MCB supports research on complex biological systems from the individual biomolecule to the cellular level across a wide range of organisms. Complex biological questions require the tools of information science and computation to study the molecular mechanisms by which genetic information is expressed and the mechanisms by which living cells communicate and respond to environmental signals. Such questions increasingly require collaborations with the physical sciences, mathematics, computer science, and engineering.

Example: Computational Simulation of Gene Networks. Complex interactions of gene networks are responsible for many critical biological processes. A quantitative, mechanistic model of a functioning gene network has been developed based on a computer simulation. The test system was the gene network responsible for generating the segmented body plan of the fruit fly. The computer software takes a non-mathematical description of a gene network, converts it into a set of differential equations, and then solves the equations to reveal how concentrations of the various network components change over time to produce the biological pattern. This software will provide a new tool to study gene networks that control other biological processes. It will also be useful for teaching. A Small Grant for Exploratory Research provided the seed funding for this successful project.

Very recently the availability of the genome sequences of organisms has made possible a new approach to the study of biology, broadly referred to as "functional genomics." Functional genomic approaches to biological problems involve the use of information encoded in the genome of an organism. These genome-enabled approaches have revolutionized biological research.

The FY 2002 Budget Request includes funding in the following areas:

• "2010 Project": The MCB Subactivity will enhance support for research to determine the functions of all the genes of the model flowering plant, Arabidopsis, as part of the "2010 Project." This research takes advantage of the newly available complete genome of Arabidopsis.
  
  
• Biocomplexity in the Environment (BE): The MCB Subactivity will emphasize genome-enabled microbial research aiming to identify and characterize the biology of microorganisms across the range of Earth's environments. This research is part of the Microbe Project. It builds on the prior Life in Extreme Environments (LExEn) effort, complements the ongoing Microbial Observatories effort, and lays the groundwork for understanding the role of the diversity of Earth's microbes in biocomplexity, particularly in shaping and sustaining the environment.
  
  
• Genome-Enabled Science: Genomics and modern molecular tools have opened windows on worlds of biology hardly imagined until recently. Indeed, well over half of new research projects proposed in the MCB Subactivity involve the use of genomics. Examples include analysis of microbial genomes to discover new organisms, determine their genetic capabilities, and study the diversity of metabolic functions that enable them to occupy diverse habitats. Genome-enabled research also seeks to answer questions such as which sets of genes are turned on or off in response to signals from other organisms or from the environment, and how multiple metabolic pathways are integrated to produce end-products needed at particular times in the life of a cell or an organism. The MCB investment will advance genome-enabled research to promote fundamental understanding of the diversity of organisms making up the natural world and will contribute to applications in biotechnology, agriculture, and the environment.
  
  
• Systems Biology: Theoretical, computational, and mathematical modeling approaches are playing increasingly important roles in all areas of the molecular and cellular biosciences - in formulating and testing physical and mathematical models of the structure and function of complex molecules, macromolecular complexes, and cellular processes; in modeling and simulation of the regulation and relationships of cellular and metabolic processes; in analysis of genome data; and in other applications in genetics and functional genomics. MCB will encourage integration of these approaches with experimental research on molecules and cells in a wide range of biological systems.