Bioinformatics tools will need to have the potential to confirm functionality changes of the underlying ecosystem (metatranscriptomics). Trend data analysis on different types of data are currently being performed to compare and match data sets where possible, leading to p-value estimations that can be evaluated and validated. This is achieved by performing additional functional metagenomics. Particular attention is being paid to the design of a correct sampling strategy and frequency.
This project, which is based at Applied Maths in Belgium, is focussed on applying and validating these tools using the metagenomics data of Caulerpa-associated bacteria, which has close links to project 6 based at the University of Ghent. Research underway will look at whether the algorithms and tools being developed can integrate with the existing BioNumerics software suite or will have to be developed as a standalone application. The integration or linking with a cloud or cluster environment is anticipated given the expected size of the data samples.
Johannes Schicker has been appointed PhD researcher to this project. His work will focus on generating metatranscriptomics data for the biological material relating to the work of project 6. For a time, therefore, Johannes will be on secondment at the University of Ghent, and also VIB where projects 14 and 15 will develop bioinformatics tools specifically targeted at Eukaryotic (algal) data.
Overall, this project will aim to provide an improved insight into sample strategy management, along with software that can match multiple trend data analyses on different types of data collected on same samples: (partial) metagenomic sequences, compositional information and functional modifications over time.