Bioinformatics

The Bioinformatics & KnetMiner group based at Rothamsted Research in Harpenden provides consultancy, software and analytics services to empower Agri genomics research across the globe. Our team of Bioinformatics data scientists and software engineers can support your plant, pathogen or soil (meta) genomics projects, advise on design and analysis of complex RNAseq experiments, and offer strategies and tools for gene and trait discovery. KnetMiner is our in-house developed platform for gene-trait discovery using knowledge graphs. It helps scientists to organise, mine and understand complex relationships between genes, gene networks and traits.  Try one of the free KnetMiner resources for selected species, or request a demo or training to understand it’s full capabilities.

Our services

• RNA-seq analysis (de novo assembly, abundance estimation, normalisation, statistical testing, visualisation)
• SNP discovery (for whole genome re-sequencing or GBS projects)
• Genome assembly and annotation
• Functional annotation of genes
• Data integration and data mining
• Network analysis and visualisation
• Gene discovery using knowledge graphs

Selected publications:

• King et al. (2023), The complete genome assemblies of 19 insect pests of worldwide importance to agriculture [https://www.sciencedirect.com/science/article/abs/pii/S0048357523000044]
• Hassani-Pak et al. (2021), KnetMiner: a comprehensive approach for supporting evidence-based gene discovery and complex trait analysis across species [https://onlinelibrary.wiley.com/doi/10.1111/pbi.13583]
• Neal et al. (2023), Arable soil nitrogen dynamics reflect organic inputs via the extended composite phenotype [https://www.nature.com/articles/s43016-022-00671-z]
• Vaughan et al. (2022), Proanthocyanidin biosynthesis in the developing wheat seed coat investigated by chemical and RNA-Seq analysis [https://onlinelibrary.wiley.com/doi/full/10.1002/pld3.453]
• Rose et al. (2022), Novel molecules and target genes for vegetative heat tolerance in wheat [https://onlinelibrary.wiley.com/doi/full/10.1002/pei3.10096]
• Rudd et al. (2015), Transcriptome and Metabolite Profiling of the Infection Cycle of Zymoseptoria tritici on Wheat Reveals a Biphasic Interaction with Plant Immunity Involving Differential Pathogen Chromosomal Contributions and a Variation on the Hemibiotrophic Lifestyle Definition [https://academic.oup.com/plphys/article/167/3/1158/6113592]