|Overview of OnPLS modeling based on combined profiling using transcriptomics, proteomics and metabolomics data from Poplar trees. [See Ref Löfstedt et al 2013].|
Experimental sciences, e.g. biology, chemistry and medicine, have to a large extent become information sciences and, in turn, bioinformatics and chemometrics are now prerequisites for experimental and applied research. Our aim is to develop and apply a systems biology approach to study growth and development in Poplar (the tree model) and Arabidopsis (the universal plant model) - all this in collaboration with Umeå Plant Science Centre and the Computational Life Science Cluster at Umeå University. We have already developed and optimized experimental protocols and data modelling tools to enable global phenotyping of thousands of plants using low-, semi- and high-throughput molecular profiling techniques for both Poplar and Arabidopsis. We have also developed novel strategies for generating and combining transcriptomic, proteomic and metabolomic profile data acquired from parallel analyses of hybrid aspen (Populus tremula × P. tremuloides). However, further research is needed to develop systems informatics tools and existing databases and statistical modeling to ‘catch up’ with the challenges that new experimental technologies provide.
Computational Life Science cluster (CLiC)
In our multidisciplinary approach, we integrate the fields of biology, mathematics, chemistry, physics and informatics. As a result, we have established a unique bioinformatics cluster, the Computational Life Science cluster (CLiC) at the Chemical Biology Centre (KBC), which encompass more than 30 researchers working together from six different departments. CLiC will stimulate and advance our already world-leading experimental research in forest biotechnology, by providing the missing link in informatics and modelling.
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- CHIMICA ACTA, 13-24:791
- Bylesjö M, Nilsson R, Srivastava V, Grönlund A, Johansson, AI, Jansson S, Karlsson J, Moritz T, Wingsle G, Trygg J, (2013). Integra- ted Analysis of Transcript, Protein and Metabolite Data to Study Lignin Biosynthesis in Hybrid Aspen, J. Proteome Res. 2009, 8, 199-210
- Bylesjö, M., D. Eriksson, M. Kusano, T. Moritz and J. Trygg, (2007). Data integration in plant biology: the O2PLS method for
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- Srivastava V, Obudulu O, Bygdell J, Löfstedt T, Rydén P, Nilsson R, Ahnlund M, Johansson A, Jonsson P, Freyhult E, Qvarnström J, Karlsson J, Melzer M, Moritz T, Trygg J, Hvidsten TR and Wingsle G, (2003) OnPLS integration of transcriptomic, proteomic and metabolomic data reveals multi-level oxidative stress responses in the cambium of transgenic hipI- superoxide dismutase Populus plants , BMC Genomics, 14:893
- Trygg, J. and S. Wold, (2002). Orthogonal projections to latent structures (O-PLS), Journal of Chemometrics, 16(3), p:119-128.