Melissa A. Gray

1.8k total citations · 1 hit paper
17 papers, 709 citations indexed

About

Melissa A. Gray is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging and Genetics. According to data from OpenAlex, Melissa A. Gray has authored 17 papers receiving a total of 709 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 5 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Genetics. Recurrent topics in Melissa A. Gray's work include Glycosylation and Glycoproteins Research (7 papers), Monoclonal and Polyclonal Antibodies Research (5 papers) and Virus-based gene therapy research (2 papers). Melissa A. Gray is often cited by papers focused on Glycosylation and Glycoproteins Research (7 papers), Monoclonal and Polyclonal Antibodies Research (5 papers) and Virus-based gene therapy research (2 papers). Melissa A. Gray collaborates with scholars based in United States, United Kingdom and Germany. Melissa A. Gray's co-authors include Carolyn R. Bertozzi, Stacy A. Malaker, Elliot C. Woods, Payton A. Weidenbacher, Natália Rodrigues Mantuano, Michal A. Stanczak, Johan F. A. Pijnenborg, Han Xiao, Heinz Läubli and Green Ahn and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Journal of Biological Chemistry.

In The Last Decade

Melissa A. Gray

16 papers receiving 705 citations

Hit Papers

Targeted glycan degradation potentiates the anticancer im... 2020 2026 2022 2024 2020 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Melissa A. Gray United States 9 569 203 181 150 138 17 709
Torben Heise Netherlands 12 534 0.9× 294 1.4× 194 1.1× 103 0.7× 85 0.6× 16 660
Caitlyn L. Miller United States 8 601 1.1× 224 1.1× 89 0.5× 265 1.8× 104 0.8× 9 824
Natascha Stergiou Germany 17 448 0.8× 252 1.2× 245 1.4× 94 0.6× 169 1.2× 28 685
Yueqing Xie China 17 556 1.0× 136 0.7× 43 0.2× 217 1.4× 226 1.6× 40 813
Detlef Grunow Germany 11 575 1.0× 95 0.5× 296 1.6× 82 0.5× 116 0.8× 18 667
Figen Beceren‐Braun Germany 8 336 0.6× 227 1.1× 105 0.6× 79 0.5× 46 0.3× 10 568
J. Michael Pierce United States 10 803 1.4× 229 1.1× 290 1.6× 55 0.4× 106 0.8× 12 927
George K. Ehrlich United States 9 347 0.6× 78 0.4× 92 0.5× 99 0.7× 220 1.6× 18 664
Haofei Hong China 14 286 0.5× 106 0.5× 50 0.3× 95 0.6× 170 1.2× 45 418
Melissa Wassink Netherlands 13 453 0.8× 435 2.1× 73 0.4× 184 1.2× 91 0.7× 16 828

Countries citing papers authored by Melissa A. Gray

Since Specialization
Citations

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

Fields of papers citing papers by Melissa A. Gray

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Melissa A. Gray

This figure shows the co-authorship network connecting the top 25 collaborators of Melissa A. Gray. A scholar is included among the top collaborators of Melissa A. 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 Melissa A. Gray. Melissa A. Gray 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.
Gainullin, Vladimir G., Violeta Beleva Guthrie, Chen Ji, et al.. (2024). Abstract A056: Performance of multi-biomarker class reflex testing in a prospectively-collected cohort. Clinical Cancer Research. 30(21_Supplement). A056–A056.
2.
Gainullin, Vladimir G., Hee Jung Hwang, Melissa A. Gray, et al.. (2024). Abstract LB100: Performance of a multi-analyte, multi-cancer early detection (MCED) blood test in a prospectively-collected cohort. Cancer Research. 84(7_Supplement). LB100–LB100. 5 indexed citations
3.
Szijj, Péter A., et al.. (2023). Chemical generation of checkpoint inhibitory T cell engagers for the treatment of cancer. Nature Chemistry. 15(11). 1636–1647. 22 indexed citations
4.
Hollander, Michael J., Stacy A. Malaker, Nicholas M. Riley, et al.. (2023). Mutational screens highlight glycosylation as a modulator of colony-stimulating factor 3 receptor (CSF3R) activity. Journal of Biological Chemistry. 299(6). 104755–104755. 2 indexed citations
5.
Gray, Melissa A., Zhengqiao Zhao, & Gail Rosen. (2022). How Scalable Are Clade-Specific Marker K-Mer Based Hash Methods for Metagenomic Taxonomic Classification?. SHILAP Revista de lepidopterología. 2. 1 indexed citations
6.
Wisnovsky, Simon, Leonhard Möckl, Stacy A. Malaker, et al.. (2021). Genome-wide CRISPR screens reveal a specific ligand for the glycan-binding immune checkpoint receptor Siglec-7. Proceedings of the National Academy of Sciences. 118(5). 89 indexed citations
7.
Schumann, Benjamin, Stacy A. Malaker, Simon Wisnovsky, et al.. (2020). Bump-and-Hole Engineering Identifies Specific Substrates of Glycosyltransferases in Living Cells. Molecular Cell. 78(5). 824–834.e15. 76 indexed citations
8.
Gray, Melissa A., Michal A. Stanczak, Natália Rodrigues Mantuano, et al.. (2020). Targeted glycan degradation potentiates the anticancer immune response in vivo. Nature Chemical Biology. 16(12). 1376–1384. 233 indexed citations breakdown →
9.
Wang, Shih‐Ting, Melissa A. Gray, Sunting Xuan, et al.. (2020). DNA origami protection and molecular interfacing through engineered sequence-defined peptoids. Proceedings of the National Academy of Sciences. 117(12). 6339–6348. 104 indexed citations
10.
Tsui, C. Kimberly, Robyn M. Barfield, Curt R. Fischer, et al.. (2019). CRISPR-Cas9 screens identify regulators of antibody–drug conjugate toxicity. Nature Chemical Biology. 15(10). 949–958. 54 indexed citations
11.
Bule, Pedro, E.V. Blagova, Liang Wu, et al.. (2019). Inverting family GH156 sialidases define an unusual catalytic motif for glycosidase action. Nature Communications. 10(1). 4816–4816. 15 indexed citations
12.
Nguyen, Nancy, et al.. (2019). The Pharmacy Student Population: Applications Received 2017-18, Degrees Conferred 2017-18, Fall 2018 Enrollments. American Journal of Pharmaceutical Education. 83(6). 7658–7658. 2 indexed citations
13.
Choi, Junwon, Suzanne B. P. E. Timmermans, Stacy A. Malaker, et al.. (2019). Engineering Orthogonal Polypeptide GalNAc-Transferase and UDP-Sugar Pairs. Journal of the American Chemical Society. 141(34). 13442–13453. 54 indexed citations
14.
Allawi, Hatim T., Maria Giakoumopoulos, Tamara Sander, et al.. (2017). Abstract 712: Detection of lung cancer by assay of novel methylated DNA markers in plasma. Cancer Research. 77(13_Supplement). 712–712. 5 indexed citations
15.
Gray, Melissa A., et al.. (2015). A Nanobody Activation Immunotherapeutic that Selectively Destroys HER2‐Positive Breast Cancer Cells. ChemBioChem. 17(2). 155–158. 41 indexed citations
16.
Lui, Irene, et al.. (2013). Mutagenesis modulates the uptake efficiency, cell-selectivity, and functional enzyme delivery of a protein transduction domain. Molecular BioSystems. 10(1). 18–23. 4 indexed citations
17.
Gray, Melissa A., et al.. (2012). A one-pot synthesis of micron-sized and nanoscale poly(N-acryloxysuccinimide-co-N-vinylpyrrolidone) particles. Tetrahedron Letters. 53(47). 6436–6438. 2 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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