Don B. Arnold

2.4k total citations
35 papers, 1.7k citations indexed

About

Don B. Arnold is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Cell Biology. According to data from OpenAlex, Don B. Arnold has authored 35 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Cellular and Molecular Neuroscience, 16 papers in Molecular Biology and 15 papers in Cell Biology. Recurrent topics in Don B. Arnold's work include Neuroscience and Neuropharmacology Research (19 papers), Neural dynamics and brain function (8 papers) and Cellular transport and secretion (8 papers). Don B. Arnold is often cited by papers focused on Neuroscience and Neuropharmacology Research (19 papers), Neural dynamics and brain function (8 papers) and Cellular transport and secretion (8 papers). Don B. Arnold collaborates with scholars based in United States, Canada and Germany. Don B. Arnold's co-authors include Tommy L. Lewis, Jacqueline F. Rivera, Tianyi Mao, Emily R. Liman, Thomas J. Wandless, Karel Svoboda, Richard W. Roberts, Garrett G. Gross, Ralf Langen and Balyn W. Zaro and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Neuron.

In The Last Decade

Don B. Arnold

33 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Don B. Arnold United States	21	924	790	519	163	149	35	1.7k
Lydia Danglot France	26	1.3k 1.4×	601 0.8×	625 1.2×	260 1.6×	89 0.6×	52	2.4k
Kira E. Poskanzer United States	22	743 0.8×	1.4k 1.7×	491 0.9×	120 0.7×	547 3.7×	28	2.1k
Kiwamu Takemoto Japan	16	905 1.0×	413 0.5×	256 0.5×	143 0.9×	125 0.8×	29	1.5k
Susanne tom Dieck Germany	31	2.6k 2.9×	1.6k 2.1×	944 1.8×	89 0.5×	290 1.9×	47	3.6k
Kimberly Gerrow Canada	11	779 0.8×	875 1.1×	372 0.7×	36 0.2×	189 1.3×	13	1.5k
Cyril Hanus Germany	18	1.0k 1.1×	633 0.8×	550 1.1×	48 0.3×	74 0.5×	23	1.5k
Jai‐Yoon Sul United States	23	1.2k 1.3×	596 0.8×	147 0.3×	84 0.5×	99 0.7×	38	1.8k
Alaa El‐Husseini Canada	20	1.7k 1.8×	1.5k 1.9×	721 1.4×	42 0.3×	265 1.8×	25	2.8k
Sergei Smirnov Finland	18	791 0.9×	912 1.2×	233 0.4×	40 0.2×	286 1.9×	24	1.6k
Anne B. Theibert United States	30	1.7k 1.9×	508 0.6×	1.3k 2.6×	75 0.5×	109 0.7×	43	2.7k

Countries citing papers authored by Don B. Arnold

Since Specialization

Citations

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

Fields of papers citing papers by Don B. Arnold

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Don B. Arnold. 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 Don B. Arnold. The network helps show where Don B. Arnold may publish in the future.

Co-authorship network of co-authors of Don B. Arnold

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Ährlund‐Richter, Sofie, et al.. (2025). Distinct roles of prefrontal subregion feedback to the primary visual cortex across behavioral states. Neuron. 114(3). 492–506.e6.

Rivera, Jacqueline F., Mingli Qin, Can Tao, et al.. (2025). ATLAS: a rationally designed anterograde transsynaptic tracer. Nature Methods. 22(5). 1101–1111. 1 indexed citations

Davenport, Christopher M., C R Taylor, Ming‐Chi Tsai, et al.. (2020). Relocation of an Extrasynaptic GABAA Receptor to Inhibitory Synapses Freezes Excitatory Synaptic Strength and Preserves Memory. Neuron. 109(1). 123–134.e4. 60 indexed citations

Wolfe, Aaron, Don B. Arnold, & Xiaojiang S. Chen. (2019). Comparison of RNA Editing Activity of APOBEC1-A1CF and APOBEC1-RBM47 Complexes Reconstituted in HEK293T Cells. Journal of Molecular Biology. 431(7). 1506–1517. 17 indexed citations

Cook, Sarah G., et al.. (2019). Simultaneous Live Imaging of Multiple Endogenous Proteins Reveals a Mechanism for Alzheimer’s-Related Plasticity Impairment. Cell Reports. 27(3). 658–665.e4. 37 indexed citations

Kannan, Madhuvanthi, Garrett G. Gross, Don B. Arnold, & Michael J. Higley. (2016). Visual Deprivation During the Critical Period Enhances Layer 2/3 GABAergic Inhibition in Mouse V1. Journal of Neuroscience. 36(22). 5914–5919. 30 indexed citations

Evenson, William E., Garrett G. Gross, Farzad Jalali‐Yazdi, et al.. (2016). RasIns: Genetically Encoded Intrabodies of Activated Ras Proteins. Journal of Molecular Biology. 429(4). 562–573. 29 indexed citations

Gross, Garrett G., Christoph Straub, Jimena Pérez-Sánchez, et al.. (2016). An E3-ligase-based method for ablating inhibitory synapses. Nature Methods. 13(8). 673–678. 34 indexed citations

Marotta, Nicholas P., Yu Lin, Mark R. Ambroso, et al.. (2015). O-GlcNAc modification blocks the aggregation and toxicity of the protein α-synuclein associated with Parkinson's disease. Nature Chemistry. 7(11). 913–920. 226 indexed citations

10.

Arnold, Don B., et al.. (2014). Actin and Myosin-Dependent Localization of mRNA to Dendrites. PLoS ONE. 9(3). e92349–e92349. 27 indexed citations

11.

Roberts, Richard W., et al.. (2013). Recombinant Probes Reveal Dynamic Localization of CaMKIIα within Somata of Cortical Neurons. Journal of Neuroscience. 33(36). 14579–14590. 20 indexed citations

12.

Gross, Garrett G., Jason A. Junge, Hyung-Bae Kwon, et al.. (2013). Recombinant Probes for Visualizing Endogenous Synaptic Proteins in Living Neurons. Neuron. 78(6). 971–985. 228 indexed citations

13.

Arnold, Don B. & Gianluca Gallo. (2013). Structure meets function: actin filaments and myosin motors in the axon. Journal of Neurochemistry. 129(2). 213–220. 33 indexed citations

14.

Xu, Min, et al.. (2012). Differential Trafficking of Transport Vesicles Contributes to the Localization of Dendritic Proteins. Cell Reports. 2(1). 89–100. 93 indexed citations

15.

Lewis, Tommy L., Tianyi Mao, & Don B. Arnold. (2011). A Role for Myosin VI in the Localization of Axonal Proteins. PLoS Biology. 9(3). e1001021–e1001021. 54 indexed citations

16.

Lewis, Tommy L., Tianyi Mao, Karel Svoboda, & Don B. Arnold. (2009). Myosin-dependent targeting of transmembrane proteins to neuronal dendrites. Nature Neuroscience. 12(5). 568–576. 147 indexed citations

17.

Rivera, Jacqueline F., et al.. (2007). The role of Kif5B in axonal localization of Kv1 K⁺ channels. European Journal of Neuroscience. 25(1). 136–146. 44 indexed citations

18.

Arnold, Don B.. (2006). Polarized targeting of ion channels in neurons. Pflügers Archiv - European Journal of Physiology. 453(6). 763–769. 16 indexed citations

19.

Rivera, Jacqueline F., et al.. (2005). The T1 domain of Kv1.3 mediates intracellular targeting to axons. European Journal of Neuroscience. 22(8). 1853–1862. 27 indexed citations

20.

Rivera, Jacqueline F., et al.. (2005). A Role for Kif17 in Transport of Kv4.2. Journal of Biological Chemistry. 281(1). 365–373. 86 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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