Dynamic covariation between gene expression and proteome characteristics

Background: Cells react to changing intra- and extracellular signals by dynamically modulating complex biochemical networks. Cellular responses to extracellular signals lead to changes in gene and protein expression. Since the majority of genes encode proteins, we investigated possible correlations between protein parameters and gene expression patterns to identify proteome-wide characteristics indicative of trends common to expressed proteins. Results: Numerous bioinformatics methods were used to filter and merge information regarding gene and protein annotations. A new statistical time point-oriented analysis was developed for the study of dynamic correlations in large time series data. The method was applied to investigate microarray datasets for different cell types, organisms and processes, including human B and T cell stimulation, Drosophila melanogaster life span, and Saccharomyces cerevisiae cell cycle. Conclusion: We show that the properties of proteins synthesized correlate ...

• Type: Journal
• Year: 2005
• Where: BMCBI
• Authors: Mansour Taghavi Azar Sharabiani, Markku Siermala, Tommi O. Lehtinen, Mauno Vihinen
• Keywords: BMCBI 2005, Extracellular Signals, Gene Expression, Protein