
TY  - JOUR
A1  - Kennedy, Gavin C. 
A1  - Wilson, Iain W. 
T1  - Plant functional genomics: opportunities in microarray databases and data mining
JF  - Functional Plant Biology
JO  - Functional Plant Biol.
Y1  - 2004
VL  - 31
IS  - 4
SP  - 295
EP  - 314
KW  - database, data mining, eQTL, functional bioinformatics, gene expression, genomics, in-silico analysis, microarray, molecular phenotype, systems biology, transcriptomics.
UR  - https://doi.org/10.1071/FP03216 
N2  - High-throughput gene expression profiling using microarrays has given plant biologists a powerful new technology to discover gene function and understand cellular processes. Bioinformatics has rapidly developed to deliver the tools necessary to interpret this gene expression data, but opportunities to further exploit the mass of data from hundreds of experiments are becoming dependent upon the use of sophisticated database repositories. Data mining of these resources will allow plant biologists to compare and link expression profiles and experimental factors to uncover functions and processes that would not normally be visible from analysing a small set of microarray experiments. This in-silico analysis will become critical when designing new experiments and interpreting new results. Consequently microarray databases and their ongoing development are now as important to plant functional genomics as the initial microarray data capture and analysis tools. In order for plant biologists to grasp these new opportunities, an appreciation of microarray database technology and future developments in biological data integration is required. The challenge for plant functional genomics is to embrace these new technologies lest the opportunities for significant discoveries be lost. 
ER  -

