Lloyd T. Elliott

12.5k total citations · 3 hit papers
25 papers, 5.4k citations indexed

About

Lloyd T. Elliott is a scholar working on Genetics, Molecular Biology and Cognitive Neuroscience. According to data from OpenAlex, Lloyd T. Elliott has authored 25 papers receiving a total of 5.4k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Genetics, 7 papers in Molecular Biology and 7 papers in Cognitive Neuroscience. Recurrent topics in Lloyd T. Elliott's work include Genetic Associations and Epidemiology (8 papers), Functional Brain Connectivity Studies (5 papers) and Neural dynamics and brain function (4 papers). Lloyd T. Elliott is often cited by papers focused on Genetic Associations and Epidemiology (8 papers), Functional Brain Connectivity Studies (5 papers) and Neural dynamics and brain function (4 papers). Lloyd T. Elliott collaborates with scholars based in Canada, United Kingdom and France. Lloyd T. Elliott's co-authors include Kevin Sharp, Jonathan Marchini, Stephen Leslie, Gavin Band, Colin Freeman, A. P. Young, Olivier Delaneau, Allan Motyer, Mark Effingham and Desislava Petkova and has published in prestigious journals such as Nature, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Lloyd T. Elliott

20 papers receiving 5.4k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

The UK Biobank resource with deep phenotyping and genomic data

2018 4.4k citations Clare Bycroft, Colin Freeman et al. Nature profile →
Genome-wide association studies of brain imaging phenotypes in UK Biobank

2018 429 citations Lloyd T. Elliott, Kevin Sharp et al. Nature profile →
An expanded set of genome-wide association studies of brain imaging phenotypes in UK Biobank

2021 244 citations Stephen M. Smith, Gwenaëlle Douaud et al. Nature Neuroscience profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Lloyd T. Elliott Canada	10	2.5k	1.4k	584	547	486	25	5.4k
Kevin Sharp United States	11	2.7k 1.1×	1.5k 1.1×	465 0.8×	539 1.0×	487 1.0×	17	5.4k
Ravindranath Duggirala United States	36	1.4k 0.5×	1.2k 0.9×	802 1.4×	529 1.0×	523 1.1×	116	4.4k
Brendan Bulik‐Sullivan United States	11	4.4k 1.8×	1.8k 1.3×	365 0.6×	540 1.0×	578 1.2×	14	6.6k
Caroline Hayward United Kingdom	47	2.3k 0.9×	2.7k 1.9×	429 0.7×	754 1.4×	457 0.9×	220	8.1k
Joanne E. Curran United States	40	1.5k 0.6×	2.3k 1.6×	424 0.7×	809 1.5×	878 1.8×	197	5.8k
Thomas D. Dyer United States	43	2.4k 0.9×	2.3k 1.6×	434 0.7×	802 1.5×	863 1.8×	186	6.7k
Stephen Leslie United States	21	2.7k 1.1×	1.7k 1.2×	202 0.3×	560 1.0×	602 1.2×	66	6.4k
Clare Bycroft United Kingdom	4	2.5k 1.0×	1.7k 1.2×	178 0.3×	469 0.9×	478 1.0×	4	5.2k
Adrián Cortés United Kingdom	19	2.6k 1.0×	1.7k 1.2×	177 0.3×	515 0.9×	595 1.2×	30	6.0k
Gavin Band United Kingdom	7	2.7k 1.0×	1.3k 0.9×	183 0.3×	460 0.8×	460 0.9×	10	5.0k

Countries citing papers authored by Lloyd T. Elliott

Since Specialization

Citations

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

Fields of papers citing papers by Lloyd T. Elliott

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lloyd T. Elliott

This figure shows the co-authorship network connecting the top 25 collaborators of Lloyd T. Elliott. A scholar is included among the top collaborators of Lloyd T. Elliott 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 Lloyd T. Elliott. Lloyd T. Elliott 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

Brooks‐Wilson, Angela, et al.. (2025). A Joint Bayesian Model for Change-Points and Heteroskedasticity Applied to the Canadian Longitudinal Study on Aging. Journal of Computational Biology. 32(4). 374–393.

Manuello, Jordi, Paul J. McCarthy, Fidel Alfaro‐Almagro, et al.. (2024). The effects of genetic and modifiable risk factors on brain regions vulnerable to ageing and disease. Nature Communications. 15(1). 2576–2576. 11 indexed citations

Cao, Jiguo, et al.. (2024). Faster Asymptotic Solutions for N-Mixtures on Large Populations. Journal of Agricultural Biological and Environmental Statistics. 30(3). 730–745.

Song, Xiaowei, et al.. (2023). Physiological phenotypes have optimal values relevant to healthy aging: sweet spots deduced from the Canadian Longitudinal Study on Aging. GeroScience. 46(2). 1589–1605. 2 indexed citations

Stenning, David C., et al.. (2023). Efficient galaxy classification through pretraining. Frontiers in Astronomy and Space Sciences. 10. 2 indexed citations

Wang, Chaoyue, Fidel Alfaro‐Almagro, Gwenaëlle Douaud, et al.. (2022). Phenotypic and genetic associations of quantitative magnetic susceptibility in UK Biobank brain imaging. Nature Neuroscience. 25(6). 818–831. 47 indexed citations

Wang, Shijia, et al.. (2022). Shape modeling with spline partitions. Statistics and Computing. 33(1).

Lee, Soojin, Janine Bijsterbosch, Lloyd T. Elliott, et al.. (2022). Amplitudes of resting-state functional networks – investigation into their correlates and biophysical properties. NeuroImage. 265. 119779–119779. 3 indexed citations

Cowen, Laura, et al.. (2022). Computational Efficiency and Precision for Replicated-Count and Batch-Marked Hidden Population Models. Journal of Agricultural Biological and Environmental Statistics. 28(1). 43–58. 1 indexed citations

10.

Wang, Shijia, et al.. (2021). Estimating Genetic Similarity Matrices Using Phylogenies. Journal of Computational Biology. 28(6). 587–600. 5 indexed citations

11.

Stockdale, Jessica E., et al.. (2021). Long time frames to detect the impact of changing COVID-19 measures, Canada, March to July 2020. Eurosurveillance. 26(40). 2 indexed citations

12.

Smith, Stephen M., Gwenaëlle Douaud, Taylor Hanayik, et al.. (2021). An expanded set of genome-wide association studies of brain imaging phenotypes in UK Biobank. Nature Neuroscience. 24(5). 737–745. 244 indexed citations breakdown →

13.

Smith, Stephen M., Lloyd T. Elliott, Fidel Alfaro‐Almagro, et al.. (2020). Brain aging comprises many modes of structural and functional change with distinct genetic and biophysical associations. eLife. 9. 113 indexed citations

14.

Mollink, Jeroen, Stephen M. Smith, Lloyd T. Elliott, et al.. (2019). The spatial correspondence and genetic influence of interhemispheric connectivity with white matter microstructure. Nature Neuroscience. 22(5). 809–819. 39 indexed citations

15.

Schwab, Simon, Valerio Zerbi, Lloyd T. Elliott, et al.. (2018). Directed functional connectivity using dynamic graphical models. NeuroImage. 175. 340–353. 18 indexed citations

16.

Elliott, Lloyd T., Maria De Iorio, Stefano Favaro, Kaustubh Adhikari, & Yee Whye Teh. (2018). Modeling Population Structure Under Hierarchical Dirichlet Processes. Bayesian Analysis. 14(2). 4 indexed citations

17.

Bycroft, Clare, Colin Freeman, Desislava Petkova, et al.. (2018). The UK Biobank resource with deep phenotyping and genomic data. Nature. 562(7726). 203–209. 4399 indexed citations breakdown →

18.

Elliott, Lloyd T., Kevin Sharp, Fidel Alfaro‐Almagro, et al.. (2018). Genome-wide association studies of brain imaging phenotypes in UK Biobank. Nature. 562(7726). 210–216. 429 indexed citations breakdown →

19.

Cichy, Radoslaw Martin, et al.. (2012). Probing principles of large‐scale object representation: Category preference and location encoding. Human Brain Mapping. 34(7). 1636–1651. 29 indexed citations

20.

Elliott, Lloyd T. & Yee Whye Teh. (2012). Scalable imputation of genetic data with a discrete fragmentation-coagulation process. Neural Information Processing Systems. 25. 2852–2860. 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.

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