Similar Datasets
Project description:In this study, we design and apply a DNA expression array for Aspergillus nidulans in combination with legacy data to form a comprehensive gene expression compendium. We apply a guilt-by-association-based analysis to predict the extent of the biosynthetic clusters for the 58 synthases active in our set of experimental conditions. A comparison with legacy data shows the method to be accurate in 13 out of 16 known clusters and nearly accurate for the remaining three. Furthermore, we apply a data clustering approach, which identifies cross-chemistry between physically separate gene clusters (super clusters), and validate this both with legacy data and experimentally by prediction and verification of a new supercluster consisting of the synthase AN1242 and the transferase AN11080. This normally requires extensive sets of combinatorial gene deletions. We have employed A. nidulansfor our method development and validation due to the wealth of available biochemical data, but the method can be applied to any fungus with a sequenced and assembled genome, thus supporting further secondary metabolite pathway elucidation in the fungal kingdom. RNA was sampled from stabbed cultures on three different solid agar-based media (CYAs, YES, CYA) after 4, 8 or 10 days, resulting in a total of 8 samples.
2013-04-04 | E-GEOD-39993 | biostudies-arrayexpress
Project description:Full legacy gene expression dataset run internally Gene expression data from various panels and experiments was collected, QC'd and normalised in tandem to provide a full summary dataset of the cell line expression data generated internally
2014-04-28 | E-GEOD-57083 | biostudies-arrayexpress
Project description:In this study, we design and apply a DNA expression array for Aspergillus nidulans in combination with legacy data to form a comprehensive gene expression compendium. We apply a guilt-by-association-based analysis to predict the extent of the biosynthetic clusters for the 58 synthases active in our set of experimental conditions. A comparison with legacy data shows the method to be accurate in 13 out of 16 known clusters and nearly accurate for the remaining three. Furthermore, we apply a data clustering approach, which identifies cross-chemistry between physically separate gene clusters (super clusters), and validate this both with legacy data and experimentally by prediction and verification of a new supercluster consisting of the synthase AN1242 and the transferase AN11080. This normally requires extensive sets of combinatorial gene deletions. We have employed A. nidulansfor our method development and validation due to the wealth of available biochemical data, but the method can be applied to any fungus with a sequenced and assembled genome, thus supporting further secondary metabolite pathway elucidation in the fungal kingdom.
2013-04-04 | GSE39993 | GEO
Project description:Full legacy gene expression dataset run internally
2014-04-28 | GSE57083 | GEO