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Stepping Beyond the Newtonian Paradigm in Biology

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Stepping Beyond the Newtonian Paradigm in Biology to be published in: Plamen L. Simeonov, Leslie S. Smith, Andrée C. Ehresmann (Eds.). 2012. Integral Biomathics: Tracing the Road to Reality. Springer. Stepping Beyond the Newtonian Paradigm in Biology Towards an Integrable Model of Life: Accelerating Discovery in the Biological Foundations of Science INBIOSA White Paper Plamen L. Simeonov, Integral Biomathics, Germany [email protected] Edwin H. Brezina, Innovation, Canada [email protected] Ron Cottam, Living Systems, Belgium [email protected] Andreé C. Ehresmann, Mathematics, France [email protected] Arran Gare, Philosophy of Science, Australia [email protected] Ted Goranson, Information Theory, USA [email protected] Jaime Gomez-Ramirez, Mathematics and Cognition, Spain [email protected] Brian D. Josephson, Mind-Matter Unification, UK [email protected] Bruno Marchal, Mathematics and Computer Science, Belgium [email protected] Koichiro Matsuno, Biophysics and Bioengineering, Japan [email protected] Robert S. Root-Bernstein, Physiology, USA [email protected] Otto E. Rössler, Biochemistry and Chaos Theory, Germany [email protected] Stanley N. Salthe, Systems Science and Natural Philosophy, USA [email protected] Marcin Schroeder, Mathematics and Theoretical Physics, Japan [email protected] Bill Seaman, Visual Arts and Science [email protected] Pridi Siregar, Biocomputing, France [email protected] Leslie S. Smith, Neuroscience and Natural Computing, UK [email protected] 2 ______________________________________________________________________________ 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' docu- ment, 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, inconsist- ences and antagonisms could not be completely avoided. This document is not intended to question the goals or the validity of Sys- tems Biology or its approaches. However, it is necessary to clearly differ- entiate what our Integral Biomathics community is attempting to do from what systems biologists are already doing. 3 ______________________________________________________________________________ The best of science doesn’t consist of mathematical models and ex- periments, 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. 4 ______________________________________________________________________________ Contents 1. Preamble ....................................................................................... 8 2. Introduction ................................................................................. 9 3. Motivation .................................................................................. 11 4. Major Biomathematical Problems ........................................... 15 5. Issues Affecting Integral Biomathics ....................................... 28 5.1 Complementarity .................................................................. 28 5.2 Scale and Hyperscale ............................................................ 30 5.3 Class Identity vs. Individual Identity .................................... 33 5.4 First Person Perspective ........................................................ 35 5.5 Biological Time .................................................................... 37 5.6 Memory ................................................................................. 41 5.7 Vagueness ............................................................................. 41 5.8 Quantum Effects in Biology ................................................. 42 5.9 Biotic vs. Abiotic Systems .................................................... 45 6. The Grand Challenge ................................................................ 46 6.1 The Relevance of Complexity to the Problems of Science .. 47 6.1.1 The Trajectory of Science: the Transformation of Methodological Paradigms from Descriptive to Mathematical47 6.1.2 The Impasse in Biology and the Need for Convergent Theoretical Synthesis .............................................................. 48 6.1.3 The Evolution of Mathematics in the Development of Science .................................................................................... 49 6.2 The Radical Paradigm ........................................................... 50 6.2.1 A New Trajectory: Towards Theoretical Foundations for Biology .................................................................................... 50 6.2.2 The Entailments of Complexity ..................................... 52 6.2.3 Bridging the Complexity-based Disciplines .................. 53 6.3 Institutionalizing the Lessons from the First Scientific Revolution ................................................................................... 55 6.4 A New Strategic Collaboration Framework ......................... 56 7. Towards a General Theory of Living Systems (GTLS) ......... 60 5 ______________________________________________________________________________ 7.1 Objective ................................................................................ 60 7.2 Background ............................................................................ 61 7.3 The Road Ahead .................................................................... 65 7.4 The Junctions ......................................................................... 67 7.4.1 Back to Aristotle? ........................................................... 67 7.4.2 Back to Plato? ................................................................. 68 7.4.3 Back to Kant? .................................................................. 71 7.5 What Can We Do Now? ........................................................ 73 7.6 A Unifying Formal Framework ............................................. 81 7.6.1 Why Categories? ............................................................. 81 7.6.2 The Memory Evolutive Systems (MES) ......................... 83 7.6.3 Open Problems ................................................................ 84 7.7 Conclusions and Outlook ....................................................... 85 8. Initial GTLS Application Domains ........................................... 86 8.1 Fusing the Different Levels of Brain/Mind Modeling ........... 87 8.2 Scale-free Dynamics .............................................................. 87 8.3 The Model MENS .................................................................. 89 8.4 Application to Complex Event Processing: A Theory of Aging ........................................................................................... 89 9. The GTLS Test Cases ................................................................. 90 9.1 WLIMES ................................................................................ 91 9.2 Hyper-B ................................................................................. 92 9.3 Morphogenesis ....................................................................... 94 10. Call to Action ............................................................................ 95 10.1 The Case for Transformative Research in Biology ............. 95 10.2 The Threat to the Certainities of Continuing Progress ........ 97 10.3 The Intellectual Challenge of the Complexity Sciences ...... 98 10.4 Programmatical Advance in Theoretical Research .............. 99 10.5 A New Framework for Mathematics and Computation .... 101 10.5.1 Approach: Constructivist Innovative Mathematical Cross-Disciplinary Models .................................................... 102 10.5.2 Focus and Implementation: Integral Biomathics ........ 104 10.5.3 Summary and Prospects .............................................. 108 References ..................................................................................... 112 6 ______________________________________________________________________________ Summary The INBIOSA project brings together a group of experts across many dis- ciplines 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 collaboration of an interdisciplinary community of original thinkers. This paper sets out the case for support for this effort. The focus of the transformative research program proposal is biology-centric. We admit that biology to date has been more fact-oriented and less theoretical than physics. However, the key leverageable idea is that 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 these have some universal application and demonstrate computational advantages, they are not theoretically mandat- ed for the living. A new set of mathematical abstractions derived from bi- ology can now be similarly extended.
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