Biology harbors hidden complexity

By Kimberly Patch, Technology Research News

Complicated systems are all around us. It takes hundreds of networked computers to keep a Boeing 777 aloft and thousands of interrelated genes to form and maintain a living being. Most of the time, however, the systems don't look so complicated.

This is because the complexity is hidden in the networks of interactions carried out by the basic components that make up the systems.

Researchers from the California Institute of Technology and the University of Michigan who are attempting to unravel the mathematical rules of network complexity have shown that there are similarities in this mid-level networking behavior of engineered and natural systems.

"I was struck by how much the engineering-level design [of biological systems] looks like engineering, despite the fact that the components were completely different and the system-level behavior might be very different," said John Doyle, a professor of control and dynamical systems, bioengineering, and electrical engineering at the California Institute of Technology.

Finding the mathematics behind the complexity could help unravel biological mysteries and maintain the world's increasingly interrelated networks.

This type of complexity in biological systems is often hidden in idealized laboratory settings, said Doyle. This is because what biology gains from the complexity is robustness, or an ability to deal with fluctuations in the environment that aren't present in the lab. The same is true for an airplane in a simple wind tunnel experiment, he said.

Both artificial and biological systems have high-level behavior that is relatively straightforward. In a network, for example, the behavior might be transferring a file, and in the human body maintaining a certain temperature.

And at the lowest level, both types of systems are made of just a few basic building blocks. All of computing is based on a small set of basic logic operations. Similarly, most organisms use the same codons, which are sets of three bases that make up the logical units of DNA. Codons specify the amino acids needed to build the many types of proteins that work together to carry out life's functions.

"The simplicity is at the high-level behavior and at the lowest levels, but the layers in between are just not simple. That doesn't mean they don't obey principles," said Doyle.

The researchers found that the same principles cover both artificial and biological systems. "The organizational... principles that govern the layers of protocols, modules and feedback that lie in between are far more alike than is commonly realized," said Doyle.

The evolution of the Internet, for instance, shows parallels to biological evolution "after you see how to look at things the right way," said Doyle. Protocols, the software programs that lay out the rules and regulations of the network, are the hidden layer of complexity that keeps the network running relatively smoothly, he said.

In addition to this common structure of simple building blocks, simple results and mid-level complexity, artificial and biological networks both show robustness, or an ability to adapt, according to Doyle.

Robustness is what allows biological organisms to, for instance, grow in almost every environment on earth, including hydrothermal vents 2,600 meters under the ocean, where temperatures are near boiling, the pressure is 3,821 pounds per square inch and the single-cell microbe Methanococcus jannaschii thrives. This robustness is manifest in the number of genes, or sequences of codons, organisms have. Even though less than 300 genes are essential to an E. coli bacteria, it contains about 4,000, said Doyle.

Along with robustness, however, the complexity brings a type of fragility, Doyle said. Although large, multicellular organisms are unaffected by the death of individual cells, certain malfunctions in the middle-layer control systems of one or a few cells can balloon into fatal autoimmune diseases or cancer, he said. These failures are due to a cascade effect among the complicated connections of that layer.

Complicated mechanical systems are also prone to extreme fragility, said Doyle. A small change in an otherwise intact control system could cause wild, catastrophic behavior. A relatively simple software bug, for example, could turn a collision-avoidance system into a collision-seeking system, according to Doyle.

The same is true of the network of networks that make up biological ecosystems, said Doyle. Epidemics, starvation, forest fires, and takeovers by exotic species typically involve small initiating perturbations that cascade into network and system-wide events, he said.

Cascading failures are relatively rare in nature, however, because systems that have them frequently die off, said Doyle. "If they were not rare, we would not exist," he said.

Artificial networks of networks are also prone fragility, said Doyle. The perpetrators of the September 11 disaster were able to cause so much damage because they tapped into networks to cause cascading failures, said Doyle. The hijackers used one complicated system -- an airplane -- to attack another complicated system -- a building. The effect went even further because the World Trade Center towers were key components of yet another network, the global financial markets, said Doyle. "Only by using networks against themselves can such large events occur," he said.

The researchers are currently refining the theory by exploring similarities in the mathematics of real-world problems that may not at first appear related. "The math underlying our theories of the Internet and biology may have deep similarities, but that won't necessarily be apparent" to experts in those individual areas, Doyle said.

The concepts already apply to the control software of complicated systems like military and commercial aircraft, manufacturing process control and smart weapons, said Doyle. "Modern aircraft and automobiles are designed with billion-dollar computer-aided design systems, and are maintained with vast networks of diagnostic software. This is not just any old software, but depends on lots of deep engineering understanding of how the networks, and not just the components of the systems, work," said Doyle.

They can also be applied, however, to unravel the secrets of biology by reverse-engineering complex biological systems, and to improve many other artificial networks, said Doyle.

The emphasis in biology is now shifting from identifying individual components and molecules to the study of the vast networks that biological molecules create, which regulate and control life, he said. "We shouldn't expect biology and medicine to be simpler than [engineered systems], and we will need similar systems-level theory and software," he said.

In addition, our daily lives are increasingly dominated by our interactions with a wide variety of networks, including, energy, health, financial, political, and data networks, which in turn interact with the local and global environments, said Doyle.

As these networks are increasingly integrated there is both unprecedented promise and unprecedented risk, he said.

Currently, "a lightning strike in one state can cause a power outage in another state. A hacker on another continent can deny Web access. A single firm can trigger a global financial crisis. A software bug can cause a rocket, airplane, or automobile to crash."

These catastrophic events still have limited impact because the different types of networks are fairly isolated from each other, said Doyle. As the world gets more interconnected, however, "this is changing," he said. Eventually, "everything will boil down to how well we can understand the complexity of our various networks and their interactions."

Doyle's research colleague was Marie E. Csete of the University of Michigan. They published the research in the March 1, 2002 issue of the journal Science. The research was funded by the Department of Defense (DOD), the National Science Foundation (NSF) and the National Institutes of Health (NIH).

Timeline:   Now
Funding:   Government
TRN Categories:   Biology; Engineering; Theory
Story Type:   News
Related Elements:  Technical paper, "Reverse Engineering of Biological Complexity," Science, March 1, 2002.


March 6, 2002

Page One

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Atomic cascade broadens laser

Biology harbors hidden complexity

Heat engines gain quantum afterburner

Nanotubes branch out


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