Network Biology: Understanding the Cell's Functional Organization
Barabási et al. (2004): Network Biology: Understanding the Cell's Functional Organization
The motivation for this paper is that:
[I]t is increasingly clear that a discrete biological function can only rarely be attributed to an individual molecule. Instead, most biological characteristics arise from complex interactions between the cell's numerous constituents, such as proteins, DNA, RNA and small molecules. Therefore, a key challenge for biology in the twenty-first century is to understand the structure and the dynamics of the complex intercellular web of interactions that contribute to the structure and function of a living cell. [...] Various types of interaction webs, or networks, (including protein–protein interaction, metabolic, signalling and transcription-regulatory networks) emerge from the sum of these interactions. None of these networks are independent, instead they form a 'network of networks' that is responsible for the behaviour of the cell.
Network research in general, including graph theory, has led to some interesting results that can also be applied to biological networks:
[T]he architectural features of molecular interaction networks within a cell are shared to a large degree by other complex systems, such as the Internet, computer chips and society. This unexpected universality indicates that similar laws may govern most complex networks in nature, which allows the expertise from large and well-mapped non-biological systems to be used to characterize the intricate interwoven relationships that govern cellular functions.
The authors "explore the specific biological details and the evolutionary origins that contribute to the formation of cellular networks, and the impact of the network structure on experimentally observable function and behavioural features" with the goal being "to help understand the large-scale characteristics of cellular networks, complementing recent excellent reviews on the function of small genetic circuits" . Regarding the nature of biological networks the authors have found out the following:
The analysis of the metabolic networks of 43 different organisms from all three domains of life (eukaryotes, bacteria, and archaea) indicates that the cellular metabolism has a scale-free topology, in which most metabolic substrates participate in only one or two reactions, but a few, such as pyruvate or coenzyme A, participate in dozens and function as metabolic hubs.
The paper continues with a section on motifs, modules and hierarchical networks. Then come a section on network robustness and one on links. Finally, the authors conclude:
Instead of chance and randomness, we have found a high degree of internal order that governs the cell's molecular organization. Along the way, a new language has been created, which allows the cell's molecular makeup to be discussed as a network of interacting constituents, and to spot and quantify the interplay between behaviour, structure and function. The cell can be approached from the bottom up, moving from molecules to motifs and modules, or from the top to the bottom, starting from the network's scale-free and hierarchical nature and moving to the organism-specific modules and molecules. In either case, it must be acknowledged that structure, topology, network usage, robustness and function are deeply interlinked, forcing us to complement the 'local' molecule-based research with integrated approaches that address the properties of the cell as a whole. [...] The breathtaking advances of modern molecular reductionist biology are starting to pay clinical dividends, from the diagnosis of selected leukaemias on a molecular level, to their molecularly targeted treatment with, for example, receptor tyrosine kinase inhibitors. [...] What is lacking is a well-developed framework in which such clinical data can be used to identify modules that are pathologically altered in a given disease state. Once such a framework is developed, the targeted pharmaceutical modification (such as rewiring) of diseased modules will surely follow.