Michael Salter‐Townshend

878 total citations
29 papers, 449 citations indexed

About

Michael Salter‐Townshend is a scholar working on Artificial Intelligence, Genetics and Statistical and Nonlinear Physics. According to data from OpenAlex, Michael Salter‐Townshend has authored 29 papers receiving a total of 449 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 7 papers in Genetics and 5 papers in Statistical and Nonlinear Physics. Recurrent topics in Michael Salter‐Townshend's work include Complex Network Analysis Techniques (5 papers), Bayesian Methods and Mixture Models (4 papers) and Genetic and phenotypic traits in livestock (4 papers). Michael Salter‐Townshend is often cited by papers focused on Complex Network Analysis Techniques (5 papers), Bayesian Methods and Mixture Models (4 papers) and Genetic and phenotypic traits in livestock (4 papers). Michael Salter‐Townshend collaborates with scholars based in Ireland, United Kingdom and Germany. Michael Salter‐Townshend's co-authors include Thomas Brendan Murphy, Simon Myers, John Haslett, Arthur White, Isabella Gollini, Tyler H. McCormick, Judy R M Allen, Brian Huntley, Sourabh Bhattacharya and Simon Wilson and has published in prestigious journals such as Genetics, BMC Bioinformatics and Journal of Machine Learning Research.

In The Last Decade

Michael Salter‐Townshend

27 papers receiving 428 citations

Peers

Michael Salter‐Townshend

SNP

GENET

GPC

Murray Jorgensen New Zealand

Ronald Ronald Indonesia

Charlotte Werndl United Kingdom

Gregor Wergen Germany

Isabella Gollini Ireland

Chandra Erdman United States

Joshua Garland United States

Kazuko Yamasaki Japan

Vyacheslav Lyubchich United States

Junjie Jiang United States

Murray Jorgensen New Zealand

Michael Salter‐Townshend

71 ×0.6

SNP

95 ×0.9

202 ×2.0

23 ×0.3

GENET

67 ×1.0

GPC

Citations per year, relative to Michael Salter‐Townshend Michael Salter‐Townshend (= 1×) peers Murray Jorgensen

Countries citing papers authored by Michael Salter‐Townshend

Since Specialization

Citations

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

Fields of papers citing papers by Michael Salter‐Townshend

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Salter‐Townshend. 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 Michael Salter‐Townshend. The network helps show where Michael Salter‐Townshend may publish in the future.

Co-authorship network of co-authors of Michael Salter‐Townshend

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

All Works

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20 of 20 papers shown

Ciuti, Simone, et al.. (2025). Using an agent-based model to inform sampling design for animal social network analysis. Behavioral Ecology and Sociobiology. 79(3). 1 indexed citations

O’Hagan, Adrian, et al.. (2024). How group structure impacts the numbers at risk for coronary artery disease: polygenic risk scores and nongenetic risk factors in the UK Biobank cohort. Genetics. 227(3). 1 indexed citations

Randhawa, Imtiaz A. S., John A. Browne, Ana M. Pérez O’Brien, et al.. (2024). Genomic insights into the population history and adaptive traits of Latin American Criollo cattle. Royal Society Open Science. 11(3). 231388–231388. 3 indexed citations

English, Holly M., et al.. (2024). A scoping review on bovine tuberculosis highlights the need for novel data streams and analytical approaches to curb zoonotic diseases. Veterinary Research. 55(1). 64–64. 7 indexed citations

Frantz, Laurent, Michael Salter‐Townshend, Emmeline W. Hill, et al.. (2024). Genome-wide local ancestry and the functional consequences of admixture in African and European cattle populations. Heredity. 134(1). 49–63.

Ciuti, Simone, Federico Ossi, Francesca Cagnacci, et al.. (2024). A protocol for assessing bias and robustness of social network metrics using GPS based radio-telemetry data. Movement Ecology. 12(1). 55–55. 2 indexed citations

Cama‐Moncunill, Raquel, et al.. (2023). Verifying origin claims on dairy products using stable isotope ratio analysis and random forest classification. Food Chemistry X. 19. 100858–100858. 6 indexed citations

Salter‐Townshend, Michael, et al.. (2023). A simulation study for multifactorial genetic disorders to quantify the impact of polygenic risk scores on critical illness insurance. European Actuarial Journal. 13(2). 775–813. 2 indexed citations

Hall, Thomas J., Tad S. Sonstegard, Daniel G. Bradley, et al.. (2022). Genome-wide local ancestry and evidence for mitonuclear coadaptation in African hybrid cattle populations. iScience. 25(7). 104672–104672. 21 indexed citations

10.

Ciuti, Simone, et al.. (2022). Static and dynamic methods in social network analysis reveal the association patterns of desert-dwelling giraffe. Behavioral Ecology and Sociobiology. 76(5). 1 indexed citations

11.

Gormley, Isobel Claire, et al.. (2021). Computational modelling of chromosomally clustering protein domains in bacteria. BMC Bioinformatics. 22(1). 593–593. 2 indexed citations

12.

Salter‐Townshend, Michael & Simon Myers. (2019). Fine-Scale Inference of Ancestry Segments Without Prior Knowledge of Admixing Groups. Genetics. 212(3). 869–889. 50 indexed citations

13.

Salter‐Townshend, Michael & Tyler H. McCormick. (2017). Latent space models for multiview network data. The Annals of Applied Statistics. 11(3). 1217–1244. 32 indexed citations

14.

Cunningham, Pádraig, et al.. (2016). Online trans-dimensional von Mises-Fisher mixture models for user profiles. Journal of Machine Learning Research. 17(1). 7021–7071. 4 indexed citations

15.

Salter‐Townshend, Michael & Thomas Brendan Murphy. (2014). Role Analysis in Networks Using Mixtures of Exponential Random Graph Models. Journal of Computational and Graphical Statistics. 24(2). 520–538. 19 indexed citations

16.

Salter‐Townshend, Michael & Thomas Brendan Murphy. (2012). Sentiment Analysis of Online Media. Research Repository UCD (University College Dublin). 1 indexed citations

17.

Salter‐Townshend, Michael & John Haslett. (2012). Fast inversion of a flexible regression model for multivariate pollen counts data. Environmetrics. 23(7). 595–605. 6 indexed citations

18.

Salter‐Townshend, Michael, Arthur White, Isabella Gollini, & Thomas Brendan Murphy. (2012). Review of statistical network analysis: models, algorithms, and software. Statistical Analysis and Data Mining The ASA Data Science Journal. 5(4). 243–264. 73 indexed citations

19.

Salter‐Townshend, Michael & Thomas Brendan Murphy. (2009). Variational Bayesian inference for the Latent Position Cluster Model. Arrow@dit (Dublin Institute of Technology). 10 indexed citations

20.

Parnell, Andrew, John Haslett, & Michael Salter‐Townshend. (2007). Modelling Temporal Uncertainty in Palaeoclimate Reconstructions. 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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