Alex M. Clark

3.2k total citations · 1 hit paper
66 papers, 2.0k citations indexed

About

Alex M. Clark is a scholar working on Computational Theory and Mathematics, Molecular Biology and Organic Chemistry. According to data from OpenAlex, Alex M. Clark has authored 66 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Computational Theory and Mathematics, 26 papers in Molecular Biology and 14 papers in Organic Chemistry. Recurrent topics in Alex M. Clark's work include Computational Drug Discovery Methods (32 papers), Genetics, Bioinformatics, and Biomedical Research (11 papers) and Organometallic Complex Synthesis and Catalysis (7 papers). Alex M. Clark is often cited by papers focused on Computational Drug Discovery Methods (32 papers), Genetics, Bioinformatics, and Biomedical Research (11 papers) and Organometallic Complex Synthesis and Catalysis (7 papers). Alex M. Clark collaborates with scholars based in United States, Canada and New Zealand. Alex M. Clark's co-authors include Sean Ekins, Kimberley M. Zorn, Paul Labute, Daniel P. Russo, Thomas R. Lane, Antony Williams, W.R. Roper, L.J. Wright, Clifton E. F. Rickard and Ana C. Puhl and has published in prestigious journals such as Nature Materials, SHILAP Revista de lepidopterología and Environmental Science & Technology.

In The Last Decade

Alex M. Clark

65 papers receiving 1.9k citations

Hit Papers

Exploiting machine learning for end-to-end drug discovery... 2019 2026 2021 2023 2019 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
Alex M. Clark United States 24 784 744 325 311 247 66 2.0k
Alan Sousa da Silva United Kingdom 7 468 0.6× 1.4k 1.9× 414 1.3× 321 1.0× 156 0.6× 8 2.5k
H. C. Stephen Chan China 20 508 0.6× 983 1.3× 244 0.8× 356 1.1× 110 0.4× 33 1.9k
Thomas Sander Switzerland 17 826 1.1× 889 1.2× 594 1.8× 357 1.1× 132 0.5× 37 2.2k
Edward W. Lowe United States 11 828 1.1× 976 1.3× 314 1.0× 238 0.8× 100 0.4× 24 1.8k
Scott A. Wildman United States 21 762 1.0× 1.0k 1.4× 474 1.5× 325 1.0× 85 0.3× 39 2.2k
Brijesh Rathi India 24 348 0.4× 726 1.0× 461 1.4× 397 1.3× 381 1.5× 125 2.4k
William R. Pitt United Kingdom 24 691 0.9× 1.3k 1.8× 625 1.9× 311 1.0× 121 0.5× 53 2.4k
Zoe Cournia Greece 28 968 1.2× 2.1k 2.8× 460 1.4× 510 1.6× 169 0.7× 65 3.2k
Fuqiang Ban Canada 28 1.4k 1.8× 1.6k 2.1× 441 1.4× 459 1.5× 374 1.5× 64 3.0k
José S. Duca United States 25 817 1.0× 1.1k 1.5× 380 1.2× 373 1.2× 161 0.7× 56 2.1k

Countries citing papers authored by Alex M. Clark

Since Specialization
Citations

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

Fields of papers citing papers by Alex M. Clark

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alex M. Clark. 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 Alex M. Clark. The network helps show where Alex M. Clark may publish in the future.

Co-authorship network of co-authors of Alex M. Clark

This figure shows the co-authorship network connecting the top 25 collaborators of Alex M. Clark. A scholar is included among the top collaborators of Alex M. Clark 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 Alex M. Clark. Alex M. Clark 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.
Lai, Adelene, Alex M. Clark, Beate I. Escher, et al.. (2022). The Next Frontier of Environmental Unknowns: Substances of Unknown or Variable Composition, Complex Reaction Products, or Biological Materials (UVCBs). Environmental Science & Technology. 56(12). 7448–7466. 40 indexed citations
2.
Ekins, Sean, Ana C. Puhl, Kimberley M. Zorn, et al.. (2019). Exploiting machine learning for end-to-end drug discovery and development. Nature Materials. 18(5). 435–441. 352 indexed citations breakdown →
4.
Clark, Alex M., Leah McEwen, Peter Gedeck, & Barry A. Bunin. (2019). Capturing mixture composition: an open machine-readable format for representing mixed substances. Journal of Cheminformatics. 11(1). 33–33. 12 indexed citations
5.
Angus, Jan, Craig Dale, Jennifer Lapum, et al.. (2018). Gender matters in cardiac rehabilitation and diabetes: Using Bourdieu's concepts. Social Science & Medicine. 200. 44–51. 15 indexed citations
6.
Ekins, Sean, et al.. (2018). Data Mining and Computational Modeling of High-Throughput Screening Datasets. Methods in molecular biology. 1755. 197–221. 9 indexed citations
7.
Zorn, Kimberley M., et al.. (2018). Assessment of Substrate-Dependent Ligand Interactions at the Organic Cation Transporter OCT2 Using Six Model Substrates. Molecular Pharmacology. 94(3). 1057–1068. 79 indexed citations
8.
Clark, Alex M., et al.. (2016). BioAssay Templates for the semantic web. PeerJ Computer Science. 2. e61–e61. 7 indexed citations
9.
Clark, Alex M., Antony Williams, & Sean Ekins. (2015). Machines first, humans second: on the importance of algorithmic interpretation of open chemistry data. Journal of Cheminformatics. 7(1). 9–9. 22 indexed citations
10.
Ekins, Sean, Alex M. Clark, & Stephen H. Wright. (2015). Making Transporter Models for Drug–Drug Interaction Prediction Mobile. Drug Metabolism and Disposition. 43(10). 1642–1645. 12 indexed citations
11.
Clark, Alex M., Malabika Sarker, & Sean Ekins. (2014). New target prediction and visualization tools incorporating open source molecular fingerprints for TB Mobile 2.0. Journal of Cheminformatics. 6(1). 38–38. 26 indexed citations
12.
Clark, Alex M.. (2013). Rendering Molecular Sketches for Publication Quality Output. Molecular Informatics. 32(3). 291–301. 4 indexed citations
13.
Ekins, Sean, Alex M. Clark, & Malabika Sarker. (2013). TB Mobile: a mobile app for anti-tuberculosis molecules with known targets. Journal of Cheminformatics. 5(1). 13–13. 24 indexed citations
14.
Clark, Alex M., Sean Ekins, & Antony Williams. (2012). Redefining Cheminformatics with Intuitive Collaborative Mobile Apps. Molecular Informatics. 31(8). 569–584. 18 indexed citations
15.
Ekins, Sean & Alex M. Clark. (2012). Secure sharing with mobile cheminformatics apps. Figshare. 1 indexed citations
16.
Głowacka, Dorota, John Shawe‐Taylor, Alex M. Clark, Colin de la Higuera, & Mark Johnson. (2011). Introduction to the Special Topic on Grammar Induction, Representation of Language and Language Learning. Journal of Machine Learning Research. 12(39). 1425–1428. 8 indexed citations
17.
Williams, Antony, et al.. (2011). Mobile apps for chemistry in the world of drug discovery. Drug Discovery Today. 16(21-22). 928–939. 30 indexed citations
18.
Sun, Qi, Robert Bukowski, Chris J. Myers, et al.. (2010). Computational Biology Service Unit: Cornell University Core Facility for Computational Biology. Journal of Biomolecular Techniques JBT. 21. 1 indexed citations
19.
Clark, Alex M.. (2010). Basic primitives for molecular diagram sketching. Journal of Cheminformatics. 2(1). 8–8. 16 indexed citations
20.
Nettles, James H., Jeremy L. Jenkins, Chris Williams, et al.. (2007). Flexible 3D pharmacophores as descriptors of dynamic biological space. Journal of Molecular Graphics and Modelling. 26(3). 622–633. 27 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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