Ty M. Thomson

965 total citations
12 papers, 590 citations indexed

About

Ty M. Thomson is a scholar working on Molecular Biology, Computational Theory and Mathematics and Biophysics. According to data from OpenAlex, Ty M. Thomson has authored 12 papers receiving a total of 590 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 2 papers in Computational Theory and Mathematics and 2 papers in Biophysics. Recurrent topics in Ty M. Thomson's work include Gene Regulatory Network Analysis (5 papers), Bioinformatics and Genomic Networks (3 papers) and Glycosylation and Glycoproteins Research (2 papers). Ty M. Thomson is often cited by papers focused on Gene Regulatory Network Analysis (5 papers), Bioinformatics and Genomic Networks (3 papers) and Glycosylation and Glycoproteins Research (2 papers). Ty M. Thomson collaborates with scholars based in Switzerland, United States and Italy. Ty M. Thomson's co-authors include Daniel Figeys, Ian I. Stewart, Julia Hoeng, Manuel C. Peitsch, Alain Sewer, Florian Martin, David A. Drubin, Dexter Pratt, Renée Deehan and Dirk Weisensee and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Drug Discovery Today.

In The Last Decade

Ty M. Thomson

12 papers receiving 570 citations

Peers

Ty M. Thomson

MB

SPECT

HTM

CTM

PHYSI

Dries Verdegem France

Clément Frainay France

Janice Nickson United Kingdom

Ethan Stancliffe United States

Stephen C. Brown United States

Jordi Capellades Spain

David Hau Canada

Keun Na South Korea

Hannes Planatscher Germany

Stéphane Camuzeaux United Kingdom

Dries Verdegem France

Ty M. Thomson

586 ×1.4

MB

113 ×0.5

SPECT

22 ×0.4

HTM

34 ×0.6

CTM

96 ×1.8

PHYSI

Citations per year, relative to Ty M. Thomson Ty M. Thomson (= 1×) peers Dries Verdegem

Countries citing papers authored by Ty M. Thomson

Since Specialization

Citations

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

Fields of papers citing papers by Ty M. Thomson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ty M. Thomson

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

All Works

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12 of 12 papers shown

1.

Tokareva, Olena, Kunhua Li, Ty M. Thomson, et al.. (2023). Recognition and reprogramming of E3 ubiquitin ligase surfaces by α-helical peptides. Nature Communications. 14(1). 6992–6992. 12 indexed citations

2.

Li, Kunhua, et al.. (2022). De novo mapping of α-helix recognition sites on protein surfaces using unbiased libraries. Proceedings of the National Academy of Sciences. 119(52). 15 indexed citations

3.

Thomson, Ty M., Reynald Lescarbeau, David A. Drubin, et al.. (2015). Blood-based identification of non-responders to anti-TNF therapy in rheumatoid arthritis. BMC Medical Genomics. 8(1). 26–26. 29 indexed citations

4.

Thomson, Ty M., et al.. (2014). An algorithm for score aggregation over causal biological networks based on random walk sampling. BMC Research Notes. 7(1). 516–516. 2 indexed citations

5.

Wilson‐Kanamori, John R., et al.. (2014). Kappa Rule-Based Modeling in Synthetic Biology. Methods in molecular biology. 1244. 105–135. 3 indexed citations

6.

Thomson, Ty M., Alain Sewer, Florian Martin, et al.. (2013). Quantitative assessment of biological impact using transcriptomic data and mechanistic network models. Toxicology and Applied Pharmacology. 272(3). 863–878. 46 indexed citations

7.

Westra, Jurjen W., Walter K. Schlage, Arnd Hengstermann, et al.. (2013). A Modular Cell-Type Focused Inflammatory Process Network Model for Non-Diseased Pulmonary Tissue. Bioinformatics and Biology Insights. 7. BBI.S11509–BBI.S11509. 35 indexed citations

8.

Martin, Florian, Ty M. Thomson, Alain Sewer, et al.. (2012). Assessment of network perturbation amplitudes by applying high-throughput data to causal biological networks. BMC Systems Biology. 6(1). 54–54. 76 indexed citations

9.

Hoeng, Julia, Renée Deehan, Dexter Pratt, et al.. (2011). A network-based approach to quantifying the impact of biologically active substances. Drug Discovery Today. 17(9-10). 413–418. 64 indexed citations

10.

Thomson, Ty M., Kirsten R. Benjamin, Alan Bush, et al.. (2011). Scaffold number in yeast signaling system sets tradeoff between system output and dynamic range. Proceedings of the National Academy of Sciences. 108(50). 20265–20270. 43 indexed citations

11.

Thomson, Ty M. & Drew Endy. (2005). Rapid Characterization of Cellular Pathways Using Time-Varying Signals. DSpace@MIT (Massachusetts Institute of Technology). 1 indexed citations

12.

Stewart, Ian I., Ty M. Thomson, & Daniel Figeys. (2001). ¹⁸ O Labeling: a tool for proteomics. Rapid Communications in Mass Spectrometry. 15(24). 2456–2465. 264 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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