Statistical Advances in the Post-Genome Era

将为后基因组生物学和生物技术建立与生物学相关的统计基础。这些主题的具体目标包括开发准确和更有效的序列比对算法，改进模型以最大限度地提高基因表达数据分析的准确性，以及用于识别使有机体容易患病的复杂基因网络的优越统计方法。该项目将对生物信息科学(包括生物信息学)这一新的和不断发展的优先研究领域作出重大贡献。成果将包括分析和挖掘后基因组数据的新技术，并应用于生物医学和生物农业的发展

Biologically relevant statistical foundations for post-genome biology and biotechnology will be developed. Specific goals of the topics include the development of accurate and more efficient algorithms for sequence alignments, improved models to maximise the accuracy of analyses for gene expression data and superior statistical methods for identification of complex gene networks that predispose an organism to disease. The Project will make significant contributions to the new and evolving priority research area of Bioinformation Science (including bioinformatics). Outcomes will include novel techniques for analysis and mining of post-genome data, with applications to developments in Bio-medicine and Bio-agriculture