Grand Challenge: In Vivo In Silico

First in the series of reviews of the Wetware-related Grand Challenges I promised; a closer look at the project In Vivo In Silico, proposed by Professor Ronan Sleep at the School of Computing Sciences, University of East Anglia, Norwich.

“In Vivo” is a Latin term commonly used in biology and medicine to refer to something that occurs within a biological organism, as opposed to “In Vitro”, meaning literally “in glass” e.g. “an egg fertilized In Vitro”. The term “In Silico” is intended to describe the third option for biological observation or experiment. The In Vivo In Silico project aims to simulate the development, cell function, sensory, interaction and overall behavior of organisms accurately enough to allow it to be used in research, adding to and sometimes even replacing the “real thing”.

Grand Challenge reviews
Here are the individual Wetware related Grand Challenge reviews:

Although the plan aims only to simulate very simple and much studied organisms, such as the Nematode worm C. elegans, this is nevertheless a very ambitious project, because of the accuracy the project aims for.

Copied from the proposal paper, the aims are “to model phenomena such as:”

    a. DEVELOPMENT from an initial fertilized cell to a full adult, at various resolution levels. An accurate model will respect knowledge about, for example: cell lineage, cell differentiation, cell lifetime, morphology, size and relation between major cellular sub-systems. Virtual experiments (e.g. moving a virtual cell during development, or making an incision) should lead to the same outcomes as real life.

    b. CELL FUNCTION and INTERACTION: the specific functions of cells should be captured in appropriate detail together with principal modes of interaction.

    c. MOTILITY and SENSORY aspects of behaviour: types of reaction to various stimuli, including neighbouring life forms; speed and nature of movement.

    d. ENVIRONMENTAL INTERACTION: interactions between organisms and the surrounding environment should be captured.

Even though the C. elegance is an extremely simple organism, this is no easy task. A simulation like this would for example have to accurately simulate the growth, division and death of every single cell in the organism’s body, from the fertilization of the egg to the organism’s death.

I wonder if that requires going as far as understanding the worm’s genome all the way down to the most fundamental functionality, or whether a less detailed simulation of each cell’s functionality will do. As far as I know, scientists are still pretty far from understanding how genomes work, even though the genomes of species ranging from C. elegans, to humans, including mice, fruit flies, rats – and just this week, Craig Venter‘s poodle, Shadow – have been sequenced.

But the project aims to do more:

    Although it by no means certain that Computer Science must follow Biology in the way it does things, the Computer Scientists may take inspiration from Biology to construct new ways of specifying complex reactive systems that construct and maintain themselves from small initial and perhaps sketchy specifications. Perhaps we can uncover some fundamental system design principles which nature uses to realise an effective �SYSTEM = NATURE + NURTURE� paradigm, creating a new generation of system design
    methodologies for complex adaptive self-maintaining systems. Theories and methods arising could give us important handles on large emerging complex systems such as the web.

I actually believe that this part of the project could be of no less value and interest. I am a true believer in highly modular systems, where simple and understandable (yet diverse and specialized) “cells” work together to create complex system. In fact I believe that many of the tasks computer science is trying to solve cannot be addressed properly with traditional computing methods. Charles C. Mann wrote an excellent article called “Why Software Is So Bad” in Technology Review earlier this year, which touches upon this subject.

And the ambitions go further:

    …just as accurate computer models of hydrodynamics have almost entirely replaced live nuclear testing, so we might hope that sufficient investment in accurate biological models might remove or at least considerably weaken many of the arguments for experimenting with live animals.

Very thoughtful indeed, but I must point out that while nuclear physics are very complex (I dare to assume), they are highly mathematical in nature and each atom is very much like the next in form and function. A living organism has many different types of cells (humans have about 200 different types) and within each cell a complex mechanism that determines based on a range of factors e.g. whether, during development, to become a part of the skin or the reproduction system. I’m pretty sure that nuclear physicists trust their models well, as the models have been mathematically proven. To prove a model that simulates a living organism in all its complexity is something I doubt we will see within 15 years and while not proven, findings from all research done In Silico, will probably be disputed until it has been repeated and proved to work In Vivo.

The project as a whole is very interesting and will advance several branches of scientific research both in biology, medicine and computer science. Computer models such as cellular automata are already very useful tools in biologists’ and ecologists’ toolbox. The mimicking of biological procedures in producing software is also one of the more interesting and promising branches of computer science and will surely bring us great things in the years to come.

Links:
Cell-O-Sim – A cell growth simulator from Dept. of Medical and Biological Informatics at the German Cancer Research Centre Heidelberg. Pretty nice video of a Cell-O-Sim simulation can be found here (4.8mb).
Institute for Systems Biology – A cross-disciplinary project, involving biology, physics, engineering, chemistry, computer science, mathematics and medicine to “unravel the mysteries of human biology to identify strategies to predicting and preventing diseases such as cancer, diabetes and AIDS. ”
E-Cell Project – An international research project aiming to model and reconstruct biological phenomena in silico, and developing necessary theoretical supports, technologies and software platforms to allow precise whole cell simulation.

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