disperse: a simple and efficient approach to parallel database searching. Bioinformatics. 16(6). 564–565. 9 indexed citations
20.
Güler, Mehmet, James D. Gorham, Chyi‐Song Hsieh, et al.. (1996). Genetic Susceptibility to Leishmania : IL-12 Responsiveness in T H 1 Cell Development. Science. 271(5251). 984–987. 333 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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