Kyle T. Powers

484 total citations
13 papers, 339 citations indexed

About

Kyle T. Powers is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Kyle T. Powers has authored 13 papers receiving a total of 339 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 4 papers in Genetics and 2 papers in Cancer Research. Recurrent topics in Kyle T. Powers's work include DNA Repair Mechanisms (7 papers), Bacterial Genetics and Biotechnology (4 papers) and RNA and protein synthesis mechanisms (4 papers). Kyle T. Powers is often cited by papers focused on DNA Repair Mechanisms (7 papers), Bacterial Genetics and Biotechnology (4 papers) and RNA and protein synthesis mechanisms (4 papers). Kyle T. Powers collaborates with scholars based in United States, United Kingdom and Germany. Kyle T. Powers's co-authors include M. Todd Washington, Christiane Schaffitzel, Kevin R. Smith, Yaxu Wu, Hong Wang, Peter C. Charles, James E. Ferguson, Cam Patterson, Christine M. Kondratick and Elizabeth M. Boehm and has published in prestigious journals such as Nucleic Acids Research, Journal of Biological Chemistry and PLoS ONE.

In The Last Decade

Kyle T. Powers

13 papers receiving 336 citations

Peers

Kyle T. Powers
Yiyong Zhou United States
Zeyun Mi China
Lahcen Jaafar United States
Lakshmi Gopinathan United States
Sofia Origanti United States
Yiyong Zhou United States
Kyle T. Powers
Citations per year, relative to Kyle T. Powers Kyle T. Powers (= 1×) peers Yiyong Zhou

Countries citing papers authored by Kyle T. Powers

Since Specialization
Citations

This map shows the geographic impact of Kyle T. Powers'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 Kyle T. Powers with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kyle T. Powers more than expected).

Fields of papers citing papers by Kyle T. Powers

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kyle T. Powers. 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 Kyle T. Powers. The network helps show where Kyle T. Powers may publish in the future.

Co-authorship network of co-authors of Kyle T. Powers

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

All Works

13 of 13 papers shown
1.
Toelzer, Christine, Kapil Gupta, Sathish K.N. Yadav, et al.. (2022). The free fatty acid–binding pocket is a conserved hallmark in pathogenic β-coronavirus spike proteins from SARS-CoV to Omicron. Science Advances. 8(47). eadc9179–eadc9179. 28 indexed citations
3.
Powers, Kyle T., Sathish K.N. Yadav, Beate Amthor, et al.. (2021). Blasticidin S inhibits mammalian translation and enhances production of protein encoded by nonsense mRNA. Nucleic Acids Research. 49(13). 7665–7679. 11 indexed citations
4.
Powers, Kyle T., et al.. (2020). New insights into no-go, non-stop and nonsense-mediated mRNA decay complexes. Current Opinion in Structural Biology. 65. 110–118. 51 indexed citations
5.
Powers, Kyle T., Melissa Gildenberg, & M. Todd Washington. (2019). Modeling Conformationally Flexible Proteins With X-ray Scattering and Molecular Simulations. Computational and Structural Biotechnology Journal. 17. 570–578. 9 indexed citations
6.
Powers, Kyle T. & M. Todd Washington. (2018). Eukaryotic translesion synthesis: Choosing the right tool for the job. DNA repair. 71. 127–134. 42 indexed citations
7.
Powers, Kyle T., et al.. (2018). Conformational Flexibility of Ubiquitin-Modified and SUMO-Modified PCNA Shown by Full-Ensemble Hybrid Methods. Journal of Molecular Biology. 430(24). 5294–5303. 5 indexed citations
8.
Powers, Kyle T., Adrian H. Elcock, & M. Todd Washington. (2018). The C-terminal region of translesion synthesis DNA polymerase η is partially unstructured and has high conformational flexibility. Nucleic Acids Research. 46(4). 2107–2120. 15 indexed citations
9.
Powers, Kyle T. & M. Todd Washington. (2017). Analyzing the Catalytic Activities and Interactions of Eukaryotic Translesion Synthesis Polymerases. Methods in enzymology on CD-ROM/Methods in enzymology. 592. 329–356. 11 indexed citations
10.
Boehm, Elizabeth M., Kyle T. Powers, Christine M. Kondratick, et al.. (2016). The Proliferating Cell Nuclear Antigen (PCNA)-interacting Protein (PIP) Motif of DNA Polymerase η Mediates Its Interaction with the C-terminal Domain of Rev1. Journal of Biological Chemistry. 291(16). 8735–8744. 42 indexed citations
11.
Kondratick, Christine M., et al.. (2016). Identification of New Mutations at the PCNA Subunit Interface that Block Translesion Synthesis. PLoS ONE. 11(6). e0157023–e0157023. 7 indexed citations
12.
Powers, Kyle T., et al.. (2015). Dead-End Elimination with a Polarizable Force Field Repacks PCNA Structures. Biophysical Journal. 109(4). 816–826. 19 indexed citations
13.
Ferguson, James E., Yaxu Wu, Kevin R. Smith, et al.. (2007). ASB4 Is a Hydroxylation Substrate of FIH and Promotes Vascular Differentiation via an Oxygen-Dependent Mechanism. Molecular and Cellular Biology. 27(18). 6407–6419. 87 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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