Matthew Thomson

5.3k total citations · 2 hit papers
20 papers, 3.8k citations indexed

About

Matthew Thomson is a scholar working on Molecular Biology, Oncology and Genetics. According to data from OpenAlex, Matthew Thomson has authored 20 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 5 papers in Oncology and 3 papers in Genetics. Recurrent topics in Matthew Thomson's work include Single-cell and spatial transcriptomics (5 papers), Cancer Cells and Metastasis (4 papers) and Pluripotent Stem Cells Research (3 papers). Matthew Thomson is often cited by papers focused on Single-cell and spatial transcriptomics (5 papers), Cancer Cells and Metastasis (4 papers) and Pluripotent Stem Cells Research (3 papers). Matthew Thomson collaborates with scholars based in United States, New Zealand and Switzerland. Matthew Thomson's co-authors include Ittai Ben‐Porath, Aviv Regev, Ruping Ge, George W. Bell, Vincent J. Carey, Robert A. Weinberg, Jeremy Gunawardena, Xin Xiong, Scott M. Coyle and Kole T. Roybal and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Matthew Thomson

20 papers receiving 3.7k citations

Hit Papers

An embryonic stem cell–like gene expression signature in ... 2008 2026 2014 2020 2008 2016 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matthew Thomson United States 15 2.7k 1.4k 678 489 367 20 3.8k
Aki Hanyu Japan 22 3.1k 1.1× 969 0.7× 658 1.0× 255 0.5× 312 0.9× 26 4.2k
Anne C. Rios Netherlands 24 1.6k 0.6× 1.3k 0.9× 416 0.6× 744 1.5× 273 0.7× 51 3.2k
Lennart Kester Netherlands 15 2.2k 0.8× 616 0.5× 673 1.0× 264 0.5× 294 0.8× 54 3.1k
Elsa Quintana United States 18 1.6k 0.6× 2.1k 1.5× 964 1.4× 330 0.7× 155 0.4× 40 3.5k
Keith Brennan United Kingdom 38 3.4k 1.2× 1.3k 1.0× 596 0.9× 147 0.3× 359 1.0× 64 4.4k
Connie A. Myers United States 26 2.2k 0.8× 754 0.6× 505 0.7× 416 0.9× 412 1.1× 40 3.3k
Jamison L. Nourse United States 24 2.9k 1.1× 1.3k 1.0× 315 0.5× 325 0.7× 323 0.9× 36 4.5k
Laura M. Selfors United States 25 2.0k 0.7× 874 0.6× 640 0.9× 240 0.5× 157 0.4× 43 3.2k
Bas Ponsioen Netherlands 20 2.2k 0.8× 909 0.7× 473 0.7× 440 0.9× 210 0.6× 27 3.3k
Ugo Cavallaro Italy 35 2.8k 1.0× 1.3k 0.9× 752 1.1× 209 0.4× 200 0.5× 78 4.4k

Countries citing papers authored by Matthew Thomson

Since Specialization
Citations

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

Fields of papers citing papers by Matthew Thomson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew Thomson

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew Thomson. A scholar is included among the top collaborators of Matthew 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 Matthew Thomson. Matthew Thomson 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.
Murrow, Lyndsay M., Robert J. Weber, Christopher S. McGinnis, et al.. (2022). Mapping hormone-regulated cell-cell interaction networks in the human breast at single-cell resolution. Cell Systems. 13(8). 644–664.e8. 16 indexed citations
2.
Abdel-Haq, Reem, Johannes C. M. Schlachetzki, Joseph C. Boktor, et al.. (2022). A prebiotic diet modulates microglial states and motor deficits in α-synuclein overexpressing mice. eLife. 11. 57 indexed citations
3.
He, Bryan, Matthew Thomson, Meena Subramaniam, et al.. (2021). CloudPred: Predicting Patient Phenotypes From Single-cell RNA-seq. 337–348. 8 indexed citations
4.
Gandhi, Shashank, et al.. (2020). Bimodal function of chromatin remodeler Hmga1 in neural crest induction and Wnt-dependent emigration. eLife. 9. 17 indexed citations
5.
Gehring, Jase, et al.. (2019). Highly multiplexed single-cell RNA-seq by DNA oligonucleotide tagging of cellular proteins. Nature Biotechnology. 38(1). 35–38. 73 indexed citations
6.
Obernier, Kirsten, Arantxa Cebrián‐Silla, Matthew Thomson, et al.. (2018). Adult Neurogenesis Is Sustained by Symmetric Self-Renewal and Differentiation. Cell stem cell. 22(2). 221–234.e8. 169 indexed citations
7.
Thomson, Matthew, et al.. (2018). Diffusion as a Ruler: Modeling Kinesin Diffusion as a Length Sensor for Intraflagellar Transport. Biophysical Journal. 114(3). 663–674. 35 indexed citations
8.
Xu, Alexander M., Yapeng Su, Igor Antoshechkin, et al.. (2018). Integrated measurement of intracellular proteins and transcripts in single cells. Lab on a Chip. 18(21). 3251–3262. 14 indexed citations
9.
Aull, Katherine H., et al.. (2017). Transient Thresholding: A Mechanism Enabling Noncooperative Transcriptional Circuitry to Form a Switch. Biophysical Journal. 112(11). 2428–2438. 9 indexed citations
10.
Morsut, Leonardo, Kole T. Roybal, Xin Xiong, et al.. (2016). Engineering Customized Cell Sensing and Response Behaviors Using Synthetic Notch Receptors. Cell. 164(4). 780–791. 675 indexed citations breakdown →
11.
Peddada, Sailaja, Nilanjana Chatterjee, Tara Friedrich, et al.. (2016). SOX2 O-GlcNAcylation alters its protein-protein interactions and genomic occupancy to modulate gene expression in pluripotent cells. eLife. 5. e10647–e10647. 62 indexed citations
12.
Tsai, Yu-Hwai, Roy Nattiv, Priya H. Dedhia, et al.. (2016). In vitro patterning of pluripotent stem cell-derived intestine recapitulates in vivo human development. Development. 144(6). 1045–1055. 68 indexed citations
13.
Cerchiari, Alec E., James C. Garbe, Michael E. Todhunter, et al.. (2015). A strategy for tissue self-organization that is robust to cellular heterogeneity and plasticity. Proceedings of the National Academy of Sciences. 112(7). 2287–2292. 95 indexed citations
14.
Finkbeiner, Stacy R., David R. Hill, Christopher Altheim, et al.. (2015). Transcriptome-wide Analysis Reveals Hallmarks of Human Intestine Development and Maturation In Vitro and In Vivo. Stem Cell Reports. 4(6). 1140–1155. 190 indexed citations
16.
Thomson, Matthew, et al.. (2011). Detection of surface cracks in fibre reinforced composites using ultrasonic Rayleigh waves. 446–451. 2 indexed citations
17.
Thomson, Matthew & Jeremy Gunawardena. (2009). The rational parameterisation theorem for multisite post-translational modification systems. Journal of Theoretical Biology. 261(4). 626–636. 67 indexed citations
18.
Thomson, Matthew & Jeremy Gunawardena. (2009). Unlimited multistability in multisite phosphorylation systems. Nature. 460(7252). 274–277. 177 indexed citations
19.
Ben‐Porath, Ittai, Matthew Thomson, Vincent J. Carey, et al.. (2008). An embryonic stem cell–like gene expression signature in poorly differentiated aggressive human tumors. Nature Genetics. 40(5). 499–507. 1967 indexed citations breakdown →
20.
Thomson, Matthew, et al.. (2008). Programming with models: modularity and abstraction provide powerful capabilities for systems biology. Journal of The Royal Society Interface. 6(32). 257–270. 57 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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