The Applied Bioinformatics (AB) group, established in 2012, is one of Rothamsted's core capabilities. We are an applied group in the sense that we apply computational and bioinformatics methods on challenging biological questions that underpin Rothamsted science. We provide bioinformatics support and training on data intensive research projects and also put a strong emphasis on bioinformatics R&D to develop novel approaches to analyse complex data from crops, insects, pathogens and metagenomes.
AB group collaborates
- to manage, process and analyse the Next Generation Sequencing data using state-of-the-art bioinformatics tools and technologies.
- to find value in complex biological data. We have worked on projects aiming to identify differentially expressed genes, co-expressed genes, copy number variations and significant SNPs in genome re-sequencing projects, etc.
- to integrate data from ‘omics experiments with information hidden in various public databases. We can also help build networks to visualise and explore complex interactions and quantitative datasets using free tools like Ondex (www.ondex.org).
- to build web applications and public resources for different communities. For example, QTLNetMiner is a web application for searching and ranking candidate genes for traits such as “flowering time” or “drought tolerance”.
AB group provides training
- Data management solutions for next generation sequencing (NGS) data and phenotypic trait information from field experiments.
- Primary analysis of high-throughput NGS data including de novo transcriptome assemblies, re-sequencing projects, expression analysis (RNA-seq) and metagenomics.
- Integration and exploration of large biological datasets to facilitate the systematic discovery of candidate genes (QTLNetMiner, Ondex).
- Bioinformatics software platforms (Galaxy, Geneious) being used by Rothamsted scientists.
AB group develops tools & resoruces
- QTLNetMiner is a web-based tool for candidate gene discovery in plant and animal genomes using data mining and network-based approaches.
- Ondex is an open-source framework for the integration and visualisation of biological databases using a labelled & directed multi-graph.
AB group supports bioinformatics platforms
- Galaxy is an open, web-based platform for data intensive biological research. Our own in-house Galaxy instance can be used to perform, reproduce, and share complete analyses.
- Geneious is a DNA, RNA and protein sequence alignment, assembly and analysis software platform, integrating bioinformatics and molecular biology tools into a simple interface.
- DeCypher© biocomputing systems accelerate sequence comparison by combining optimized bioinformatics applications with powerful FPGA-based accelerator cards. A single DeCypher server can provide the performance equivalent of hundreds of CPU cores.
- Berger M, Puinean AM, Randall E, Zimmer CT, Silva WM, Bielza P, Field LM, Hughes D, Mellor I, Hassani-Pak K, Siqueira HAA, Williamson MS and Bass C (2016). Insecticide resistance mediated by an exon skipping event. Mol Ecol. doi:10.1111/mec.13882
- Urban M, King R, Andongabo A, Maheswari U, Pedro H, Kersey P, Hammond-Kosack K (2016). First Draft Genome Sequence of a UK Strain (UK99) of Fusarium culmorum . Genome Announc. 2016 Sep 15;4(5). pii: e00771-16. doi: 10.1128/genomeA.00771-16.
- McGrann GR, Andongabo A, Sjökvist E, Trivedi U, Dussart F, Kaczmarek M, Mackenzie A, Fountaine JM, Taylor JM, Paterson LJ, Gorniak K, Burnett F, Kanyuka K, Hammond-Kosack KE, Rudd JJ, Blaxter M, Havis ND (2016). The genome of the emerging barley pathogen Ramularia collo-cygni. BMC Genomics. 2016 Aug 9;17:584. doi: 10.1186/s12864-016-2928-3.
- Jones FP, Clark I, King R, Shaw JL, Woodward M and Hirsch P (2016). Novel European free-living, non-diazotrophic Bradyrhizobium isolates from contrasting soils that lack nodulation and nitrogen fixation genes – a genome comparison. Nature Scientific Reports 6, Article number: 25858.
- King R, Bird N, Ramirez-Gonzalez R, Coghill J, Patil A, Hassani-Pak K, Uauy C and Phillips A (2015). Mutation scanning in wheat by exon capture and next-generation sequencing. PLoS ONE 10(9): e0137549.
- King R, Urban M, Hammond-Kosack M, Hassani-Pak K and Hammond-Kosack K (2015). The completed genome sequence of the pathogenic ascomycete fungus Fusarium graminearum. BMC Genomics 2015, 16:544.
- Urban M, King R, Hassani-Pak K and Hammond-Kosack K (2015). Whole-genome analysis of Fusarium graminearum insertional mutants identifies virulence associated genes and unmasks untagged chromosomal deletions. BMC Genomics 2015, 16:261.
- Rudd J, Kanyuka K, Hassani-Pak K, Derbyshire M, Andongabo A, Devonshire J, Lysenko A, Saqi M, Desai N, Powers S, Hooper J, Ambroso L, Bharti A, Farmer A, Hammond-Kosack K, Dietrich R, Courbot M (2015). Transcriptome and metabolite profiling the infection cycle of Zymoseptoria tritici on wheat (Triticum aestivum) reveals a biphasic interaction with plant immunity involving differential pathogen chromosomal contributions, and a variation on the hemibiotrophic lifestyle definition. Plant Physiol. 2015 Jan 16. pii: pp.114.255927.
- Wan Y, Gritsch C, Tryfona T, Ray M, Andongabo A, Hassani-Pak K, Jones H, Dupree P, Shewry P, Mitchell R. (2014). Secondary cell wall composition and candidate gene expression in developing willow (Salix purpurea) stems. Planta: 1-13.
- Taubert J, Hassani-Pak K,Castells-Brooke N and Rawlings C (2014). Ondex Web: web-based visualization and exploration of heterogeneous biological networks. Bioinformatics. doi:10.1093/bioinformatics/btt740
- Wilkinson M D, Castells-Brooke N I, Shewry P R (2012) Diversity of sequences encoded by the Gsp-1 genes in wheat and other grass species. Journal of Cereal Science, 57 (1), 1–9
- Love C G, Andongabo A E, Wang J, Carion P W C, Rawlings C J, King G J. (2012). InterStoreDB: A Generic Integration Resource for Genetic and Genomic Data. J. Integr. Plant Biol. 54(5), 345-355.
- Lysenko A, Defoin-Platel M, Hassani-Pak K, Taubert J, Hodgman C, Rawlings C and Saqi M. (2011). Assessing the functional coherence of modules found in multiple-evidence networks from Arabidopsis. BMC Bioinformatics 2011, 12: 203
- Defoin-Platel M, Hassani-Pak K, Rawlings C. (2011) Gaining confidence in cross-species annotation transfer: from simple molecular function to complex phenotypic traits. Aspects of Applied Biology 107: 79-87.
- Hassani-Pak K, Legaie R, Canevet C, van den Berg H, Moore J and Rawlings C. (2010). Enhancing Data Integration with Text Analysis to Find Proteins Implicated in Plant Stress Response. Journal of Integrative Bioinformatics, 7(3): 121.