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Stepping Beyond the Newtonian Paradigm in Biology

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Stepping Beyond the Newtonian Paradigm in Biology Stepping Beyond the Newtonian Paradigm in Biology Towards an Integrable Model of Life: Accelerating Discovery in the Biological Foundations of Science White Paper V.5.0 December 9th, 2011 This White Paper is for informational purposes only. WE MAKE NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS DOCUMENT. © 2011 EC FP7 INBIOSA (grant number 269961). All rights reserved. The names of actual companies and products mentioned herein may be the trademarks of their respective owners. 2 The best of science doesn’t consist of mathematical models and experiments, as textbooks make it seem. Those come later. It springs fresh from a more primitive mode of thought when the hunter’s mind weaves ideas from old facts and fresh metaphors and the scrambled crazy images of things recently seen. To move forward is to concoct new patterns of thought, which in turn dictate the design of models and experiments. Edward O. Wilson, The Diversity of Life, 1992, Harvard University Press, ISBN 0-674-21298-3. 3 The project INBIOSA acknowledges the financial support of the Future and Emerging Technologies (FET) programme within the ICT theme of the Seventh Framework Programme for Research of the European Commission. 4 Contributors Plamen L. Simeonov Germany Integral Biomathics Edwin H. Brezina Canada Innovation Ron Cottam Belgium Living Systems Andreé C. Ehresmann France Mathematics Arran Gare Australia Philosophy of Science Ted Goranson USA Information Theory Jaime Gomez-Ramirez Spain Mathematics and Cognition Brian D. Josephson UK Mind-Matter Unification Bruno Marchal Belgium Mathematics and Computer Science Koichiro Matsuno Japan Biophysics and Bioengineering Robert S. Root-Bernstein USA Physiology Otto E. Rössler Germany Biochemistry and Chaos Theory Stanley N. Salthe USA Systems Science and Natural Philosophy Marcin Schroeder Japan Mathematics and Theoretical Physics Bill Seaman USA Visual Arts and Science Pridi Siregar France Biocomputing Leslie S. Smith UK Neuroscience and Computer Science Note: This White Paper is not a concise report on the research program we seek to elaborate in INBIOSA. It has been conceived as a 'living' document, progressively developed along the months by discussions among scientists with differing formations and states of mind. We have chosen to respect their personalities, at the risk of some lack of homogeneity and repetitions between different passages. Also, incompleteness, inconsistences and antagonisms could not be completely avoided. This document is not intended to question the goals or the validity of Systems Biology or its approaches. However, it is necessary to clearly differentiate what our Integral Biomathics community is attempting to do from what systems biologists are already doing. 5 Contents 1. Preamble .............................................................................................................................. 10 2. Introduction .......................................................................................................................... 11 3. Motivation ............................................................................................................................ 13 5. Issues Affecting Integral Biomathics ..................................................................................... 25 5.1 Complementarity ............................................................................................................ 25 5.2 Scale and Hyperscale ...................................................................................................... 26 5.3 Class Identity vs. Individual Identity ............................................................................... 29 5.4 First Person Perspective ................................................................................................. 30 5.5 Biological Time ................................................................................................................ 31 5.6 Memory .......................................................................................................................... 34 5.7 Vagueness ....................................................................................................................... 35 5.8 Quantum Effects in Biology ............................................................................................ 35 5.9 Biotic vs. Abiotic Systems ............................................................................................... 37 6. The Grand Challenge ............................................................................................................ 38 6.1 The Relevance of Complexity to the Problems of Science .............................................. 39 6.2 The Radical Paradigm ..................................................................................................... 41 6.2.1 A New Trajectory: Towards Theoretical Foundations for Biology ............................... 41 6.3 Institutionalizing the Lessons of the First Scientific Revolution ..................................... 45 6.4 A New Strategic Collaboration Framework .................................................................... 46 7. Towards a General Theory of Living Systems (GTLS) ............................................................ 49 7.1 Objective ......................................................................................................................... 49 7.2 Background ..................................................................................................................... 49 7.3 The Road Ahead .............................................................................................................. 52 7.4 The Junctions .................................................................................................................. 54 7.5 What Can We Do Now? .................................................................................................. 58 7.6 A Unifying Formal Framework ........................................................................................ 64 7.7 Conclusions and Outlook ................................................................................................ 67 6 8. Initial GTLS Application Domains .......................................................................................... 68 8.1 Fusing the Different Levels of Brain/Mind Modeling ..................................................... 68 8.2 Scale-free Dynamics ....................................................................................................... 69 8.3 The Model MENS ............................................................................................................ 70 8.4 Application to Complex Event Processing. A Theory of Aging ........................................ 70 9. The GTLS Test Cases ............................................................................................................. 71 9.1 WLIMES ........................................................................................................................... 71 9.2 Hyper-B ........................................................................................................................... 73 9.3 Morphogenesis ............................................................................................................... 74 10. Call to Action ...................................................................................................................... 75 10.1 The Case for Transformative Research in Biology ........................................................ 75 10.2 The Threat to the Certainities of Continuing Progress ................................................. 76 10.3 The Intellectual Challenge of the Complexity Complexity ............................................ 77 10.4 Programmatic Advance in Theoretical Research .......................................................... 78 10.5 A New Framework for Mathematics and Computation ............................................... 79 References ................................................................................................................................ 89 7 We still know little about how the world works, and these limits are acknowledged in our emergent biological systems and in the frontiers of astrophysics. A new mathematical foundation could Executive Summary punch through those barriers and produce completely unexpected The INBIOSA project brings together a group of experts across many benefits. disciplines who believe that science requires a revolutionary transformative step in order to address many of the vexing challenges presented by the world. It is INBIOSA’s purpose to enable the focused The reason that biology has failed to collaboration of an interdisciplinary community of original thinkers. develop a viable set of mathematical methods appropriate to solving its This paper sets out the case for support for this effort. The focus of problems is that we have relied too the transformative research program proposal is biology-centric. We long on mathematics developed to admit that biology to date has been more fact-oriented and less model physical problems that are theoretical than physics. However, the key leverageable idea is that intrinsically different. careful extension of the science of living systems can be more effectively applied to some of our most vexing modern problems than the prevailing scheme, derived from abstractions in physics. While The
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