Title: e-Photosynthesis - A system biology platform for guiding improvement in photosynthesis and crop productivity (research with Eric de Sturler and Steve P. Long)

Abstract: Theoretical analysis has shown that photosynthesis is the only major route for further improvement of crop productivity. Potential targets for improving photosynthesis include modification of photosynthetic metabolisms, anatomical structures of photosynthetic apparatus, and canopy structures. Given thousands even millions of permutations to test, identifying targets to improve photosynthesis using experimental approach is time consuming, costly, and impractical. The e-Photosynthesis research platform aims to integrate the genomic, proteomic, and metabolomic information, together with the microscopic structure of leaf and the macroscopic structure of canopy to predict the efficiency of photosynthesis under different environmental conditions for different natural or genetically modified plants. It can also be used to test hypothesis related to photosynthesis. The presentation will describe the basic structure of e-Photosynthesis, the methodology used to build e-Photosynthesis, supporting algorithms for apply e-Photosynthesis in research.

Bio: Xinguang Zhu received his MS degree from Institute of Botany, Chinese Academy of Sciences in 1999. He received his Ph.D. from UIUC in 2004 with a thesis titled "Computational Approaches to Guiding Biotechnological Improvements in Crop Photosynthetic Efficiency." His main research interest is to accurately simulate the photosynthetic and associated metabolisms in natural environmental conditions at different time scales, study the system properties of the photosynthesis system, and explore ways to increase photosynthesis yield. He is especially interested in combining the large amount of genomic, microarray, proteomics, and metabolomics data with modeling techniques to improve understanding about photosynthesis.