From components to regulatory motifs in signalling networks

Abstract

The developments in biochemistry and molecular biology over the past 30 years have produced an impressive parts list of cellular components. It has become increasingly clear that we need to understand how components come together to form systems. One area where this approach has been growing is cell signalling research. Here, instead of focusing on individual or small groups of signalling proteins, researchers are now using a more holistic perspective. This approach attempts to view how many components are working together in concert to process information and to orchestrate cellular phenotypic changes. Additionally, the advancements in experimental techniques to measure and visualize many cellular components at once gradually grow in diversity and accuracy. The multivariate data, produced by experiments, introduce new and exciting challenges for computational biologists, who develop models of cellular systems made up of interacting cellular components. The integration of high-throughput experimental results and information from legacy literature is expected to produce computational models that would rapidly enhance our understanding of the detail workings of mammalian cells.

Figure 1

Integration of the high-throughput experimental results with knowledge gained in the past four decades is expected to breed computational models that would rapidly enhance our understanding of the detailed workings inside mammalian cells.

Figure 2

The process of discovering how bio-molecules work together to perform the functions of a cell, is analogous to solving a jigsaw puzzle. The pieces of this puzzle were created from a 3D VRML image. The image was automatically created from interactions extracted from literature that describe the signalling network from norepinephrine to reach intracellular components in five steps of coupled interactions.