Jonathan N. Wells

2.1k total citations · 1 hit paper
25 papers, 1.2k citations indexed

About

Jonathan N. Wells is a scholar working on Molecular Biology, Cell Biology and Plant Science. According to data from OpenAlex, Jonathan N. Wells has authored 25 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 6 papers in Cell Biology and 5 papers in Plant Science. Recurrent topics in Jonathan N. Wells's work include Protein Structure and Dynamics (6 papers), RNA and protein synthesis mechanisms (6 papers) and Microtubule and mitosis dynamics (5 papers). Jonathan N. Wells is often cited by papers focused on Protein Structure and Dynamics (6 papers), RNA and protein synthesis mechanisms (6 papers) and Microtubule and mitosis dynamics (5 papers). Jonathan N. Wells collaborates with scholars based in United States, United Kingdom and Italy. Jonathan N. Wells's co-authors include Cédric Feschotte, Joseph A. Marsh, L. Therese Bergendahl, John C. Gerhart, Brian A. Rowning, Carolyn A. Larabell, Mike Wu, Zuzana Štorchová, Randall T. Moon and Erik McShane and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Jonathan N. Wells

24 papers receiving 1.2k citations

Hit Papers

A Field Guide to Eukaryotic Transposable Elements 2020 2026 2022 2024 2020 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jonathan N. Wells United States 12 927 285 194 185 61 25 1.2k
Raman Nambudripad United States 5 1.1k 1.2× 204 0.7× 270 1.4× 130 0.7× 23 0.4× 5 1.4k
Tetsuro Kokubo Japan 30 2.6k 2.8× 244 0.9× 132 0.7× 363 2.0× 41 0.7× 69 2.9k
Michael S. Cosgrove United States 22 1.9k 2.1× 135 0.5× 69 0.4× 146 0.8× 50 0.8× 36 2.2k
Judith Sleeman United Kingdom 18 1.7k 1.9× 129 0.5× 240 1.2× 61 0.3× 116 1.9× 25 1.9k
Jonathan J. Ipsaro United States 16 812 0.9× 279 1.0× 86 0.4× 83 0.4× 18 0.3× 23 1.1k
C.H.S. Aylett United Kingdom 17 937 1.0× 82 0.3× 170 0.9× 174 0.9× 55 0.9× 26 1.2k
Andreas Mayer Germany 26 2.7k 2.9× 144 0.5× 141 0.7× 190 1.0× 32 0.5× 48 3.0k
Eden Fussner Canada 10 2.2k 2.4× 206 0.7× 225 1.2× 188 1.0× 20 0.3× 13 2.4k
Adam G. Larson United States 11 2.2k 2.4× 301 1.1× 506 2.6× 114 0.6× 19 0.3× 16 2.5k
Matt E. Oates United Kingdom 12 1.1k 1.2× 106 0.4× 91 0.5× 110 0.6× 58 1.0× 17 1.5k

Countries citing papers authored by Jonathan N. Wells

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan N. Wells

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jonathan N. Wells. 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 Jonathan N. Wells. The network helps show where Jonathan N. Wells may publish in the future.

Co-authorship network of co-authors of Jonathan N. Wells

This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan N. Wells. A scholar is included among the top collaborators of Jonathan N. Wells 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 Jonathan N. Wells. Jonathan N. Wells 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.
Chang, Ni‐Chen, et al.. (2025). Gag proteins encoded by endogenous retroviruses are required for zebrafish development. Proceedings of the National Academy of Sciences. 122(18). e2411446122–e2411446122. 4 indexed citations
2.
Gunasekara, Chathura, Taylor Zhang, Jonathan N. Wells, et al.. (2025). Mouse metastable epialleles are extremely rare. Nucleic Acids Research. 53(14).
3.
Wells, Jonathan N., et al.. (2023). Transposable elements drive the evolution of metazoan zinc finger genes. Genome Research. 33(8). 1325–1339. 22 indexed citations
4.
Bergendahl, L. Therese, et al.. (2019). The role of protein complexes in human genetic disease. Protein Science. 28(8). 1400–1411. 52 indexed citations
5.
Brennan, Christopher M., Laura Pontano Vaites, Jonathan N. Wells, et al.. (2019). Protein aggregation mediates stoichiometry of protein complexes in aneuploid cells. Genes & Development. 33(15-16). 1031–1047. 79 indexed citations
6.
Wells, Jonathan N., L. Therese Bergendahl, & Joseph A. Marsh. (2018). Computational Modelling of Protein Complex Structure and Assembly. Methods in molecular biology. 1764. 347–356. 2 indexed citations
7.
Wells, Jonathan N. & Joseph A. Marsh. (2018). A Graph-Based Approach for Detecting Sequence Homology in Highly Diverged Repeat Protein Families. Methods in molecular biology. 1851. 251–261. 1 indexed citations
8.
Pan, Joshua, Robin M. Meyers, Brittany C. Michel, et al.. (2018). Interrogation of Mammalian Protein Complex Structure, Function, and Membership Using Genome-Scale Fitness Screens. Cell Systems. 6(5). 555–568.e7. 92 indexed citations
9.
Wells, Jonathan N. & Joseph A. Marsh. (2018). Experimental Characterization of Protein Complex Structure, Dynamics, and Assembly. Methods in molecular biology. 1764. 3–27. 5 indexed citations
10.
Natan, Eviatar, Jonathan N. Wells, Sarah A. Teichmann, & Joseph A. Marsh. (2016). Regulation, evolution and consequences of cotranslational protein complex assembly. Current Opinion in Structural Biology. 42. 90–97. 54 indexed citations
11.
McShane, Erik, Celine Sin, Henrik Zauber, et al.. (2016). Kinetic Analysis of Protein Stability Reveals Age-Dependent Degradation. Cell. 167(3). 803–815.e21. 212 indexed citations
12.
Wells, Jonathan N., L. Therese Bergendahl, & Joseph A. Marsh. (2016). Operon Gene Order Is Optimized for Ordered Protein Complex Assembly. Cell Reports. 14(4). 679–685. 69 indexed citations
13.
Wells, Jonathan N.. (2014). Membrane Patterns Carry Ontogenetic Information that is Specified Independently of DNA. Biophysical Journal. 106(2). 596a–596a. 1 indexed citations
14.
Wells, Jonathan N.. (2011). Gene regulatory networks in embryos depend on pre-existing spatial coordinates. Developmental Biology. 356(1). 207–207. 1 indexed citations
15.
Wells, Jonathan N.. (2005). Do centrioles generate a polar ejection force?. PubMed. 98(1). 71–95. 2 indexed citations
16.
Wells, Jonathan N.. (2004). Using Intelligent Design Theory to Guide Scientific Research. 3 indexed citations
17.
Nelson, Paul A. & Jonathan N. Wells. (2003). Homology in Biology. Toxicology Mechanisms and Methods. 19(3). 202–8. 1 indexed citations
18.
Larabell, Carolyn A., Brian A. Rowning, Jonathan N. Wells, Mike Wu, & John C. Gerhart. (1996). Confocal microscopy analysis of living Xenopus eggs and the mechanism of cortical rotation. Development. 122(4). 1281–1289. 49 indexed citations
19.
Wells, Jonathan N., et al.. (1986). The acute effects of different energy beta-emitters on pig and mouse skin.. PubMed. 19. 47–51. 20 indexed citations
20.
Wells, Jonathan N.. (1985). Inertial force as a possible factor in mitosis. Biosystems. 17(4). 301–315. 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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