Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/80214
Title: IN SILICO MODELING AND “-OMICS” DATA ANALYSIS FOR RICE SYSTEMS AGROBIOTECHOLOGY
Authors: MEIYAPPAN LAKSHMANAN
Keywords: systems biology, rice, constraints-based modeling, omics data, abiotic stress, light signaling
Issue Date: 28-Mar-2014
Source: MEIYAPPAN LAKSHMANAN (2014-03-28). IN SILICO MODELING AND “-OMICS” DATA ANALYSIS FOR RICE SYSTEMS AGROBIOTECHOLOGY. ScholarBank@NUS Repository.
Abstract: Rice is one of the major food crops in the world, especially in Asia. Although the overall yield of rice has been increasing since the Green Revolution in 1960s, the growing population and adverse climatic changes pose huge challenges for its sustained production in the future. Moreover, several biotic and abiotic stresses such as drought, flooding and salinity a ect the rice production signi cantly.Despite several decades of research, still, a clear understanding on how the cellular phenotype of rice varies across various stress conditions remains elusive. Such situations exist even with the availability of multiple high throughput data such as metabolomics, proteomics and transcriptomics mainly due to the lack of systematic approaches. To this end, the current work aims to initiate a systems approach to characterise the rice cellular physiology under various stresses by combining the mathematical network models and highthroughput data through an integrative in silico framework.
URI: http://scholarbank.nus.edu.sg/handle/10635/80214
Appears in Collections:Ph.D Theses (Open)

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