Carrow I. Wells

2.8k total citations
46 papers, 843 citations indexed

About

Carrow I. Wells is a scholar working on Molecular Biology, Oncology and Cell Biology. According to data from OpenAlex, Carrow I. Wells has authored 46 papers receiving a total of 843 indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Molecular Biology, 14 papers in Oncology and 12 papers in Cell Biology. Recurrent topics in Carrow I. Wells's work include Cancer-related Molecular Pathways (11 papers), Microtubule and mitosis dynamics (8 papers) and Protein Kinase Regulation and GTPase Signaling (8 papers). Carrow I. Wells is often cited by papers focused on Cancer-related Molecular Pathways (11 papers), Microtubule and mitosis dynamics (8 papers) and Protein Kinase Regulation and GTPase Signaling (8 papers). Carrow I. Wells collaborates with scholars based in United States, United Kingdom and Brazil. Carrow I. Wells's co-authors include David H. Drewry, William J. Zuercher, Timothy M. Willson, Alison D. Axtman, Julie E. Pickett, Christopher R. M. Asquith, Tuomo Laitinen, Jonathan M. Elkins, Rafael M. Couñago and Stefan Knapp and has published in prestigious journals such as Nature Communications, The EMBO Journal and Blood.

In The Last Decade

Carrow I. Wells

44 papers receiving 835 citations

Peers

Carrow I. Wells
Jim Nonomiya United States
Martin Schröder Germany
Julie E. Pickett United States
Alexander Gozman United States
Marton I. Siklos United States
Françoise Perron‐Sierra France
Sascha Menninger Germany
Krista K. Bowman United States
Dalia I. Hammoudeh United States
Qiaodan Zhou China
Jim Nonomiya United States
Carrow I. Wells
Citations per year, relative to Carrow I. Wells Carrow I. Wells (= 1×) peers Jim Nonomiya

Countries citing papers authored by Carrow I. Wells

Since Specialization
Citations

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

Fields of papers citing papers by Carrow I. Wells

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Carrow I. Wells

This figure shows the co-authorship network connecting the top 25 collaborators of Carrow I. Wells. A scholar is included among the top collaborators of Carrow I. 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 Carrow I. Wells. Carrow I. 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.
Newman, J.A., H. Aitkenhead, Robert te Poele, et al.. (2025). Structural insights into human brachyury DNA recognition and discovery of progressible binders for cancer therapy. Nature Communications. 16(1). 1596–1596. 2 indexed citations
2.
Yan, Zhibo, Carrow I. Wells, Jian Wu, et al.. (2025). Targeting STK17B kinase activates ferroptosis and suppresses drug resistance in multiple myeloma. Blood. 147(1). 48–60.
3.
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
4.
5.
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
6.
Wells, Carrow I. & David H. Drewry. (2023). Developing a Kinase Chemogenomic Set: Facilitating Investigation into Kinase Biology by Linking Phenotypes to Targets. Methods in molecular biology. 2706. 11–24. 1 indexed citations
7.
Tiek, Deanna, Carrow I. Wells, Martin Schröder, et al.. (2023). SGC-CLK-1: A chemical probe for the Cdc2-like kinases CLK1, CLK2, and CLK4. PubMed. 3. 100045–100045. 1 indexed citations
8.
Ercoli, María Florencia, Rashmi Jain, Oliver Xiaoou Dong, et al.. (2022). An open source plant kinase chemogenomics set. Plant Direct. 6(11). e460–e460. 1 indexed citations
9.
Capuzzi, Stephen J., Dmytro S. Radchenko, Olena Savych, et al.. (2022). Generative and reinforcement learning approaches for the automated de novo design of bioactive compounds. Communications Chemistry. 5(1). 129–129. 59 indexed citations
10.
Asquith, Christopher R. M., Michael P. East, Tuomo Laitinen, et al.. (2022). Identification of 4‐Anilinoquin(az)oline as a Cell‐Active Protein Kinase Novel 3 (PKN3) Inhibitor Chemotype**. ChemMedChem. 17(12). e202200161–e202200161. 3 indexed citations
11.
Wells, Carrow I., Julie E. Pickett, Lauren E. Howard, et al.. (2021). Non-canonical role of Hippo tumor suppressor serine/threonine kinase 3 STK3 in prostate cancer. Molecular Therapy. 30(1). 485–500. 23 indexed citations
12.
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
13.
Wells, Carrow I., James D. Vasta, Cesear Corona, et al.. (2020). Quantifying CDK inhibitor selectivity in live cells. Nature Communications. 11(1). 2743–2743. 78 indexed citations
14.
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
15.
Profeta, Gerson S., André da Silva Santiago, Paulo H. Godoi, et al.. (2019). Binding and structural analyses of potent inhibitors of the human Ca2+/calmodulin dependent protein kinase kinase 2 (CAMKK2) identified from a collection of commercially-available kinase inhibitors. Scientific Reports. 9(1). 16452–16452. 15 indexed citations
16.
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
17.
Byrne, Dominic P., Yong Li, Claire E. Eyers, et al.. (2018). New tools for evaluating protein tyrosine sulfation: tyrosylprotein sulfotransferases (TPSTs) are novel targets for RAF protein kinase inhibitors. Biochemical Journal. 475(15). 2435–2455. 28 indexed citations
18.
Byrne, Dominic P., Yong Li, Igor Barsukov, et al.. (2018). New tools for carbohydrate sulfation analysis: heparan sulfate 2- O -sulfotransferase (HS2ST) is a target for small-molecule protein kinase inhibitors. Biochemical Journal. 475(15). 2417–2433. 17 indexed citations
19.
Matossian, Margarite D., Steven Elliott, Van T. Hoang, et al.. (2017). Novel application of the published kinase inhibitor set to identify therapeutic targets and pathways in triple negative breast cancer subtypes. PLoS ONE. 12(8). e0177802–e0177802. 4 indexed citations
20.
Couñago, Rafael M., C.K. Allerston, P. Savitsky, et al.. (2017). Structural characterization of human Vaccinia-Related Kinases (VRK) bound to small-molecule inhibitors identifies different P-loop conformations. Scientific Reports. 7(1). 7501–7501. 25 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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