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Towards insilico Science

Silicon Genomics is strategically positioned at the intersection of computer science and the life sciences.

At our inception, we took a leap from the application of computing to support scientists "do" science (i.e. "computational science") to the integration of computer science concepts, tools and theorems into the very fabric of science.

On the surface, this change may seem subtle, however, we believe it to be fundamental to science and the way science is practiced. insilico science represents the foundations of a new revolution in science and Silicon Genomics is committed to thought leadership in the field.

Conceptual and technological tools developed within computer science are, for the first time, starting to have wide-ranging applications outside the subject in which they originated, especially in sciences investigating complex systems, most notably in biology and chemistry. We believe computer science is poised to become as fundamental to biology as mathematics has become to physics.

We suggest this because there is a growing awareness among biologists that to understand cells and cellular systems requires viewing them as information processing systems, as evidenced by the fundamental similarity between molecular machines of the living cell and computational automata, and by the natural fit between computer process algebras and biological signaling and between computational logical circuits and regulatory systems in the cell. We believe this is a potential starting point for fundamental new developments in biology, biotechnology and medicine.

We believe that computer science concepts and tools in science form a third, and vital component of enabling a "golden triangle" to be formed with novel mathematical and statistical techniques in science, and scientific computing platforms and applications integrated into experimental and theoretical science.

This combination is likely to accelerate key breakthroughs in science and benefits to society, from understanding biology and revolutionizing medicine and healthcare, and from understanding the universe to understanding and helping to protect the life-support systems of Earth on which we all depend for our survival.

An immediate and important challenge is that of end-to-end scientific data management, from data acquisition and data integration, to data treatment, provenance and persistence. But importantly, our research urgently requires us to reconsider current thinking in the increasingly prominent domain of "computational science".

While advances in computing, and in particular scientific data management and application development environments for science will be important towards insilico science, we believe that vitally more important, and dramatic in its impact, will be the integration of new conceptual and technological tools from computer science into the sciences.

Computer science concepts provide levels of abstraction allowing scientists from different fields to understand and learn from each other’s solutions, and ultimately for scientists to acquire a set of widely applicable complex problem solving capabilities, based on the use of a generic computational environment, in the same way that they learn universally applicable mathematical skills.

We believe that the current view of "computational science" as a separate "third pillar" in science alongside experimental and theoretical science is an intermediate, unsustainable and undesirable state.

Our research has significant implications for scientific publishing, where we believe that even near-term developments in the computing infrastructure for science which links data, knowledge and scientists will lead to a transformation of the scientific communication paradigm.

We also believe this development is not only a potential starting point for fundamental new developments in biology, biotechnology and medicine, but also for potentially profound developments in the future of computing. Big challenges for future computing systems have elegant analogies and solutions in biology, such as the development and evolution of complex systems, resilience and fault tolerance, and adaptation and learning. New levels of understanding and knowledge about biological processes and systems will underpin the new building blocks of the next century of computing.

Finally, our research shows significant implications for the education of tomorrow’s scientists and science policy and funding. Scientists will need to be completely computationally and mathematically literate, and it will simply not be possible to do science without such literacy. This therefore has important implications for educational policy right now. The output of computer scientists today barely meets the needs of the public and industrial computing sectors, let alone those required for future science sectors.

These developments will also fundamentally affect how science needs to be funded, what science is funded, and many current assumptions underpinning existing science policies. They also have economic implications. We are starting to give birth to "new types" of science and possibly a new economic era of "science-based innovation" that will create new types of high-tech sectors that we can barely imagine today, just as we could hardly have imagined today’s rapidly growing "genomics" sector happening two decades ago.

Silicon Genomics has developed a vision towards insilico science, and has reasoned through how this vision can underpin fundamental breakthroughs in science and provide benefits to societies around the world.

Our vision and our research are what we believe to be the first ever comprehensive attempt to define a roadmap towards insilico science, which we hope will stimulate discussion and debate and give direction for scientists, policy makers and governments, as well as inspire a generation of today’s children to become tomorrow’s scientists.

Read the NeuroGen Vision for information about Silicon Genomics insilico Drug Discovery Optimization Platform.