1. The Alpha Project: a model system for systems biology research
- Author
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Yu, R. C., Resnekov, O., Abola, A. P., Andrews, S. S., Benjamin, K. R., Bruck, J., Burbulis, I. E., Colman-Lerner, A., Endy, D., Gordon, A., Holl, M., Lok, L., Pesce, C. G., Serra, E., Smith, R. D., Thomson, T. M., Tsong, A. E., and Brent, R.
- Subjects
Saccharomyces cerevisiae Proteins ,Proteome ,Research ,Saccharomyces cerevisiae ,Cell Biology ,Models, Biological ,Pheromones ,Article ,Modeling and Simulation ,Protein Interaction Mapping ,Genetics ,Computer Simulation ,Molecular Biology ,Signal Transduction ,Biotechnology - Abstract
One goal of systems biology is to understand how genome-encoded parts interact to produce quantitative phenotypes. The Alpha Project is a medium-scale, interdisciplinary systems biology effort that aims to achieve this goal by understanding fundamental quantitative behaviours of a prototypic signal transduction pathway, the yeast pheromone response system from Saccharomyces cerevisiae. The Alpha Project distinguishes itself from many other systems biology projects by studying a tightly bounded and well-characterised system that is easily modified by genetic means, and by focusing on deep understanding of a discrete number of important and accessible quantitative behaviours. During the project, the authors have developed tools to measure the appropriate data and develop models at appropriate levels of detail to study a number of these quantitative behaviours. The authors have also developed transportable experimental tools and conceptual frameworks for understanding other signalling systems. In particular, the authors have begun to interpret system behaviours and their underlying molecular mechanisms through the lens of information transmission, a principal function of signalling systems. The Alpha Project demonstrates that interdisciplinary studies that identify key quantitative behaviours and measure important quantities, in the context of well-articulated abstractions of system function and appropriate analytical frameworks, can lead to deeper biological understanding. The authors’ experience may provide a productive template for systems biology investigations of other cellular systems.
- Published
- 2008
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