Michael G. Sehorn

2.2k total citations
33 papers, 1.8k citations indexed

About

Michael G. Sehorn is a scholar working on Molecular Biology, Cancer Research and Cell Biology. According to data from OpenAlex, Michael G. Sehorn has authored 33 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Molecular Biology, 6 papers in Cancer Research and 5 papers in Cell Biology. Recurrent topics in Michael G. Sehorn's work include DNA Repair Mechanisms (21 papers), CRISPR and Genetic Engineering (7 papers) and Carcinogens and Genotoxicity Assessment (6 papers). Michael G. Sehorn is often cited by papers focused on DNA Repair Mechanisms (21 papers), CRISPR and Genetic Engineering (7 papers) and Carcinogens and Genotoxicity Assessment (6 papers). Michael G. Sehorn collaborates with scholars based in United States, United Kingdom and France. Michael G. Sehorn's co-authors include Patrick Sung, Stephen Van Komen, Lumír Krejčí, Peter Chi, Stefán Sigurðsson, Wendy Bussen, Joseph San Filippo, William R. Marcotte, William A. Gaines and Vinzenz M. Unger and has published in prestigious journals such as Nature, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Michael G. Sehorn

31 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael G. Sehorn United States 19 1.7k 299 286 204 192 33 1.8k
Fabien Mongélard France 23 1.6k 1.0× 191 0.6× 197 0.7× 208 1.0× 304 1.6× 32 1.9k
Amber Ablack United States 13 605 0.4× 244 0.8× 182 0.6× 127 0.6× 103 0.5× 18 1.2k
Chengqi Lin China 21 2.7k 1.6× 197 0.7× 269 0.9× 241 1.2× 257 1.3× 44 3.1k
Allison Lange United States 9 1.1k 0.6× 166 0.6× 87 0.3× 99 0.5× 151 0.8× 11 1.4k
Alexandra Moreira Portugal 21 1.3k 0.7× 191 0.6× 116 0.4× 86 0.4× 66 0.3× 37 1.7k
Sarah Seifert Germany 12 1.4k 0.8× 106 0.4× 170 0.6× 63 0.3× 218 1.1× 21 2.0k
Junwei Chen China 19 548 0.3× 247 0.8× 175 0.6× 154 0.8× 74 0.4× 63 1.4k
Stephen A. Scaringe United States 17 3.4k 2.0× 108 0.4× 540 1.9× 109 0.5× 476 2.5× 23 3.7k
Tristan Tay United States 6 1.8k 1.1× 111 0.4× 128 0.4× 95 0.5× 328 1.7× 8 2.0k
Elaine Chiu New Zealand 8 1.3k 0.8× 184 0.6× 608 2.1× 64 0.3× 50 0.3× 11 1.5k

Countries citing papers authored by Michael G. Sehorn

Since Specialization
Citations

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

Fields of papers citing papers by Michael G. Sehorn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael G. Sehorn

This figure shows the co-authorship network connecting the top 25 collaborators of Michael G. Sehorn. A scholar is included among the top collaborators of Michael G. Sehorn 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 G. Sehorn. Michael G. Sehorn 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.
2.
Welter, Brenda H., Michael G. Sehorn, & Lesly A. Temesvari. (2017). Flow cytometric characterization of encystation in Entamoeba invadens. Molecular and Biochemical Parasitology. 218. 23–27. 6 indexed citations
3.
Turchick, Audrey, Deepti Sharma, Stephen H. Foulger, et al.. (2016). Characterization of the recombination activities of the Entamoeba histolytica Rad51 recombinase. Molecular and Biochemical Parasitology. 210(1-2). 71–84. 10 indexed citations
4.
Diehl, J. Nathaniel, et al.. (2016). The β-isoform of BCCIP promotes ADP release from the RAD51 presynaptic filament and enhances homologous DNA pairing. Nucleic Acids Research. 45(2). 711–725. 18 indexed citations
5.
Sharma, Deepti, et al.. (2015). Entamoeba histolytica Dmc1 Catalyzes Homologous DNA Pairing and Strand Exchange That Is Stimulated by Calcium and Hop2-Mnd1. PLoS ONE. 10(9). e0139399–e0139399. 10 indexed citations
6.
Daniele, Michael A., et al.. (2012). Substrate‐Baited Nanoparticles: A Catch and Release Strategy for Enzyme Recognition and Harvesting. Small. 8(13). 2083–2090. 8 indexed citations
7.
Sharma, Deepti, et al.. (2012). Role of the conserved lysine within the Walker A motif of human DMC1. DNA repair. 12(1). 53–62. 12 indexed citations
8.
Baldwin, William S., et al.. (2011). Selective Imaging and Killing of Cancer Cells with Protein‐Activated Near‐Infrared Fluorescing Nanoparticles. Macromolecular Bioscience. 11(7). 927–937. 27 indexed citations
9.
Sharma, Deepti, Akhilesh K. Singh, Wing‐Kit Leung, et al.. (2011). The budding yeast Mei5–Sae3 complex interacts with Rad51 and preferentially binds a DNA fork structure. DNA repair. 10(6). 586–594. 23 indexed citations
10.
Sehorn, Michael G., et al.. (2011). Visualization of Human Dmc1 Presynaptic Filaments. Methods in molecular biology. 745. 485–496.
11.
Busygina, Valeria, et al.. (2008). Hed1 regulates Rad51-mediated recombination via a novel mechanism. Genes & Development. 22(6). 786–795. 86 indexed citations
12.
Yu, Xiong, Robyn Roth, John E. Heuser, et al.. (2008). A comparative analysis of Dmc1 and Rad51 nucleoprotein filaments. Nucleic Acids Research. 36(12). 4057–4066. 90 indexed citations
13.
Seong, Changhyun, Michael G. Sehorn, Binwei Song, et al.. (2008). Molecular Anatomy of the Recombination Mediator Function of Saccharomyces cerevisiae Rad52. Journal of Biological Chemistry. 283(18). 12166–12174. 45 indexed citations
14.
Hu, Yiduo, Steven Raynard, Michael G. Sehorn, et al.. (2007). RECQL5/Recql5 helicase regulates homologous recombination and suppresses tumor formation via disruption of Rad51 presynaptic filaments. Genes & Development. 21(23). 3073–3084. 272 indexed citations
15.
Filippo, Joseph San, Peter Chi, Michael G. Sehorn, et al.. (2006). Recombination Mediator and Rad51 Targeting Activities of a Human BRCA2 Polypeptide. Journal of Biological Chemistry. 281(17). 11649–11657. 105 indexed citations
16.
Chi, Peter, Stephen Van Komen, Michael G. Sehorn, Stefán Sigurðsson, & Patrick Sung. (2006). Roles of ATP binding and ATP hydrolysis in human Rad51 recombinase function. DNA repair. 5(3). 381–391. 147 indexed citations
17.
Komen, Stephen Van, Margaret Macris, Michael G. Sehorn, & Patrick Sung. (2006). Purification and Assays of Saccharomyces cerevisiae Homologous Recombination Proteins. Methods in enzymology on CD-ROM/Methods in enzymology. 408. 445–463. 37 indexed citations
18.
Sehorn, Michael G., Stefán Sigurðsson, Wendy Bussen, Vinzenz M. Unger, & Patrick Sung. (2004). Human meiotic recombinase Dmc1 promotes ATP-dependent homologous DNA strand exchange. Nature. 429(6990). 433–437. 145 indexed citations
19.
Sehorn, Michael G. & Patrick Sung. (2004). Meiotic Recombination: An Affair of Two Recombinases. Cell Cycle. 3(11). 1375–1377. 20 indexed citations
20.
Buczynski, Greg, Sergey V. Slepenkov, Michael G. Sehorn, & Stephan N. Witt. (2001). Characterization of a Lidless Form of the Molecular Chaperone DnaK. Journal of Biological Chemistry. 276(29). 27231–27236. 71 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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