The Biocomplexity workshop series aims to be broader in scope and more interdisciplinary than other workshops and conferences in this area, while each workshop remains focused on a clearly defined problem. Biocomplexity VII will bring together researchers in many disciplines (including experimental and theoretical biology, biophysics, engineering, mathematics and computer science) to discuss current and future problems in the reconstruction, kinetics and function of biological networks. While numerous workshops and scientific meetings have addressed the topology of biological networks, network dynamics and the relation of topology to dynamics, few have focused on the reconstruction of the biochemical networks from experimental data, which is one of the most important problems in this area.

The functions of uncharacterized proteins have usually been inferred on the basis of sequence similarities, common structural motifs, gene order, gene fusion events, or similarities in gene expression. Recently developed mathematical and computational methods predict function based on the role of genes in networks. These methods allow us to predict functions for proteins independent of homologies in structure or sequence and provide a way to characterize proteins that have not yet been studied, using published biological data from high-throughput technologies.

High throughput experimental assays play a major role in the current shift from reductionist to systems approaches to biological and biomedical problems. The data sets these experiments generate promise to identify the components and interactions of regulatory biochemical networks. Despite the current wealth of genomics, proteomics and microarray data available, we have many more questions than answers about the function of genes and proteins and their downstream effects on the behavior of cells or organisms. We increasingly require computational approaches suited to the analysis of these data sets, in particular techniques which require little prior knowledge of the chemical interactions involved. The Biocomplexity VII workshop aims to bring together specialists in a broad array of methodologies to see how they can combine to explicate the functions of genes and proteins in a network context.

The workshop will foster the creation of computational and mathematical frameworks to infer the network architectures of cells in a massively parallel computing environment. This framework will include techniques to integrate data and to explore millions of "what if" hypotheses about the functions of genes and proteins within pathways. It will bring experimentalists and modelers and engineers and basic researchers together (people who would not normally attend the same conference) because such cross fertilization should improve our understanding of the fundamental biology of network dynamics, lead to more useful models and engineering techniques, initiate new modeling efforts, promote collaborations between experimentalists and modelers, transfer best practice between sub-disciplines and encourage more holistic approaches to problem solving. We have already than twelve confirmed speakers from the USA and Europe and anticipate a total participation of about one hundred.

The methodologies the workshop will discuss will apply to any organism, including humans, where only three to five percent of genes have identified functions. Understanding the function of genes and proteins in a network context, will improve our ability to predict and control their responses to internal and external perturbations. The workshop will include a panel to discuss and report on promising future research foci in this area.

The workshop will include a significant educational component directed at graduate students and junior scientists, especially those not currently involved in modeling complex biochemical networks, but interested in learning about open problems, methodologies and opportunities. As part of our outreach effort we will sponsor a public lecture for nonscientists and interested members of the community at large.

Based on our experience in past workshops, we anticipate very substantial participation by researchers and students from outside the field. The workshop represents an excellent opportunity to attract new researchers to both experiment and modeling in these important areas.

Beginning with Biocomplexity V, we have published conference proceedings in a major journal.