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CoSBi Models

By John Russell

March 24, 2009 | Russell Transcript | Using computers to model living systems and to make useful predictions about their behavior is a holy grail pursued by many; yet there are far fewer seeking to go in the reverse direction and infer principles from living systems to improve computer science. Corrado Priami, president and CEO of the Centre for Computational and Systems Biology (CoSBi), a partnership between Microsoft, the Italian Government and University of Trento, is hoping to do both.

Formed just three years ago, CoSBi has grown steadily (see, “The CoSBi Show,” Bio•IT World, Dec 2006). Today it has about 25 researchers and has already developed a number of prototype tools freely available at BetaWB, Cyto-Sim, Kinfer, Snazer, and Redi.

More recently, Priami has written a short paper on “algorithmic systems biology” that will be published in Communications of ACM (Association for Computing Machinery) this June, in which he sketches his ideas on how computer science can be brought to bear on biology and vice versa. The heart of what computer science can learn from biology, he says, is parallelism and robustness.  “Computers crash too easily, they’re not naturally tolerant, while living systems are robust and adapt well to environment. Maybe we can make better software using principles from living systems,” he says.

Priami says that the convergence between computing and systems biology provides “a valuable opportunity that can fuel the discovery of solutions to many of the current challenges in both fields, moving towards an algorithmic view of systems biology.” He envisions different levels of cross fertilization between the two areas. Living systems are much more robust than current computer systems, much more adaptive to their environment. A priority—“probably of interest to our joint venture with Microsoft”—is learning how to improve the tolerance of software development. Another lesson, he suggests, might be more energy-conserving approaches to computation.

In that paper, Priami picks up the ongoing debate over whether computer science is indeed a science, and contrasts it to mathematics with which computer science is often allied in a subordinate, supportive role. He argues computation is a distinct science, in part because its operations necessarily have a physical reality while mathematics may be theoretical or solvable in the abstract. He further argues that living systems share much with computation since they too are information processing (i.e. computation) systems in which real events must occur to do the “computation.”

Borrowing from Biology

Broadly speaking, CoSBi is trying to develop a new programming language, syntax, and toolset to model and simulate living systems. Asked to distinguish his approach from companies such as Entelos, Genstruct, and Gene Network Sciences, Priami says: “We are not using mathematical tools; we are using computer science tools. There are lots of professional reasons for doing that because biological systems are highly parallel; you have thousands of interactions that happen simultaneously. Mathematical modeling is mainly an equation and it is combinatorial in size so when you have to describe all those ways in which systems can touch, it is not so suitable to model large systems.”

Priami says he is trying to produce models that are “transition-based, not state based.” State-based systems, he says, “describe the differential expressions or other quantities of variables with state changes and try to condense this into relations and [from these] infer the dynamics of the systems. We’re trying to describe not the state, but the transition from one state to another, which is exactly the way computer scientists describe the behavior of distributed programs, so programs that run on different nodes of a network, exchanging messages. It is a newer way of representing the phenomena.”

“Our approach is much more scalable. We do not have theoretical limitations to the size of the model; only technology limitations in terms of the size of the memory we can use. We aim to make models [that have], say, gene regulatory networks and metabolic networks and what people ordinarily do is look at the networks in isolation. We attempt to have the two together interacting in the same system so that we can understand how they interact together. A long term perspective is to be able to model things like immune system at a molecular level.”

Ease of use remains an issue, agrees Priami. In the next 18 months, he hopes to develop an interface to the platform that is useable by biologists. He also hopes to validate some in silico predictions in the lab and demonstrate effective crosstalk between large systems that demonstrate the scalability of CoSBi’s approach.

It should be fascinating to watch not only the systems biology tools developed by CoSBi but also to monitor how successful it is in taking ideas and techniques from living systems and incorporating them into computer science.

This article also appeared in the March-April 2009 issue of Bio-IT World Magazine.
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