Abstract
We applied Inductive Process Modeling (Langley et al., in press) to induce biological process models from background knowledge and temporal gene expression data relating to the regulation of bacterial photosynthesis. Labiosa et al. (2003) studied the regulation of all of the genes in the Cyanobacterium Synechocystis sp. 6803. They simulated the natural day/night light cycle in a continuous culture cyclostat, and extracted samples at 2AM, 8AM, 10AM, noon, 2PM, 6PM, and midnight. Whole-cell RNA from these samples was converted to cDNA and hybridized to DNA microarrays, thereby measuring the abundance of RNA transcripts for all the genes in the organism at the selected times. Many of the photosynthesis-related RNAs show low abundance at night and increase rapidly when the sun rises, but these also exhibit an ‘M-shaped’ pattern with a substantial decrease at noon.
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Saito, K., George, D., Bay, S., Shrager, J. (2003). Inducing Biological Models from Temporal Gene Expression Data. In: Grieser, G., Tanaka, Y., Yamamoto, A. (eds) Discovery Science. DS 2003. Lecture Notes in Computer Science(), vol 2843. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39644-4_47
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DOI: https://doi.org/10.1007/978-3-540-39644-4_47
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