Gregory D. Gregory

852 total citations
9 papers, 674 citations indexed

About

Gregory D. Gregory is a scholar working on Molecular Biology, Immunology and Physiology. According to data from OpenAlex, Gregory D. Gregory has authored 9 papers receiving a total of 674 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 5 papers in Immunology and 4 papers in Physiology. Recurrent topics in Gregory D. Gregory's work include Mast cells and histamine (4 papers), Epigenetics and DNA Methylation (3 papers) and Cancer-related gene regulation (3 papers). Gregory D. Gregory is often cited by papers focused on Mast cells and histamine (4 papers), Epigenetics and DNA Methylation (3 papers) and Cancer-related gene regulation (3 papers). Gregory D. Gregory collaborates with scholars based in United States and Israel. Gregory D. Gregory's co-authors include Gerd A. Blobel, Christopher R. Vakoc, Melissa A. Brown, Shetal Patel, Eli Canaani, Tanya Rozovskaia, Tatsuya Nakamura, Wulan Deng, Ying Zhang and Ross C. Hardison and has published in prestigious journals such as The EMBO Journal, Blood and The Journal of Immunology.

In The Last Decade

Gregory D. Gregory

9 papers receiving 667 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gregory D. Gregory United States 8 413 194 118 83 74 9 674
Stuart Ellison United Kingdom 14 250 0.6× 112 0.6× 116 1.0× 47 0.6× 147 2.0× 27 552
Jun Ohta Japan 10 427 1.0× 110 0.6× 123 1.0× 83 1.0× 82 1.1× 23 638
Erica Bresciani United States 13 308 0.7× 100 0.5× 134 1.1× 68 0.8× 54 0.7× 28 569
Claire Dobson United Kingdom 10 349 0.8× 100 0.5× 159 1.3× 40 0.5× 42 0.6× 14 513
Mark D. Ware Canada 11 385 0.9× 138 0.7× 40 0.3× 30 0.4× 36 0.5× 15 583
Karin Soller Germany 12 306 0.7× 211 1.1× 323 2.7× 92 1.1× 80 1.1× 19 619
Vanessa M. Scarfone United States 10 215 0.5× 123 0.6× 109 0.9× 53 0.6× 20 0.3× 16 475
Jiajing Qiu United States 13 443 1.1× 138 0.7× 319 2.7× 156 1.9× 77 1.0× 23 722
Ashley C. Kramer United States 13 490 1.2× 63 0.3× 131 1.1× 53 0.6× 23 0.3× 28 653
Elizabeth J. Heller United States 6 541 1.3× 253 1.3× 147 1.2× 41 0.5× 23 0.3× 6 856

Countries citing papers authored by Gregory D. Gregory

Since Specialization
Citations

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

Fields of papers citing papers by Gregory D. Gregory

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gregory D. Gregory. 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 Gregory D. Gregory. The network helps show where Gregory D. Gregory may publish in the future.

Co-authorship network of co-authors of Gregory D. Gregory

This figure shows the co-authorship network connecting the top 25 collaborators of Gregory D. Gregory. A scholar is included among the top collaborators of Gregory D. Gregory 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 Gregory D. Gregory. Gregory D. Gregory 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.
Rao, Kavitha N., et al.. (2013). Ikaros limits basophil development by suppressing C/EBP-α expression. Blood. 122(15). 2572–2581. 24 indexed citations
2.
Gregory, Gregory D., Annarita Miccio, Alexey Bersenev, et al.. (2010). FOG1 requires NuRD to promote hematopoiesis and maintain lineage fidelity within the megakaryocytic-erythroid compartment. Blood. 115(11). 2156–2166. 46 indexed citations
3.
Gregory, Gregory D., et al.. (2009). Cutting Edge: Ikaros Is a Regulator of Th2 Cell Differentiation. The Journal of Immunology. 182(2). 741–745. 56 indexed citations
4.
Miccio, Annarita, Yuhuan Wang, Hong Wei, et al.. (2009). NuRD mediates activating and repressive functions of GATA‐1 and FOG‐1 during blood development. The EMBO Journal. 29(2). 442–456. 127 indexed citations
5.
Gregory, Gregory D., Annarita Miccio, Alexey Bersenev, et al.. (2009). FOG-1 Requires NuRD to Promote Hematopoiesis and Maintain Lineage Fidelity within the Megakaryocytic–Erythroid Compartment.. Blood. 114(22). 702–702. 1 indexed citations
6.
Tripic, Tamara, Wulan Deng, Yong Cheng, et al.. (2008). SCL and associated proteins distinguish active from repressive GATA transcription factor complexes. Blood. 113(10). 2191–2201. 141 indexed citations
7.
Gregory, Gregory D., Christopher R. Vakoc, Tanya Rozovskaia, et al.. (2007). Mammalian ASH1L Is a Histone Methyltransferase That Occupies the Transcribed Region of Active Genes. Molecular and Cellular Biology. 27(24). 8466–8479. 175 indexed citations
8.
Gregory, Gregory D., Michaela Robbie‐Ryan, Virginia H. Secor, Joseph J. Sabatino, & Melissa A. Brown. (2005). Mast cells are required for optimal autoreactive T cell responses in a murine model of multiple sclerosis. European Journal of Immunology. 35(12). 3478–3486. 72 indexed citations
9.
Gregory, Gregory D. & Melissa A. Brown. (2005). Mast Cells in Allergy and Autoimmunity: Implications for Adaptive Immunity. Humana Press eBooks. 315. 35–50. 32 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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