Thomas Thorne

1.7k total citations · 1 hit paper
28 papers, 1.1k citations indexed

About

Thomas Thorne is a scholar working on Molecular Biology, Statistics and Probability and Statistical and Nonlinear Physics. According to data from OpenAlex, Thomas Thorne has authored 28 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 5 papers in Statistics and Probability and 4 papers in Statistical and Nonlinear Physics. Recurrent topics in Thomas Thorne's work include Gene Regulatory Network Analysis (10 papers), Bioinformatics and Genomic Networks (10 papers) and Microbial Metabolic Engineering and Bioproduction (8 papers). Thomas Thorne is often cited by papers focused on Gene Regulatory Network Analysis (10 papers), Bioinformatics and Genomic Networks (10 papers) and Microbial Metabolic Engineering and Bioproduction (8 papers). Thomas Thorne collaborates with scholars based in United Kingdom, Denmark and Germany. Thomas Thorne's co-authors include Michael P. H. Stumpf, Carsten Wiuf, Eric de Silva, Michael Lappé, R. J. C. Stewart, Paul Kirk, C. Barnes, Huizhi Liang, Sarah Filippi and Maxime Huvet and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Bioinformatics and Trends in Ecology & Evolution.

In The Last Decade

Thomas Thorne

27 papers receiving 1.1k citations

Hit Papers

Estimating the size of the human interactome 2008 2026 2014 2020 2008 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Thomas Thorne United Kingdom 15 822 174 108 106 85 28 1.1k
Eric de Silva United Kingdom 10 681 0.8× 154 0.9× 39 0.4× 121 1.1× 84 1.0× 16 1.0k
Vladislav Vyshemirsky United Kingdom 13 668 0.8× 145 0.8× 53 0.5× 47 0.4× 19 0.2× 30 959
Jerome T. Mettetal United States 18 1.6k 1.9× 213 1.2× 22 0.2× 477 4.5× 62 0.7× 48 2.5k
Vincenzo Belcastro Switzerland 18 2.0k 2.4× 523 3.0× 88 0.8× 180 1.7× 25 0.3× 32 2.5k
Hon Nian Chua Singapore 17 1.4k 1.7× 601 3.5× 43 0.4× 81 0.8× 80 0.9× 26 1.7k
Vijayalakshmi Chelliah United Kingdom 17 1.2k 1.4× 227 1.3× 36 0.3× 102 1.0× 8 0.1× 22 1.5k
Chee-Keong Kwoh Singapore 17 1.2k 1.5× 744 4.3× 224 2.1× 44 0.4× 49 0.6× 37 1.6k
Gabriel F. Berriz United States 12 2.3k 2.8× 295 1.7× 53 0.5× 280 2.6× 115 1.4× 15 2.8k
Le Ou-Yang China 20 840 1.0× 231 1.3× 108 1.0× 37 0.3× 52 0.6× 95 1.1k
Quentin Vanhaelen United States 11 649 0.8× 521 3.0× 76 0.7× 62 0.6× 10 0.1× 20 1.2k

Countries citing papers authored by Thomas Thorne

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Thorne

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thomas Thorne

This figure shows the co-authorship network connecting the top 25 collaborators of Thomas Thorne. A scholar is included among the top collaborators of Thomas Thorne 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 Thomas Thorne. Thomas Thorne 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.
Thorne, Thomas, et al.. (2024). Calibration of stochastic, agent-based neuron growth models with approximate Bayesian computation. Journal of Mathematical Biology. 89(5). 50–50. 3 indexed citations
2.
Thorne, Thomas, et al.. (2024). Shrinkage estimation of gene interaction networks in single-cell RNA sequencing data. BMC Bioinformatics. 25(1). 339–339.
3.
Thorne, Thomas, Paul Kirk, & Heather A. Harrington. (2022). Topological approximate Bayesian computation for parameter inference of an angiogenesis model. Bioinformatics. 38(9). 2529–2535. 5 indexed citations
4.
Gafson, Arie, et al.. (2018). Lipoprotein markers associated with disability from multiple sclerosis. Scientific Reports. 8(1). 17026–17026. 27 indexed citations
5.
Thorne, Thomas. (2018). Approximate inference of gene regulatory network models from RNA-Seq time series data. BMC Bioinformatics. 19(1). 127–127. 15 indexed citations
6.
Thorne, Thomas. (2016). NetDiff – Bayesian model selection for differential gene regulatory network inference. Scientific Reports. 6(1). 39224–39224. 7 indexed citations
7.
Thorne, Thomas, Pietro Fratta, Michael G. Hanna, et al.. (2013). Graphical modelling of molecular networks underlying sporadic inclusion body myositis. Molecular BioSystems. 9(7). 1736–1742. 6 indexed citations
8.
Kirk, Paul, Thomas Thorne, & Michael P. H. Stumpf. (2013). Model selection in systems and synthetic biology. Current Opinion in Biotechnology. 24(4). 767–774. 80 indexed citations
9.
You, Tao, Piers J. Ingram, Mette D. Jacobsen, et al.. (2012). A systems biology analysis of long and short-term memories of osmotic stress adaptation in fungi. BMC Research Notes. 5(1). 258–258. 32 indexed citations
10.
Liepe, Juliane, C. Barnes, Maxime Huvet, et al.. (2012). Calibrating spatio-temporal models of leukocyte dynamics against in vivo live-imaging data using approximate Bayesian computation. Integrative Biology. 4(3). 335–335. 27 indexed citations
11.
Thorne, Thomas & Michael P. H. Stumpf. (2012). Graph spectral analysis of protein interaction network evolution. Journal of The Royal Society Interface. 9(75). 2653–2666. 19 indexed citations
12.
Harrington, Heather A., Kenneth L. Ho, Thomas Thorne, & Michael P. H. Stumpf. (2012). Parameter-free model discrimination criterion based on steady-state coplanarity. Proceedings of the National Academy of Sciences. 109(39). 15746–15751. 20 indexed citations
13.
Harrington, Heather A., Kenneth L. Ho, Thomas Thorne, & Michael P. H. Stumpf. (2011). A parameter-free model selection criterion based on steady-state coplanarity. arXiv (Cornell University). 1 indexed citations
14.
Thorne, Thomas, et al.. (2010). Prediction of putative protein interactions through evolutionary analysis of osmotic stress response in the model yeast Saccharomyces cerevisae. Fungal Genetics and Biology. 48(5). 504–511. 8 indexed citations
15.
Huvet, Maxime, Tina Toni, Thomas Thorne, et al.. (2010). The Evolution of the Phage Shock Protein Response System: Interplay between Protein Function, Genomic Organization, and System Function. Molecular Biology and Evolution. 28(3). 1141–1155. 46 indexed citations
16.
Stumpf, Michael P. H., Thomas Thorne, Eric de Silva, et al.. (2008). Estimating the size of the human interactome. Proceedings of the National Academy of Sciences. 105(19). 6959–6964. 563 indexed citations breakdown →
17.
Thorne, Thomas & Michael P. H. Stumpf. (2007). Generating confidence intervals on biological networks. BMC Bioinformatics. 8(1). 467–467. 14 indexed citations
18.
Stumpf, Michael P. H., et al.. (2007). Evolution at the system level: the natural history of protein interaction networks. Trends in Ecology & Evolution. 22(7). 366–373. 38 indexed citations
19.
Silva, Eric de, Thomas Thorne, Piers J. Ingram, et al.. (2006). The effects of incomplete protein interaction data on structural and evolutionary inferences. BMC Biology. 4(1). 39–39. 52 indexed citations
20.
Bradley, Jeremy T. & Thomas Thorne. (2006). Stochastic Process Algebra Models of a Circadian Clock. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 0. 1 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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