Lawrence W. Gray

640 total citations
9 papers, 504 citations indexed

About

Lawrence W. Gray is a scholar working on Nutrition and Dietetics, Health, Toxicology and Mutagenesis and Molecular Biology. According to data from OpenAlex, Lawrence W. Gray has authored 9 papers receiving a total of 504 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Nutrition and Dietetics, 4 papers in Health, Toxicology and Mutagenesis and 2 papers in Molecular Biology. Recurrent topics in Lawrence W. Gray's work include Trace Elements in Health (6 papers), Heavy Metal Exposure and Toxicity (4 papers) and Molecular Sensors and Ion Detection (2 papers). Lawrence W. Gray is often cited by papers focused on Trace Elements in Health (6 papers), Heavy Metal Exposure and Toxicity (4 papers) and Molecular Sensors and Ion Detection (2 papers). Lawrence W. Gray collaborates with scholars based in United States, Germany and Philippines. Lawrence W. Gray's co-authors include Svetlana Lutsenko, Tasuku Hirayama, Genevieve C. Van de Bittner, Christopher J. Chang, Jason L. Burkhead, Jean A. Büttner‐Ennever, David Solomon, David S. Zee, Edward B. Maryon and Dominik Hüster and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and PLoS ONE.

In The Last Decade

Lawrence W. Gray

9 papers receiving 499 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lawrence W. Gray United States 7 250 149 144 112 96 9 504
I. B. Mahadevan Australia 11 276 1.1× 113 0.8× 159 1.1× 164 1.5× 77 0.8× 15 637
M. Thomas Morgan United States 12 221 0.9× 62 0.4× 274 1.9× 160 1.4× 142 1.5× 16 566
Gnana S. Siluvai United States 9 299 1.2× 87 0.6× 35 0.2× 138 1.2× 194 2.0× 12 532
Charles P. Fontaine United States 8 597 2.4× 310 2.1× 100 0.7× 192 1.7× 71 0.7× 8 793
Shannon A. Molloy United States 6 383 1.5× 192 1.3× 30 0.2× 106 0.9× 176 1.8× 8 493
Andrea K. Stoddard United States 11 154 0.6× 42 0.3× 141 1.0× 353 3.2× 56 0.6× 15 644
Jefferson Chan United States 4 127 0.5× 59 0.4× 106 0.7× 133 1.2× 29 0.3× 5 470
Jay P. Stasser United States 8 175 0.7× 55 0.4× 36 0.3× 182 1.6× 97 1.0× 8 469
Adam Pomorski Poland 11 131 0.5× 44 0.3× 50 0.3× 145 1.3× 62 0.6× 21 347

Countries citing papers authored by Lawrence W. Gray

Since Specialization
Citations

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

Fields of papers citing papers by Lawrence W. Gray

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lawrence W. Gray. 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 Lawrence W. Gray. The network helps show where Lawrence W. Gray may publish in the future.

Co-authorship network of co-authors of Lawrence W. Gray

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

All Works

9 of 9 papers shown
1.
Gray, Lawrence W., et al.. (2015). Using membrane composition to fine-tune the pKa of an optical liposome pH sensor. Journal of Materials Chemistry C. 4(14). 2925–2930. 6 indexed citations
2.
Gray, Lawrence W., Fangyu Peng, Shannon A. Molloy, et al.. (2012). Urinary Copper Elevation in a Mouse Model of Wilson's Disease Is a Regulated Process to Specifically Decrease the Hepatic Copper Load. PLoS ONE. 7(6). e38327–e38327. 57 indexed citations
3.
Hirayama, Tasuku, Genevieve C. Van de Bittner, Lawrence W. Gray, Svetlana Lutsenko, & Christopher J. Chang. (2012). Near-infrared fluorescent sensor for in vivo copper imaging in a murine Wilson disease model. Proceedings of the National Academy of Sciences. 109(7). 2228–2233. 190 indexed citations
4.
Burkhead, Jason L., Lawrence W. Gray, & Svetlana Lutsenko. (2011). Systems biology approach to Wilson’s disease. BioMetals. 24(3). 455–466. 55 indexed citations
5.
Endo, Masayuki, Antoneta Radu, Lawrence W. Gray, et al.. (2011). Early gestational gene transfer with targeted ATP7B expression in the liver improves phenotype in a murine model of Wilson's disease. Gene Therapy. 19(11). 1085–1094. 28 indexed citations
6.
Ralle, Martina, Dominik Hüster, Stefan Vogt, et al.. (2010). Wilson Disease at a Single Cell Level. Journal of Biological Chemistry. 285(40). 30875–30883. 90 indexed citations
7.
Gray, Lawrence W., Theodros Z. Kidane, S. K. Akagi, et al.. (2008). Copper proteins and ferroxidases in human plasma and that of wild-type and ceruloplasmin knockout mice. Biochemical Journal. 419(1). 237–245. 29 indexed citations
8.
Solomon, David, et al.. (2005). Niemann‐Pick Type C Disease in Two Affected Sisters: Ocular Motor Recordings and Brain‐Stem Neuropathology. Annals of the New York Academy of Sciences. 1039(1). 436–445. 48 indexed citations
9.
Fingeret, Murray, et al.. (2002). HOW TO BECOME A DIPLOMATE IN DISEASE.. Optometry and Vision Science. 79(Supplement). 31–31. 1 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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