It is generally recognized that the field of biology is undergoing a
revolution, spearheaded by the rapid advances in genomics, proteomics, and
small molecule high throughput screening technologies. Data can be generated
more rapidly than it can be assimilated, and a central issue is to decide
which experiments to perform and how to extract their information content. Can
a focus on CDFN themes help in the discovery of high-level structure and
thus suggest new priorities for pursuing and organizing data?
Two broad themes are emerging relative to CDS: (i) unraveling nature's complex
bio-networks and the mysteries of how they operate, and (ii) the introduction
of control concepts to redirect the function and utility of bio-systems for a
variety of practical purposes. Both of these goals
may be recognized as intimately involving issues of feedback control, system
identification, and model reduction. However, the challenges involved are not
simply analogous to those in engineering, as bio-systems operate under unusual
conditions, including strong stochasticity, high specificity, high robustness,
and an ability to rapidly adapt. New conceptual, mathematical, and laboratory
tools will be needed to unravel these mysteries.
We plan to complement the already substantial efforts on understanding the
complex molecular biology inside the cell (including active ongoing work at
Caltech, Princeton, and UCSB in systems biology) and mainly focus on higher
level operating principles of biological systems. We provide a brief summary
of the research opportunities in two such areas: cell-to-cell communications
and integrative biology.
In contrast to the cells and organisms discussed in the previous section,
emergent properties of aggregations and ecosystems inherently reflect
selection mechanisms which act on multiple levels, and primarily on scales
well below that of the system as a whole. In this section, we describe our
plans for new collaborations which combine the top down approach of Carlson
and Doyle with the individual-based approaches of Naomi Leonard, Simon Levin
and Roger Nisbet. Primary case studies will include the evolution of
cooperation and quorum-sensing in microbial systems (Bonnie Bassler, Jared
Leadbetter), the ecology and evolution of animal aggregations, and emergent
patterns of stoichiometry and resource use in marine and terrestrial
ecosystems.
While some of the previous sections have presented research topics that are
localized at a fairly specific physical scale (molecular, cellular or
organismal), we have seen that research in fields such as forest fire
management and ecosystem dynamics addresses inherently multiscale
issues. Modern geophysics bridges an even wider range of scales, cutting
across microscopic and macroscopic realms of modeling natural
phenomena. Accordingly, preliminary investigations have identified areas of
essential overlap with the CDFN research themes of interconnection,
stability, and robust emergent phenomena.
The physical instabilities that underlie the complexity of earthquakes, as
well as challenges associated with multiscale modeling and uncertainty
management for geophysical phenomena, are clearly amenable to CDS-inspired
methodology. New reduced order models are emerging for noncrystalline solids,
soils, and related geophysical materials which explain complex physical
behaviors not properly understood by conventional phenomenological
techniques. New tools aimed at developing more rigorous accounting of feedback
and uncertainty would be of enormous practical impact in assessing seismic
hazards.
