CSIRO is helping bioscience researchers get the most out of their experiments.
Bioinformatics can help identify commercially valuable traits that effect the quality of end-products.
Statistical bioinformatics for agribusiness
CSIRO uses statistics, mathematics and informatics to help understand biological features or 'traits' that are important to agribusiness.
- 30 September 2009 | Updated 14 October 2011
- Consulting for industry
- Measuring and modelling complex traits and end-product qualities
- Analysis of massively multivariate data
- Current projects
Advances in agricultural research have resulted in massive increases in the volume and variety of agricultural data.
Analysing this data and extracting its full value has created a wave of information-specific research challenges.
CSIRO is solving these challenges using mathematical and information sciences.
Consulting for industry
We provide consulting services to industry to support research into commercially important agricultural traits and also work with imaging technology experts to deliver integrated solutions to agribusiness.
Our areas of expertise include:
We provide consulting services to industry to support research into commercially important agricultural traits.
- experimental design for efficient high-throughput bioscience
- developing information management systems for large-scale bioscience, tailored to research needs
- measuring and modelling complex phenotypes and end-product qualities
- analysis of massively multivariate data.
Measuring and modelling complex traits and end-product qualities
Important agricultural traits such as grain hardness or durum vitreousness can be difficult to quantify, as can end-product attributes like baking quality, dough flow qualities, and wine flavour and aroma.
We use mathematics and statistics to enable more objective measurement and understanding of these traits.
We have also developed computational blending methods to simulate the properties of mixtures of grain without actually having to mix real grain.
Analysis of massively multivariate data
Modern bioscience experiments often generate the sort of data where the number of measurements of each sample is much greater than the number of samples. These ‘massively multivariate’ datasets are unable to be analysed by traditional statistical methods.
We offer statistical technologies to help researchers explore this data and identify small subsets of measurements that are predictive of important phenotypes.
Current projects
Our current projects include:
Find out more about CSIRO Mathematical & Information Sciences.
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Fast facts
- Advances in agricultural research have resulted in massive increases in the volume and variety of agricultural data
- CSIRO provides statistical consulting services to industry to support research into commercially important agricultural traits
- Areas of expertise include experimental design, information management systems and using mathematics and statistics to understand complex traits and end-product qualities
