Aldons J. Lusis

2.2k total citations · 1 hit paper
17 papers, 1.8k citations indexed

About

Aldons J. Lusis is a scholar working on Molecular Biology, Genetics and Immunology. According to data from OpenAlex, Aldons J. Lusis has authored 17 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 6 papers in Genetics and 4 papers in Immunology. Recurrent topics in Aldons J. Lusis's work include RNA Research and Splicing (6 papers), Virus-based gene therapy research (2 papers) and Genetic Associations and Epidemiology (2 papers). Aldons J. Lusis is often cited by papers focused on RNA Research and Splicing (6 papers), Virus-based gene therapy research (2 papers) and Genetic Associations and Epidemiology (2 papers). Aldons J. Lusis collaborates with scholars based in United States, France and Hong Kong. Aldons J. Lusis's co-authors include Yu-Rong Xia, Diana M. Shih, Alan M. Fogelman, Lawrence W. Castellani, Lucio G. Costa, Susan Hama, Ilya Gukovsky, Sheng‐Cai Lin, Paul E. Sawchenko and Chijen R. Lin and has published in prestigious journals such as Nature, Cell Metabolism and PLoS Genetics.

In The Last Decade

Aldons J. Lusis

17 papers receiving 1.8k citations

Hit Papers

Mice lacking serum paraoxonase are susceptible to organop... 1998 2026 2007 2016 1998 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Aldons J. Lusis United States 16 740 555 452 396 272 17 1.8k
Yu-Rong Xia United States 19 825 1.1× 830 1.5× 194 0.4× 474 1.2× 120 0.4× 28 2.1k
Qida Ju United States 12 387 0.5× 988 1.8× 352 0.8× 88 0.2× 105 0.4× 16 2.0k
Masahiro Masada Japan 21 145 0.2× 635 1.1× 169 0.4× 255 0.6× 55 0.2× 43 1.5k
Venkateswaran Subramanian United States 24 80 0.1× 438 0.8× 430 1.0× 158 0.4× 140 0.5× 54 1.6k
S. E. Olpin United Kingdom 31 1.5k 2.1× 1.9k 3.4× 190 0.4× 173 0.4× 232 0.9× 81 3.0k
Jianling Xie Australia 25 310 0.4× 1.0k 1.9× 171 0.4× 47 0.1× 110 0.4× 55 1.8k
Nobuhiro Morisaki Japan 26 107 0.1× 748 1.3× 208 0.5× 50 0.1× 81 0.3× 73 1.7k
Gursev S. Dhaunsi Kuwait 21 139 0.2× 626 1.1× 259 0.6× 23 0.1× 77 0.3× 63 1.4k
Gabriela Orasanu United States 14 108 0.1× 822 1.5× 302 0.7× 24 0.1× 91 0.3× 20 1.6k
Agnieszka Karkucińska‐Więckowska Poland 20 240 0.3× 943 1.7× 111 0.2× 44 0.1× 81 0.3× 48 1.5k

Countries citing papers authored by Aldons J. Lusis

Since Specialization
Citations

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

Fields of papers citing papers by Aldons J. Lusis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aldons J. Lusis

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

All Works

17 of 17 papers shown
1.
Shu, Le, Kei Hang Katie Chan, Victor Wei Zhang, et al.. (2017). Shared genetic regulatory networks for cardiovascular disease and type 2 diabetes in multiple populations of diverse ethnicities in the United States. PLoS Genetics. 13(9). e1007040–e1007040. 62 indexed citations
2.
Gordts, Philip L.S.M., Erin M. Foley, Roger Lawrence, et al.. (2014). Reducing Macrophage Proteoglycan Sulfation Increases Atherosclerosis and Obesity through Enhanced Type I Interferon Signaling. Cell Metabolism. 20(5). 813–826. 64 indexed citations
3.
Kautz, Léon, Victoria Gabayan, Xuping Wang, et al.. (2013). Testing the Iron Hypothesis in a Mouse Model of Atherosclerosis. Cell Reports. 5(5). 1436–1442. 43 indexed citations
4.
Drake, Thomas A., et al.. (2001). Genetic loci influencing natural variations in femoral bone morphometry in mice. Journal of Orthopaedic Research®. 19(4). 511–517. 27 indexed citations
5.
Shih, Diana M., Yu-Rong Xia, Susan Hama, et al.. (1998). Mice lacking serum paraoxonase are susceptible to organophosphate toxicity and atherosclerosis. Nature. 394(6690). 284–287. 900 indexed citations breakdown →
6.
Jiang, Zhiming, Diana M. Shih, Yu-Rong Xia, et al.. (1998). Structure, Organization, and Chromosomal Mapping of the Gene Encoding Macrosialin, a Macrophage-Restricted Protein. Genomics. 50(2). 199–205. 25 indexed citations
7.
Tischfield, Jay A., Yu-Rong Xia, Diana M. Shih, et al.. (1996). Low-Molecular-Weight, Calcium-Dependent Phospholipase A2Genes Are Linked and Map to Homologous Chromosome Regions in Mouse and Human. Genomics. 32(3). 328–333. 91 indexed citations
8.
Ardehali, Abbas, et al.. (1995). Direct gene transfer into donor hearts at the time of harvest. Journal of Thoracic and Cardiovascular Surgery. 109(4). 716–720. 42 indexed citations
9.
Warden, Craig H., Skaidrite K. Krisans, Aaron Daluiski, et al.. (1994). Mouse Cellular Nucleic Acid Binding Proteins: A Highly Conserved Family Identified by Genetic Mapping and Sequencing. Genomics. 24(1). 14–19. 42 indexed citations
10.
Lin, Sheng‐Cai, Chijen R. Lin, Ilya Gukovsky, et al.. (1993). Molecular basis of the little mouse phenotype and Implications for cell type-specific growth. Nature. 364(6434). 208–213. 385 indexed citations
11.
Sparkes, Robert S., et al.. (1993). Localization of the Gene-Encoding Upstream Stimulatory Factor (USF) to Human Chromosome 1q22-q23. Genomics. 16(1). 266–268. 21 indexed citations
12.
Berliner, Judith A., et al.. (1993). Induction of Chemotactic Cytokines by Minimally Oxidized Ldl. Advances in experimental medicine and biology. 351. 13–18. 27 indexed citations
13.
Heiba, Ibrahim M., Anh Diep, Varghese George, et al.. (1993). Genetic contributions to quantitative lipoprotein traits associated with coronary artery disease: Analysis of a large pedigree from the Bogalusa heart study. American Journal of Medical Genetics. 47(6). 875–883. 23 indexed citations
14.
Xia, Yu-Rong, Bogi Andersen, Margarete Mehrabian, et al.. (1993). Chromosomal Organization of Mammalian POU Domain Factors. Genomics. 18(1). 126–130. 21 indexed citations
15.
Diep, Anh, I Klisak, T. Mohandas, et al.. (1991). Assignment of the gene for cyclic AMP-response element binding protein 2 (CREB2) to human chromosome 2q24.1–q32. Genomics. 11(4). 1161–1163. 5 indexed citations
16.
Mehrabian, Margarete, Robert S. Sparkes, T. Mohandas, Alan M. Fogelman, & Aldons J. Lusis. (1991). Localization of monocyte chemotactic protein-1 gene (SCYA2) to human chromosome 17q11.2–q21.1. Genomics. 9(1). 200–203. 37 indexed citations
17.
Johnson, Lorin K., et al.. (1990). Localization and Evolution of Two Human Phospholipase A2 Genes and Two Related Genetic Elements. Advances in experimental medicine and biology. 275. 17–34. 23 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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