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Our exciting projects range from genomics through bioinformatics and citizen science to evolutionary modeling. We bring together biology, computational science and bioinformatics to make the most of big data and help answer big questions.

We study data from citizen science projects to understand how the ‘crowd’ can be used as a super-intelligent computer.

We develop tools and methods to make the most of high throughput sequence data to study non-reference, non-model organisms

We use mathematical modelling techniques to understand what drives genome size and the dynamics of gene regulation.

Latest Publications

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MacLean D (2019)

A convolutional neural network for predicting transcriptional regulators of genes in Arabidopsis transcriptome data reveals classification based on positive regulatory interactions. bioRxiv preprint Apr 28, 2019 doi: https://doi.org/10.1101/618926

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Rallapalli G, Corredor-Moreno P, Chalstrey E, Page M, MacLean D (2019)

Rapid fine mapping of causative mutations from sets of unordered, contig-sized fragments of genome sequence. BMC Bioinformatics. 2019 Jan 7;20(1):9. doi: 10.1186/s12859-018-2515-5.

Bourdais G, McLachlan DH, Rickett LM, Zhou J, Siwoszek A, Häweker H, Hartley M, Kuhn H, Morris RJ, MacLean D, Robatzek S (2018)

The use of quantitative imaging to investigate regulators of membrane trafficking in Arabidopsis stomatal closure. Traffic. 2018 Nov 16. doi: 10.1111/tra.12625.

Wirthmueller L, Asai S, Rallapalli G, Sklenar J, Fabro G, Kim DS, Lintermann R, Jaspers P, Wrzaczek M, Kangasjärvi J, MacLean D, Menke FLH, Banfield MJ, Jones JDG (2018)

Arabidopsis downy mildew effector HaRxL106 suppresses plant immunity by binding to RADICAL-INDUCED CELL DEATH1. New Phytol. 2018 Oct;220(1):232-248. doi: 10.1111/nph.15277.

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