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
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.
Our current projects include:
Find out more about CSIRO Mathematical & Information Sciences.