Alison D. Axtman

1.2k total citations
42 papers, 440 citations indexed

About

Alison D. Axtman is a scholar working on Molecular Biology, Oncology and Cell Biology. According to data from OpenAlex, Alison D. Axtman has authored 42 papers receiving a total of 440 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Molecular Biology, 9 papers in Oncology and 8 papers in Cell Biology. Recurrent topics in Alison D. Axtman's work include Computational Drug Discovery Methods (7 papers), Microtubule and mitosis dynamics (6 papers) and Protein Kinase Regulation and GTPase Signaling (5 papers). Alison D. Axtman is often cited by papers focused on Computational Drug Discovery Methods (7 papers), Microtubule and mitosis dynamics (6 papers) and Protein Kinase Regulation and GTPase Signaling (5 papers). Alison D. Axtman collaborates with scholars based in United States, Canada and United Kingdom. Alison D. Axtman's co-authors include David H. Drewry, Carrow I. Wells, Frances Potjewyd, Julie E. Pickett, Andreas Krämer, Jeffery L. Smith, Timothy M. Willson, David W. Litchfield, Laszlo Gyenis and Stefan Knapp and has published in prestigious journals such as Journal of Biological Chemistry, SHILAP Revista de lepidopterología and Nature Reviews Drug Discovery.

In The Last Decade

Alison D. Axtman

39 papers receiving 440 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alison D. Axtman United States 12 299 96 86 49 44 42 440
Rafael J. Rojas United States 12 412 1.4× 123 1.3× 90 1.0× 34 0.7× 27 0.6× 17 523
Yuri Tomabechi Japan 15 403 1.3× 78 0.8× 31 0.4× 42 0.9× 33 0.8× 26 527
Naoto Soya Canada 13 524 1.8× 90 0.9× 37 0.4× 95 1.9× 56 1.3× 15 928
Po Hien Ear United States 14 453 1.5× 111 1.2× 189 2.2× 44 0.9× 65 1.5× 35 737
Martin Golkowski United States 14 374 1.3× 73 0.8× 67 0.8× 52 1.1× 28 0.6× 28 511
Rosario Recacha United States 11 227 0.8× 96 1.0× 24 0.3× 93 1.9× 29 0.7× 22 423
Audrey van Drogen Switzerland 10 570 1.9× 230 2.4× 84 1.0× 24 0.5× 46 1.0× 11 752
Bernhard C. Lechtenberg United States 17 558 1.9× 86 0.9× 128 1.5× 28 0.6× 55 1.3× 26 810
D. Kudlinzki Germany 13 324 1.1× 103 1.1× 115 1.3× 37 0.8× 26 0.6× 20 448
Cecilia Y. Cheng United States 7 624 2.1× 85 0.9× 55 0.6× 25 0.5× 34 0.8× 11 728

Countries citing papers authored by Alison D. Axtman

Since Specialization
Citations

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

Fields of papers citing papers by Alison D. Axtman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alison D. Axtman. 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 Alison D. Axtman. The network helps show where Alison D. Axtman may publish in the future.

Co-authorship network of co-authors of Alison D. Axtman

This figure shows the co-authorship network connecting the top 25 collaborators of Alison D. Axtman. A scholar is included among the top collaborators of Alison D. Axtman 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 Alison D. Axtman. Alison D. Axtman 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.
Smith, Jeffrey L., et al.. (2025). Development of a Second-Generation, In Vivo Chemical Probe for PIKfyve. Journal of Medicinal Chemistry. 68(3). 3282–3308. 1 indexed citations
2.
Ong, Han Wee, Jeffery L. Smith, Jason W. Brown, et al.. (2024). More than an Amide Bioisostere: Discovery of 1,2,4-Triazole-containing Pyrazolo[1,5- a ]pyrimidine Host CSNK2 Inhibitors for Combatting β-Coronavirus Replication. Journal of Medicinal Chemistry. 67(14). 12261–12313. 6 indexed citations
3.
Ong, Han Wee, Jeffery L. Smith, Sharon Taft-Benz, et al.. (2024). Strategic Fluorination to Achieve a Potent, Selective, Metabolically Stable, and Orally Bioavailable Inhibitor of CSNK2. Molecules. 29(17). 4158–4158. 1 indexed citations
4.
Gomez, Shawn M., Alison D. Axtman, Timothy M. Willson, et al.. (2024). Illuminating function of the understudied druggable kinome. Drug Discovery Today. 29(3). 103881–103881. 6 indexed citations
5.
Rocha, Cecilia, Brian Anderson, Thomas M. Durcan, et al.. (2024). Illumination of understudied ciliary kinases. Frontiers in Molecular Biosciences. 11. 1352781–1352781. 5 indexed citations
6.
Calderón‐Rivera, Aida, et al.. (2024). Targeting Nav1.7 and Nav1.8 with a PIKfyve inhibitor to reverse inflammatory and neuropathic pain. PubMed. 17. 100174–100174. 1 indexed citations
7.
Asquith, Christopher R. M., Michael P. East, Tuomo Laitinen, et al.. (2024). Discovery and optimization of narrow spectrum inhibitors of Tousled like kinase 2 (TLK2) using quantitative structure activity relationships. European Journal of Medicinal Chemistry. 271. 116357–116357. 1 indexed citations
8.
Ong, Han Wee, Jeffery L. Smith, Jason W. Brown, et al.. (2023). Optimization of 3-Cyano-7-cyclopropylamino-pyrazolo[1,5- a ]pyrimidines toward the Development of an In Vivo Chemical Probe for CSNK2A. ACS Omega. 8(42). 39546–39561. 12 indexed citations
9.
Ong, Han Wee, William Richardson, Emily R. Lowry, et al.. (2023). Discovery of a Potent and Selective CDKL5/GSK3 Chemical Probe That Is Neuroprotective. ACS Chemical Neuroscience. 14(9). 1672–1685. 7 indexed citations
10.
11.
Du, Yuhong, W.J. Bradshaw, Kun Qian, et al.. (2023). Discovery of FERM domain protein–protein interaction inhibitors for MSN and CD44 as a potential therapeutic approach for Alzheimer’s disease. Journal of Biological Chemistry. 299(12). 105382–105382. 8 indexed citations
12.
Davis‐Gilbert, Zachary W., Andreas Krämer, James E. Dunford, et al.. (2023). Discovery of a Potent and Selective Naphthyridine-Based Chemical Probe for Casein Kinase 2. ACS Medicinal Chemistry Letters. 14(4). 432–441. 11 indexed citations
13.
Du, Yuhong, V.L. Katis, Stephen V. Frye, et al.. (2023). Fused Tetrahydroquinolines Are Interfering with Your Assay. Journal of Medicinal Chemistry. 66(21). 14434–14446. 4 indexed citations
14.
15.
Axtman, Alison D., Paul E. Brennan, Ranjita Betarbet, et al.. (2023). Open drug discovery in Alzheimer's disease. Alzheimer s & Dementia Translational Research & Clinical Interventions. 9(2). e12394–e12394. 4 indexed citations
16.
Agajanian, Megan J., Frances Potjewyd, Brittany M. Bowman, et al.. (2022). Protein proximity networks and functional evaluation of the casein kinase 1 gamma family reveal unique roles for CK1γ3 in WNT signaling. Journal of Biological Chemistry. 298(6). 101986–101986. 6 indexed citations
17.
Lorente‐Macías, Álvaro, et al.. (2020). Towards a RIOK2 chemical probe: cellular potency improvement of a selective 2-(acylamino)pyridine series. RSC Medicinal Chemistry. 12(1). 129–136. 4 indexed citations
18.
Tamir, Tigist Y., David H. Drewry, Carrow I. Wells, Michael B. Major, & Alison D. Axtman. (2020). PKIS deep dive yields a chemical starting point for dark kinases and a cell active BRSK2 inhibitor. Scientific Reports. 10(1). 15826–15826. 9 indexed citations
19.
Wells, Carrow I., Rafael M. Couñago, Juanita C. Limas, et al.. (2019). SGC-AAK1-1: A Chemical Probe Targeting AAK1 and BMP2K. ACS Medicinal Chemistry Letters. 11(3). 340–345. 28 indexed citations
20.
Ruan, Zheng, et al.. (2018). Substrate binding allosterically relieves autoinhibition of the pseudokinase TRIB1. Science Signaling. 11(549). 46 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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