Glenna Foight

687 total citations · 1 hit paper
10 papers, 388 citations indexed

About

Glenna Foight is a scholar working on Molecular Biology, Immunology and Oncology. According to data from OpenAlex, Glenna Foight has authored 10 papers receiving a total of 388 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 4 papers in Immunology and 3 papers in Oncology. Recurrent topics in Glenna Foight's work include interferon and immune responses (3 papers), Cell death mechanisms and regulation (3 papers) and CRISPR and Genetic Engineering (2 papers). Glenna Foight is often cited by papers focused on interferon and immune responses (3 papers), Cell death mechanisms and regulation (3 papers) and CRISPR and Genetic Engineering (2 papers). Glenna Foight collaborates with scholars based in United States, Denmark and South Korea. Glenna Foight's co-authors include Amy E. Keating, William Sheffler, David Baker, Binchen Mao, Po‐Ssu Huang, Sergey Ovchinnikov, Banumathi Sankaran, Barry Stoddard, Matthew J. Bick and Enrique Marcos and has published in prestigious journals such as Nature, Journal of the American Chemical Society and Nature Biotechnology.

In The Last Decade

Glenna Foight

10 papers receiving 385 citations

Hit Papers

De novo design of a fluorescence-activating β-barrel 2018 2026 2020 2023 2018 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
Glenna Foight United States 7 311 66 42 37 31 10 388
Kimberly J. Zanotti United States 10 367 1.2× 40 0.6× 21 0.5× 73 2.0× 36 1.2× 12 457
Stefan Reinke Germany 10 328 1.1× 36 0.5× 108 2.6× 77 2.1× 31 1.0× 13 463
Luke Vistain United States 9 245 0.8× 48 0.7× 26 0.6× 16 0.4× 32 1.0× 11 396
Xinyong Ma China 8 173 0.6× 59 0.9× 35 0.8× 52 1.4× 48 1.5× 10 332
Lena Voith von Voithenberg Germany 12 364 1.2× 42 0.6× 27 0.6× 12 0.3× 51 1.6× 19 517
Tobias Vöpel Germany 10 237 0.8× 63 1.0× 15 0.4× 24 0.6× 28 0.9× 18 354
Gayle Buller United States 5 214 0.7× 65 1.0× 40 1.0× 34 0.9× 80 2.6× 9 361
Galen Dods United States 6 430 1.4× 33 0.5× 32 0.8× 11 0.3× 28 0.9× 8 500
Marion Fillies Germany 6 312 1.0× 14 0.2× 65 1.5× 38 1.0× 39 1.3× 7 388
Mariya I. Meschaninova Russia 16 715 2.3× 34 0.5× 18 0.4× 19 0.5× 42 1.4× 69 792

Countries citing papers authored by Glenna Foight

Since Specialization
Citations

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

Fields of papers citing papers by Glenna Foight

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Glenna Foight

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

All Works

10 of 10 papers shown
1.
Foight, Glenna, et al.. (2023). Synthetic transcription factor engineering for cell and gene therapy. Trends in biotechnology. 42(4). 449–463. 13 indexed citations
2.
Foight, Glenna, Zhizhi Wang, Per Greisen, et al.. (2019). Multi-input chemical control of protein dimerization for programming graded cellular responses. Nature Biotechnology. 37(10). 1209–1216. 57 indexed citations
3.
Foight, Glenna, et al.. (2019). A Chemically Disrupted Proximity System for Controlling Dynamic Cellular Processes. Journal of the American Chemical Society. 141(8). 3352–3355. 15 indexed citations
4.
Dou, Jiayi, Anastassia A. Vorobieva, William Sheffler, et al.. (2018). De novo design of a fluorescence-activating β-barrel. Nature. 561(7724). 485–491. 249 indexed citations breakdown →
5.
Foight, Glenna, et al.. (2017). Enriching Peptide Libraries for Binding Affinity and Specificity Through Computationally Directed Library Design. Methods in molecular biology. 1561. 213–232. 6 indexed citations
6.
Chan, Gary C., et al.. (2016). Selective peptide inhibitors of antiapoptotic cellular and viral Bcl-2 proteins lead to cytochrome c release during latent Kaposi’s sarcoma-associated herpesvirus infection. DSpace@MIT (Massachusetts Institute of Technology). 3 indexed citations
7.
Foight, Glenna & Amy E. Keating. (2016). Comparison of the peptide binding preferences of three closely related TRAF paralogs: TRAF2, TRAF3, and TRAF5. Protein Science. 25(7). 1273–1289. 22 indexed citations
8.
Foight, Glenna & Amy E. Keating. (2015). Locating Herpesvirus Bcl-2 Homologs in the Specificity Landscape of Anti-Apoptotic Bcl-2 Proteins. Journal of Molecular Biology. 427(15). 2468–2490. 15 indexed citations
10.
Hogdal, Leah J., Brenda Chyla, Evelyn McKeegan, et al.. (2015). Abstract 2834: BH3 profiling predicts clinical response in a phase II clinical trial of ABT-199 (GDC-0199) in acute myeloid leukemia. Cancer Research. 75(15_Supplement). 2834–2834. 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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