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Wenbin Guo

Staff picture: Wenbin Guo
Information and Computational Sciences
Information and Computational Sciences
Bioinformatician
wenbin.guo@hutton.ac.uk
+44 (0)344 928 5428 (*)

The James Hutton Institute
Invergowrie
Dundee DD2 5DA
Scotland UK

 

Wenbin is a bioinformatician and his work focuses on developing computational and mathematical models for high-throughput experimental data analysis. He has developed several easy-to-use tools and novel pipelines for accurate transcriptomics data analysis, including RTDBox for reference transcript data (RTD) construction with Illumina short read sequencing and high-resolution single molecule long read sequencing data, Splice Junction  Usage Score (SJUS) for RTD assembly quality evaluation, 3D RNA-seq App for differential expression and differential alternative splicing analysis, and RLowPC for co-expression regulatory network construction. These tools have been applied in a wide range of projects, such as RTD constructions and data analyses in barley (BART1, BART2 and pan transcriptome studies of 20 barley genotypes), Arabidopsis (AtRTD1, AtRTD2, and AtRTD3), rice, potato, raspberry, lettuce, pumpkin as well as animal and human disease data. The 3D RNA-seq App he developed has over 6,000 users and won the Best Innovation Award in the School of Life Sciences at the University of Dundee as it is a real game-changer that allows biologists to conquer complex RNA-seq analysis in a couple of hours. The outputs of his work have engaged various opportunities for research commercialisation, internal and external collaborations with excellent research groups.

Current research interests

  • BBSRC BBR BB/S020160/1 “PlantRTD” 2019-2022 (£391,401) (Leading researcher)
  • FAPESP 2019/13158-8 “Heat-induced alternative splicing in rice” 2021-2026 (R$766,868) (Co-I)
  • FAPESP 2021/00394-5 “Camara growth house for plant” 2021-2026 (U$73,276) (Co-I)
  • Serrapilheira R-2011-37880 “Rice temperature memory” 2021-2024 (R$650,000) (Co-I)

Past research

  • Project in Zhejiang University of Technology: Set up mathematical models to investigate the ozone in greenhouse pest control.
  • Honours year project: Set up spatiotemporal PDE mathematical models to investigate the population movement of insects, such as locusts and aphids. The outcome is expected to provide an idea to detect and control the insect swarm. Further to reduce the chemical use and to protect the environment.
  • MSc project: Detect how to acquire and process gene expression data, how to construct gene networks from experimental data, how to simplify and optimise the network models. The goal is to have a basic scope of how to construct gene networks from large scale experimental data.
  • PhD project: Computational analysis and method development for high throughput transcriptomics and transcriptional regulatory inference in plants. 

Bibliography

  • Runxuan, Z.; Calixto Cristiane, P.G.; Tzioutziou, N.A.; James, A.B.; Simpson, C.G.; Guo, W.; Marquez, Y.; Kalyna, M.; Patro, R.; Eyras, E.; Barta, A.; Nimmo. H.G.; Brown, J.W.S. (2015) A comprehensive and non-redundant transcript reference enables accurate quantification of transcript-specific expression in Arabidopsis thaliana., Plant Genomes and Biotechnology: from Genes to Networks, Cold Spring Harbor lab., Long Island, USA, 2-5 December 2015.

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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.