"Gene expression in living cells is a most intricate molecular process, occurring in stages, each of which is regulated by a diversity of mechanisms. Among the various stages leading to gene expression, only transcription is relatively well understood, thanks to Genomics and bioinformatics. In contrast to the vast amounts of genome-wide data and a growing understanding of the structure of networks controlling transcription, we still lack quantitative, genome-wide knowledge of the mechanisms underlying regulation of mRNA degradation and translation. Among the unknowns are the identity of the regulators, their kinetic modes of action, and their means of interaction with the sequence features that make-up their targets; how these target combine to produce a higher level ""grammar"" is also unknown. An important part of the project is dedicated to generating genome-wide experimental data that will form the basis for quantitative and more comprehensive analysis of gene expression. Specifically, the primary objectives of our proposed research plan are: 1) to advance our understanding of the transcriptome, by deciphering the code regulating mRNA decay 2) to break the code which controls protein translation efficiency 3) to understand how mRNA degradation and translation efficiency determine noise in protein expression levels. The proposed strategy is based on an innovative combination of computational prediction, synthetic gene design, and genome-wide data acquisition, all culminating in extensive data analysis, mathematical modeling and focused experiments. This highly challenging, multidisciplinary project is likely to greatly enhance our knowledge of the various modes by which organisms regulate expression of their genomes, how these regulatory mechanisms are interrelated, how they generate precise response to environmental challenges and how they have evolved over time."
Field of science
- /natural sciences/mathematics/applied mathematics/mathematical model
- /natural sciences/biological sciences/genetics and heredity/genome
- /natural sciences/computer and information sciences/data science/data analysis
Call for proposal
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