Michael J. Gray

8.0k total citations
112 papers, 6.2k citations indexed

About

Michael J. Gray is a scholar working on Molecular Biology, Oncology and Epidemiology. According to data from OpenAlex, Michael J. Gray has authored 112 papers receiving a total of 6.2k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Molecular Biology, 24 papers in Oncology and 21 papers in Epidemiology. Recurrent topics in Michael J. Gray's work include Coagulation, Bradykinin, Polyphosphates, and Angioedema (15 papers), Angiogenesis and VEGF in Cancer (13 papers) and Enzyme function and inhibition (10 papers). Michael J. Gray is often cited by papers focused on Coagulation, Bradykinin, Polyphosphates, and Angioedema (15 papers), Angiogenesis and VEGF in Cancer (13 papers) and Enzyme function and inhibition (10 papers). Michael J. Gray collaborates with scholars based in United States, Canada and Germany. Michael J. Gray's co-authors include Ursula Jakob, Lee M. Ellis, Fan Fan, Nikolaos A. Dallas, George Van Buren, Ling Xia, Sherry J. Lim, Shaija Samuel, Ray Somcio and Kathryn J. Boor and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Michael J. Gray

109 papers receiving 6.1k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Michael J. Gray 3.0k 1.6k 887 832 752 112 6.2k
Gerrit Jansen 5.1k 1.7× 3.9k 2.4× 957 1.1× 769 0.9× 632 0.8× 330 11.4k
Hideaki Ito 2.2k 0.7× 686 0.4× 614 0.7× 429 0.5× 1.3k 1.7× 169 5.0k
Yutaka Kohgo 2.9k 1.0× 1.4k 0.9× 1.0k 1.1× 575 0.7× 1.5k 2.0× 243 7.4k
Marc Bracke 5.0k 1.7× 2.6k 1.6× 1.8k 2.1× 898 1.1× 271 0.4× 188 8.9k
John M. Luk 5.4k 1.8× 1.5k 0.9× 1.8k 2.1× 901 1.1× 1.4k 1.8× 187 9.8k
Janko Kos 4.3k 1.5× 2.1k 1.3× 3.6k 4.0× 1.3k 1.6× 535 0.7× 314 10.9k
Ping‐Kun Zhou 4.6k 1.5× 1.4k 0.8× 1.3k 1.5× 865 1.0× 692 0.9× 286 7.7k
Eugenio Scanziani 2.2k 0.7× 1.2k 0.7× 676 0.8× 1.3k 1.5× 385 0.5× 210 6.0k
Leili Aghebati‐Maleki 2.4k 0.8× 954 0.6× 641 0.7× 1.9k 2.2× 276 0.4× 219 6.4k
Shrikant Anant 5.3k 1.8× 2.2k 1.4× 1.5k 1.7× 1.5k 1.8× 742 1.0× 212 9.3k

Countries citing papers authored by Michael J. Gray

Since Specialization
Citations

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

Fields of papers citing papers by Michael J. Gray

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael J. Gray

This figure shows the co-authorship network connecting the top 25 collaborators of Michael J. Gray. A scholar is included among the top collaborators of Michael J. 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 Michael J. Gray. Michael J. Gray 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.
Denoncourt, Alix, A. D. Simms, Adam D. Rudner, et al.. (2025). Identification of polyphosphate-binding proteins in Escherichia coli uncovers targets involved in translation control and ribosome biogenesis. mBio. 16(8). e0050025–e0050025. 1 indexed citations
2.
Meza‐Perez, Selene, Aarón Silva-Sánchez, Casey D. Morrow, et al.. (2024). Proteobacteria impair anti-tumor immunity in the omentum by consuming arginine. Cell Host & Microbe. 32(7). 1177–1191.e7. 17 indexed citations
3.
Gray, Michael J.. (2024). The role of metals in hypothiocyanite resistance in Escherichia coli. Journal of Bacteriology. 206(8). e0009824–e0009824. 1 indexed citations
4.
Gray, Michael J., et al.. (2024). C-terminal Poly-histidine Tags Alter Escherichia coli Polyphosphate Kinase Activity and Susceptibility to Inhibition. Journal of Molecular Biology. 436(16). 168651–168651. 2 indexed citations
5.
Gray, Michael J., et al.. (2023). Hypothiocyanite and host–microbe interactions. Molecular Microbiology. 119(3). 302–311. 9 indexed citations
6.
Ulrich, Kathrin, et al.. (2022). Escherichia coli RclA is a highly active hypothiocyanite reductase. Proceedings of the National Academy of Sciences. 119(30). e2119368119–e2119368119. 16 indexed citations
7.
Gray, Michael J., et al.. (2022). The role of nitrogen-responsive regulators in controlling inorganic polyphosphate synthesis in Escherichia coli. Microbiology. 168(4). 7 indexed citations
8.
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10.
Königstorfer, Andreas, et al.. (2020). Induction of the reactive chlorine-responsive transcription factor RclR in Escherichia coli following ingestion by neutrophils. Pathogens and Disease. 79(1). 11 indexed citations
11.
Singer, Jeffrey R., Carlene L. Zindl, Daniel J. Silberger, et al.. (2019). Preventing dysbiosis of the neonatal mouse intestinal microbiome protects against late-onset sepsis. Nature Medicine. 25(11). 1772–1782. 107 indexed citations
12.
Freimark, Bruce, Jian Gong, Dan Ye, et al.. (2016). Antibody-Mediated Phosphatidylserine Blockade Enhances the Antitumor Responses to CTLA-4 and PD-1 Antibodies in Melanoma. Cancer Immunology Research. 4(6). 531–540. 21 indexed citations
13.
Gray, Michael J., Yan Li, Lars I. Leichert, Zhaohui Xu, & Ursula Jakob. (2015). Does the Transcription Factor NemR Use a Regulatory Sulfenamide Bond to Sense Bleach?. Antioxidants and Redox Signaling. 23(9). 747–754. 44 indexed citations
14.
Lin, Yvonne G., Anand Immaneni, William M. Merritt, et al.. (2008). Targeting Aurora Kinase with MK-0457 Inhibits Ovarian Cancer Growth. Clinical Cancer Research. 14(17). 5437–5446. 51 indexed citations
15.
Buren, George Van, Michael J. Gray, Nikolaos A. Dallas, et al.. (2007). A monoclonal antibody targeting the human urokinase plasminogen activator receptor (uPAR) combined with bevacizumab inhibits the growth of colon cancer metastases in the liver: Differential effects mediated by tumor burden.. Molecular Cancer Therapeutics. 6. 2 indexed citations
16.
Treviño, José G., Michael J. Gray, Justin M. Summy, et al.. (2006). Interleukin-8 is regulated by a Src/STAT3 pathway in pancreatic adenocarcinoma cells that is NF-κB independent. Cancer Research. 66. 1135–1135. 1 indexed citations
17.
Leung, Kitty, Emily Louca, Michael J. Gray, Graham Tipples, & Allan L. Coates. (2005). Use of the Next Generation Pharmaceutical Impactor for Particle Size Distribution Measurements of Live Viral Aerosol Vaccines. Journal of Aerosol Medicine. 18(4). 414–426. 8 indexed citations
18.
Wey, Jane, Michael J. Gray, Fan Fan, et al.. (2004). Neuropilin-1, a novel vascular endothelial growth factor receptor, promotes chemoresistance in pancreatic cancer cell lines. Cancer Research. 64. 1127–1127. 1 indexed citations
19.
Gray, Michael J., et al.. (2004). Detection of Viable Mycobacterium avium Subsp. Paratuberculosis Using Luciferase Reporter Systems. Foodborne Pathogens and Disease. 1(4). 258–266. 14 indexed citations
20.
Gray, Michael J., et al.. (2000). Characterization of Chocolate Milk Spoilage Patterns. Journal of Food Protection. 63(4). 516–521. 26 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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