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Key Words genome-wide high-throughput experiments, protein-protein interaction networks, regulatory networks, integration and prediction, network topology
Abstract One way to understand cells and circumscribe the function of proteins is through molecular networks. These networks take a variety of forms including webs of protein-protein interactions, regulatory circuits linking transcription factors and targets, and complex pathways of metabolic reactions. We first survey experimental techniques for mapping networks (e.g., the yeast two-hybrid screens). We then turn our attention to computational approaches for predicting networks from individual protein features, such as correlating gene expression levels or analyzing sequence coevolution. All the experimental techniques and individual predictions suffer from noise and systematic biases. These problems can be overcome to some degree through statistical integration of different experimental datasets and predictive features (e.g., within a Bayesian formalism). Next, we discuss approaches for characterizing the topology of networks, such as finding hubs and analyzing subnetworks in terms of common motifs. Finally, we close with perspectives on how network analysis represents a preliminary step toward a systems approach for modeling cells.
INTRODUCTION
An important idea emerging in postgenomic biology is that the cell can be viewed as a complex network of interacting proteins, nucleic acids, and other biomolecules (1, 2). Similarly complex networks are also used to describe the structure of a number of wide-ranging systems, including the Internet, power grids, the ecological food web, and scientific collaborations. Despite the seemingly vast differences among these systems, they all share common features in terms of network topology (3-11). Therefore, networks may provide a framework for describing biology in a universal language understandable to a broad audience.
Many fundamental cellular processes involve interactions among proteins and other biomolecules. Comprehensively identifying these interactions is an important step toward systematically defining protein function (2, 12) because clues about the function of an unknown protein can be obtained by investigating its interaction with other proteins of known function.
A biomolecular interaction network can be viewed as a collection of nodes (representing biomolecules), some of which are connected by links (representing interactions). There are many classes of molecular networks in a cell, each with different types of nodes and links. We list a representative subset below:
* Protein-protein physical interaction networks. Here nodes represent proteins, and links represent direct...