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Functional Genomics of Developing Barley Seeds

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Supplemental Material for the manuscript: N. Sreenivasulu et al., Gene expression patterns reveal tissue-specific signaling networks controlling programmed cell death and ABA-regulated maturation in developing barley seeds. The Plant Journal 47 (2): 310-327, 2006.

Functional annoation of 12000 ESTs and Differentially expressed gene set:


Visual exploration of gene expressions in developing endosperm tissue from 12K EST arrays.

Supplemental Material for the manuscript: M. Strickert, N. Sreenivasulu, U. Seiffert;
Correlation-maximizing surrogate space for visual gene expression mining and pattern identification in developing barley endosperm tissue;
BMC Bioinformatics.

The following links refer to additional material referred to in the manuscript:
  • Additional file 1 (Fig.): Additional HiT-MDS-2 embeddings for different exponentsp.
  • Additional file 2 (Tab.): List of 4824 genes with 64 centroids
  • Additional file 3 (Tab.): Table of functional categories
  • Additional file 4 (Fig.): HiT-MDS-2 embedding of gene expressions of 3031 filtered genes from developing barley endosperm at time points 4, 8, 16, 25 days after flowering. Expression levels are taken from Barley 1 Affymetrix chip. Like in Figure 2 of the manuscript, a sandglass shape is obtained for a correlation exponent of p=8. Since only four time points are considered, the four-dimensional expression vectors are very faithfully represented in the scatter plot. The corresponding regulation patterns of up-, down- and intermediate regulation are displayed in Figure S4.
  • Additional file 5 (Fig.): Gene expression profiles obtained from Barley 1 Affymetrix gene chip connected to highlighted regions of the HiT-MDS-2 gene space plot given in Figure S3. High spatial specificity is observed in the exemplary clusters 1-8 covering interesting locations in the gene space. Patterns of up- and down-regulation fall into opposite poles. Cluster number 5 shows intermediate up-regulation with quite diverse characteristic, where Pearson correlation does not yield good discrimination between peaks in the second or third temporal stage. Cluster number 3 contains genes that become active just at the last stage (day 25 after flowering).
  • Additional file 6 (Fig.): Gene expression profiles corresponding to the six subcluster groups 2a, 2b, 3a, 3b, 4a and 4b refered in Figure 3 of the manuscript. The expression profiles reflect z-score normalized log-2 values. In addition to individual gene expression curves displayed in blue, their mean and standard deviation are depicted by red lines. Highest variability is observed for intermediate regulation events in cluster 2a; yet, the overall quality of coexpression in the six clusters is represented well.
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