Devon F. Pendlebury

472 total citations
9 papers, 301 citations indexed

About

Devon F. Pendlebury is a scholar working on Molecular Biology, Physiology and Genetics. According to data from OpenAlex, Devon F. Pendlebury has authored 9 papers receiving a total of 301 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 4 papers in Physiology and 1 paper in Genetics. Recurrent topics in Devon F. Pendlebury's work include DNA Repair Mechanisms (4 papers), Telomeres, Telomerase, and Senescence (3 papers) and CRISPR and Genetic Engineering (2 papers). Devon F. Pendlebury is often cited by papers focused on DNA Repair Mechanisms (4 papers), Telomeres, Telomerase, and Senescence (3 papers) and CRISPR and Genetic Engineering (2 papers). Devon F. Pendlebury collaborates with scholars based in United States, Sweden and Japan. Devon F. Pendlebury's co-authors include Jayakrishnan Nandakumar, Eric M. Smith, Hiroki Shibuya, Evette S. Radisky, Yasuhiro Fujiwara, Alexandra Hockla, Ruiying Wang, Alexei S. Soares, Marat D. Kazanov and Kexin Zhang and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and Brain.

In The Last Decade

Devon F. Pendlebury

9 papers receiving 300 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Devon F. Pendlebury United States	7	178	119	38	33	30	9	301
Tina Wagner Germany	6	299 1.7×	172 1.4×	34 0.9×	26 0.8×	30 1.0×	7	400
Thijmen van Vliet Netherlands	5	130 0.7×	193 1.6×	47 1.2×	44 1.3×	43 1.4×	5	341
Marina Kolesnichenko Germany	12	212 1.2×	87 0.7×	83 2.2×	64 1.9×	29 1.0×	13	379
Penelope D. Ruiz United States	8	306 1.7×	101 0.8×	93 2.4×	28 0.8×	19 0.6×	10	404
Wendy M. McKimpson United States	7	261 1.5×	88 0.7×	108 2.8×	43 1.3×	18 0.6×	19	422
Damien Ythier France	8	297 1.7×	52 0.4×	44 1.2×	65 2.0×	11 0.4×	9	355
Laura J. Niedernhofer United States	5	352 2.0×	97 0.8×	57 1.5×	91 2.8×	31 1.0×	7	440
Andrea Schienke Germany	6	227 1.3×	238 2.0×	112 2.9×	42 1.3×	75 2.5×	9	460
Yael Morgenstern Israel	4	228 1.3×	76 0.6×	118 3.1×	60 1.8×	10 0.3×	9	364
Kelly E. Leon United States	10	191 1.1×	67 0.6×	47 1.2×	56 1.7×	9 0.3×	16	311

Countries citing papers authored by Devon F. Pendlebury

Since Specialization

Citations

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

Fields of papers citing papers by Devon F. Pendlebury

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Devon F. Pendlebury. 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 Devon F. Pendlebury. The network helps show where Devon F. Pendlebury may publish in the future.

Co-authorship network of co-authors of Devon F. Pendlebury

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

All Works

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9 of 9 papers shown

Vaibhav, Vineet, Niveda Sundararaman, Devon F. Pendlebury, et al.. (2024). Dysregulation of protein SUMOylation networks in Huntington’s disease R6/2 mouse striatum. Brain. 148(4). 1212–1227. 4 indexed citations

Zhang, Kexin, et al.. (2022). The TERB1 MYB domain suppresses telomere erosion in meiotic prophase I. Cell Reports. 38(4). 110289–110289. 7 indexed citations

Pendlebury, Devon F., et al.. (2021). Structure of a meiosis-specific complex central to BRCA2 localization at recombination sites. Nature Structural & Molecular Biology. 28(8). 671–680. 5 indexed citations

Zhang, Jingjing, Manickam Gurusaran, Yasuhiro Fujiwara, et al.. (2020). The BRCA2-MEILB2-BRME1 complex governs meiotic recombination and impairs the mitotic BRCA2-RAD51 function in cancer cells. Nature Communications. 11(1). 2055–2055. 41 indexed citations

Smith, Eric M., Devon F. Pendlebury, & Jayakrishnan Nandakumar. (2019). Structural biology of telomeres and telomerase. Cellular and Molecular Life Sciences. 77(1). 61–79. 144 indexed citations

Pendlebury, Devon F., Yasuhiro Fujiwara, Valerie M. Tesmer, et al.. (2017). Dissecting the telomere–inner nuclear membrane interface formed in meiosis. Nature Structural & Molecular Biology. 24(12). 1064–1072. 27 indexed citations

Wang, Ruiying, Devon F. Pendlebury, Itay Cohen, et al.. (2016). An Acrobatic Substrate Metamorphosis Reveals a Requirement for Substrate Conformational Dynamics in Trypsin Proteolysis. Journal of Biological Chemistry. 291(51). 26304–26319. 20 indexed citations

Mehner, Christine, Ann L. Oberg, Kimberly R. Kalli, et al.. (2015). Serine protease inhibitor Kazal type 1 (SPINK1) drives proliferation and anoikis resistance in a subset of ovarian cancers. Oncotarget. 6(34). 35737–35754. 23 indexed citations

Pendlebury, Devon F., Ruiying Wang, Alexandra Hockla, et al.. (2014). Sequence and Conformational Specificity in Substrate Recognition. Journal of Biological Chemistry. 289(47). 32783–32797. 30 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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