302 CATALYZING INQUIRY
whose behavior can be analyzed. Such modules would be building blocks that researchers could use to
build functionality, understand controllable aspects, and identify points of failure.
- Data acquisition. Simulation models are data-intensive, and today there are relatively few sys-
tems with enough quality data to create highly detailed models of cellular function. It will be important
to develop ways of measuring many more aspects of internal cellular state, and in particular, new
techniques for measuring rates of processes and biochemical reactions in situ in living cells will be
necessary. Besides additional reporter molecules, selective fluorescent dyes, and so on, a particular need
is to develop good ways of tracking cellular state at different points in time, so that cellular dynamics
can be better understood. Large volumes of data on reaction rates will also be necessary to model many
cellular processes. - Integrative tools. Because cellular function is so complex, researchers have used a variety of data
collection techniques. Data from multiple sources—microarrays, protein mass spectroscopy, capillary
and high-pressure chromatographies, high-end fluorescence microscopy, and so on—will have to be
integrated—and are indeed required—if validated, high-fidelity cellular models are to be built. More-
over, because existing models and simulations relevant to a given cell span multiple levels of organiza-
tional hierarchy (temporal, spatial, etc.), tools are necessary to facilitate their integration. With such
tools at the researcher’s disposal, it will be possible to develop complex models rapidly, assembling
molecular components into modules, linking modules, computing dynamic interactions, and compar-
ing predictions to data.
Finally, despite the power of cellular modeling and simulation to advance understanding, models
should not be regarded as an end product in and of themselves. Because all models are unfaithful to the
phenomena they represent in some way, models should be regarded as tools to gain insight and to be
used in continual refinement of our understanding, rather than as accurate representations of real
systems, and model predictions should be taken as promising hypotheses that will require experimental
validation if they are to be accepted as reliable.
The discussion above suggests that many researchers will have to collaborate in the search for an
integrated understanding. Such coordinated marshaling of researchers and resources toward a shared
goal is a common model for industry, but this multi-investigator approach is new for the academic
environment. Large government-funded projects such as the Alliance for Cellular Signaling (discussed
in Chapter 4) or private organizations like the Institute for Systems Biology^3 are the new great experi-
ments in bringing a cooperative approach to academic biology.
Still more ambitious—probably by an order of magnitude or more—is the notion of simulating the
behavior of a multicelled organism. For example, Harel proposes to develop a model of the Caenorhabditis
elegans nematode, an organism that is well characterized with respect to its anatomy and genetics.^4
Harel describes the challenge as one of constructing “a full, true-to-all-known-facts, 4-dimensional,
fully animated model of the development and behavior of this worm... , which is easily extendable as
new biological facts are discovered.”
In Harel’s view, the feasibility of such a model is based on the notion that the complexity of
biological systems stems from their high reactivity (i.e., they are highly concurrent and time-intensive,
exhibit hybrid behavior that is predominantly discrete in nature but with continuous aspects as well,
and consist of many interacting, often distributed, components). The structure of a reactive system may
itself be dynamic, with its components being repeatedly created and destroyed during the system’s life
span. Harel notes:
(^3) See http://www.systemsbiology.org/home.html.
(^4) D. Harel, “A Grand Challenge for Computing: Towards Full Reactive Modeling of a Multi-Cellular Animal,” European Asso-
ciation for Theoretical Computer Science (EATCS) Bulletin, 2003, available at http://www.wisdom.weizmann.ac.il/~dharel/
papers/GrandChallenge.doc.