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Runxuan Zhang

Staff picture: Runxuan Zhang
Information and Computational Sciences
Information and Computational Sciences
Quantitative Geneticist / Computational Biologist
runxuan.zhang@hutton.ac.uk
+44 (0)1382 568886

The James Hutton Institute
Invergowrie
Dundee DD2 5DA
Scotland UK

 

Runxuan is a computational biologist, who was trained in machine learning and artificial neural networks for his PhD. His 20 years of research have focused on developing computational and analysis methods/tools for high throughput experimental data, such as RNA-seq for gene expression analysis. His team has published several widely used and easily accessible software and tools for analyzing sequencing data.

He has gained extensive experience in computational biology by taking up postdoc positions in Systems Biology Group of Institut Pasteur, Paris, Center for Model Organisms Proteome, University of Zurich, Zurich and Translational Medicine Research Collaboration lab, Dundee, where his research focused on the development of novel and cutting-edge computational methods for high throughput experimental data, especially for transcriptomics and proteomics experiments.

 

 

Current research interests

His research group focuses on the development of novel and cutting-edge computational methods for analysing high throughput experimental data. He pioneered the development of methods for accurately measuring gene expression from plant RNA-seq experiments by developing the quality control pipelines that were essential for constructing a comprehensive Reference Transcript Dataset in Arabidopsis (AtRTD2). AtRTD2 allows rapid and accurate quantification of differential expression and alternative splicing (AS) analysis. This method has been translated into barley, potato and other plant species. His group also developed novel analytical tools for time-series RNA-seq data that capture the dynamics of expression and AS changes, including the first tool (R package TSIS) for characterising transcript isoform switches in a time series. These methods have now been incorporated into an easy-to-use tool for rapid and accurate RNA-seq and alternative splicing analysis (3D RNA-seq) which has been taken up by >6,000 users from ~60 countries. His group recently developed Protview, which optimizes the enzyme scheme to increase the protein coverage for proteomics experiments.

Current research projects

  • BBSRC BBR BB/S020160/1 ‘PlantRTD’ 2019-2022 (£391,401) (PI)
  • BBSRC Response Mode ‘The Generation Gap - Mechanisms of maternal control on grain’ BB/W002590/1 2022-2025 (£744,015) (Co-I)
  • BBSRC International Partnering Award ‘BarleyEUNetwork’ BB/V018906/1 2021-2024 (£30,000) (Co-I)
  • BBSRC International Partnering Award ‘UK Australia’ BB/V018299/1 2021-2024 (£30,000) (Co-I)
  • BBSRC ERA-CAPS BB/S004610/1 ‘BARN’ 2018-2022 (£649,658) (Co-I)

Bibliography

  • Simpson, C.G.; Barrero, R.A.; Bayer, M.; Flavell, A.; Rapazote-Flores, P.; Bellgard, M.I.; Hedley, P.E.; Zhang, R.; Waugh, R. (2018) The expressed portion of the barley genome., In: Stein, N. & Muehlbauer, G. (eds.). The Barley Genome, Compendium of Plant Genomes. Springer, Cham, Switzerland, Chapter 7, 789-107.

Printed from /staff/runxuan-zhang on 04/10/22 04:43:41 AM

The James Hutton Research Institute is the result of the merger in April 2011 of MLURI and SCRI. This merger formed a new powerhouse for research into food, land use, and climate change.