John T. Ormerod

2.0k total citations
50 papers, 1.1k citations indexed

About

John T. Ormerod is a scholar working on Statistics and Probability, Artificial Intelligence and Molecular Biology. According to data from OpenAlex, John T. Ormerod has authored 50 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Statistics and Probability, 23 papers in Artificial Intelligence and 15 papers in Molecular Biology. Recurrent topics in John T. Ormerod's work include Bayesian Methods and Mixture Models (19 papers), Statistical Methods and Inference (19 papers) and Statistical Methods and Bayesian Inference (17 papers). John T. Ormerod is often cited by papers focused on Bayesian Methods and Mixture Models (19 papers), Statistical Methods and Inference (19 papers) and Statistical Methods and Bayesian Inference (17 papers). John T. Ormerod collaborates with scholars based in Australia, United States and China. John T. Ormerod's co-authors include M. P. Wand, Jean Yang, Pengyi Yang, Simone A. Padoan, R. Frühwirth, Chong You, Samuel Müller, Christel Faes, Kitty Lo and Shila Ghazanfar and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and SHILAP Revista de lepidopterología.

In The Last Decade

John T. Ormerod

48 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John T. Ormerod Australia 17 487 454 259 81 67 50 1.1k
Jianhua Z. Huang United States 18 607 1.2× 378 0.8× 247 1.0× 125 1.5× 81 1.2× 39 1.4k
Jacob Bien United States 14 189 0.4× 316 0.7× 195 0.8× 45 0.6× 54 0.8× 35 976
Carlos M. Carvalho United States 13 471 1.0× 402 0.9× 291 1.1× 173 2.1× 59 0.9× 41 1.2k
Kam‐Wah Tsui United States 16 775 1.6× 261 0.6× 625 2.4× 116 1.4× 136 2.0× 55 1.6k
Kimberly F. Sellers United States 14 360 0.7× 170 0.4× 146 0.6× 72 0.9× 30 0.4× 42 986
Bertrand Clarke United States 13 314 0.6× 535 1.2× 176 0.7× 37 0.5× 25 0.4× 61 1.1k
Lingzhou Xue United States 16 429 0.9× 217 0.5× 175 0.7× 61 0.8× 39 0.6× 62 1.2k
Aurélie Lozano United States 16 122 0.3× 323 0.7× 202 0.8× 35 0.4× 36 0.5× 52 857
Yoonkyung Lee United States 14 166 0.3× 618 1.4× 388 1.5× 24 0.3× 27 0.4× 46 1.5k
David R. Bickel Canada 15 363 0.7× 187 0.4× 309 1.2× 68 0.8× 132 2.0× 90 934

Countries citing papers authored by John T. Ormerod

Since Specialization
Citations

This map shows the geographic impact of John T. Ormerod'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 John T. Ormerod with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John T. Ormerod more than expected).

Fields of papers citing papers by John T. Ormerod

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John T. Ormerod. 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 John T. Ormerod. The network helps show where John T. Ormerod may publish in the future.

Co-authorship network of co-authors of John T. Ormerod

This figure shows the co-authorship network connecting the top 25 collaborators of John T. Ormerod. A scholar is included among the top collaborators of John T. Ormerod 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 John T. Ormerod. John T. Ormerod 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.
Ormerod, John T., et al.. (2025). Gaussian Variational Approximation for Ordinal Data with Crossed Random Effects. Journal of Computational and Graphical Statistics. 35(1). 63–74.
2.
Yang, Pengyi, et al.. (2022). scREMOTE: Using multimodal single cell data to predict regulatory gene relationships and to build a computational cell reprogramming model. NAR Genomics and Bioinformatics. 4(1). lqac023–lqac023. 8 indexed citations
3.
Ormerod, John T., et al.. (2022). spicyR: spatial analysis of in situ cytometry data in R. Bioinformatics. 38(11). 3099–3105. 25 indexed citations
4.
Benzie, Ronald, et al.. (2022). Maternal diabetes independent of BMI is associated with altered accretion of adipose tissue in large for gestational age fetuses. PLoS ONE. 17(5). e0268972–e0268972. 2 indexed citations
5.
Ormerod, John T., et al.. (2020). Variational discriminant analysis with variable selection. Statistics and Computing. 30(4). 933–951. 5 indexed citations
6.
Lin, Yingxin, Shila Ghazanfar, Kevin Wang, et al.. (2019). scMerge leverages factor analysis, stable expression, and pseudoreplication to merge multiple single-cell RNA-seq datasets. Proceedings of the National Academy of Sciences. 116(20). 9775–9784. 110 indexed citations
7.
Cao, Yue, Yingxin Lin, John T. Ormerod, et al.. (2019). scDC: single cell differential composition analysis. BMC Bioinformatics. 20(S19). 721–721. 28 indexed citations
8.
Hall, P., et al.. (2019). Fast and Accurate Binary Response Mixed Model Analysis via Expectation Propagation. Journal of the American Statistical Association. 115(532). 1902–1916. 3 indexed citations
9.
Azizi, Lamiae, et al.. (2019). Variational nonparametric discriminant analysis. Computational Statistics & Data Analysis. 142. 106817–106817. 2 indexed citations
10.
Ghazanfar, Shila, Dario Strbenac, John T. Ormerod, Jean Yang, & Ellis Patrick. (2018). DCARS: differential correlation across ranked samples. Bioinformatics. 35(5). 823–829. 5 indexed citations
11.
12.
Al-Anzi, Bader, et al.. (2017). Modeling and analysis of modular structure in diverse biological networks. Journal of Theoretical Biology. 422. 18–30. 3 indexed citations
13.
Ghazanfar, Shila, et al.. (2016). Integrated single cell data analysis reveals cell specific networks and novel coactivation markers. BMC Systems Biology. 10(S5). 127–127. 18 indexed citations
14.
Altwegg, Res, et al.. (2016). A Variational Bayes Approach to the Analysis of Occupancy Models. PLoS ONE. 11(2). e0148966–e0148966. 3 indexed citations
15.
You, Chong, Samuel Müller, & John T. Ormerod. (2014). On generalized degrees of freedom with application in linear mixed models selection. Statistics and Computing. 26(1-2). 199–210. 7 indexed citations
16.
You, Chong, John T. Ormerod, & Samuel Müller. (2014). On Variational Bayes Estimation and Variational Information Criteria for Linear Regression Models. Australian & New Zealand Journal of Statistics. 56(1). 73–87. 20 indexed citations
17.
Wand, M. P., John T. Ormerod, Simone A. Padoan, & R. Frühwirth. (2011). Mean Field Variational Bayes for Elaborate Distributions. Bayesian Analysis. 6(4). 88 indexed citations
18.
Ormerod, John T. & M. P. Wand. (2010). Explaining Variational Approximations. The American Statistician. 64(2). 140–153. 226 indexed citations
19.
Wand, M. P. & John T. Ormerod. (2008). ON SEMIPARAMETRIC REGRESSION WITH O'SULLIVAN PENALIZED SPLINES. Australian & New Zealand Journal of Statistics. 50(2). 179–198. 124 indexed citations
20.
Jeyakumar, V., John T. Ormerod, & Robert S. Womersley. (2006). Knowledge-based semidefinite linear programming classifiers. Optimization methods & software. 21(5). 693–706. 7 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Jianhua Z. Huang Breakdown of academic impact, for papers by Jacob Bien Breakdown of academic impact, for papers by Carlos M. Carvalho Breakdown of academic impact, for papers by Kam‐Wah Tsui Breakdown of academic impact, for papers by Kimberly F. Sellers Breakdown of academic impact, for papers by Bertrand Clarke Breakdown of academic impact, for papers by Lingzhou Xue Breakdown of academic impact, for papers by Aurélie Lozano Breakdown of academic impact, for papers by Yoonkyung Lee Breakdown of academic impact, for papers by David R. Bickel
Rankless by CCL
2026