Biology is at a crossroads, with researchers having realised that it is not genes but networks that create change and generate function – networks so rich and complex that understanding them requires mathematical and computer science methods, not only molecular biology and bioinformatics. The early promise of the genomic era has not been realised. Even the central dogma has come into question. Systems biology is now an integral part of biology proper – modelling and simulation are standard practice. But its fundamental concepts and methods are far from settled. Even the basic aims are not precisely formulated.
This project developed a series of seminars focusing on the interdisciplinary dialogue to discover, elaborate, and clarify the fundamental concepts underlying modern biology – its biological presuppositions, its formal models, and its mathematics. Some fundamental questions explored included: What controls biological processes, such as the development of embryos? Networks are important, but are they all there is? What is the relationship between complexity of genomes, cells, and development? How is information processed in cells and organisms? What is the nature of biological information anyway? Is the cell something like a robot controlled by programs? Are there biological ‘programs’ at all? What is ‘causality’ in biology? In modelling? How does the complexity of life emerge? How did it evolve from unorganised matter?
Professor Tom Melham,Tutorial Fellow in Computer Science, Balliol College, University of Oxford
Professor Denis Noble, Emeritus Professor of Cardiovascular Physiology, Balliol College, University of Oxford
Dr Eric Werner, Computing Laboratory, University of Oxford
Dr Jonathan Bard, Department of Physiology, Anatomy and Genetics, University of Oxford
Contact details for enquiries
Please email the lead investigator, Professor Tom Melham<, with any queries regarding this project.
These seminars informed the development of ‘The Conceptual Foundations of Systems Biology’ issue of Progress in Biophysics and Molecular Biology, published in May 2013. Individual articles within this issue are available for download here.