creators_name: Baianu, I.C. creators_name: Glazebrook, James F. creators_id: ibaianu@illinois.edu creators_id: jfglazebrook@eiu.edu editors_name: Iamtovics, Barna editors_name: R·adoiu, D. , editors_name: Dehmer, M. type: journalp datestamp: 2011-12-16 00:04:40 lastmod: 2011-12-16 00:04:40 metadata_visibility: show title: Categorical Ontology of Complex Systems, Meta-Systems and Theory of Levels: The Emergence of Life, Human Consciousness and Society ispublished: pub subjects: bio-theory subjects: comp-neuro-sci subjects: comp-sci-art-intel subjects: comp-sci-complex-theory subjects: comp-sci-mach-dynam-sys subjects: neurgen subjects: neuro-anat subjects: neuro-chem subjects: neuro-mod full_text_status: public keywords: Quantum-Weave Patterns in Learning and the Development of Human Consciousness;Quantum Automata; Cell Interactomics; dynamics of genetic-proteomic networks and signalling pathways, development, regeneration, the control mechanisms of cell dynamic programming in cells; Neoplastic Transformations and Oncogenesis; Categories and Functors; Homology Theory applications to Qualitative Dynamics; Quantum Genetics; Relational Oscillations; Organismic Supercategories; Qualitative Dynamics of Systems in Organismic Supercategories; Algebraic Geometry in Biology, Cell Division Control and Dynamic Programnming;Cancer Cell Cycling; Categorical Dynamic Systems; Observables Generating Diagram, Relational Biology;Single Molecule Dynamics; Quantum, Electron Tunneling mechanisms in Enzyme Catalized reactions. note: Complex Systems Biology, Łukasiewicz-Topos and Higher-Dimensional Algebraic Models of Cell Interactomics; cell interactomics, dynamics of coupled genetic-proteomic networks and signaling pathways, development, regeneration, and control mechanisms of cell dynamic programming in cells, neoplastic transformations and oncogenesis; complex system modeling and biomolecular network representations in categories of Łukasiewicz Logic Algebras and Łukasiewicz-Topos Relational and Molecular Biology, Cell Genomics and Proteomics, and Cell Interactomics are represented in Supercategories defined currently as n-categories (or higher dimensional algebra), Axiomatic definitions of Categories and Supercategories of Relational, Complex Biological Systems. abstract: Single cell interactomics in simpler organisms, as well as somatic cell interactomics in multicellular organisms, involve biomolecular interactions in complex signalling pathways that were recently represented in modular terms by quantum automata with ‘reversible behavior’ representing normal cell cycling and division. Other implications of such quantum automata, modular modeling of signaling pathways and cell differentiation during development are in the fields of neural plasticity and brain development leading to quantum-weave dynamic patterns and specific molecular processes underlying extensive memory, learning, anticipation mechanisms and the emergence of human consciousness during the early brain development in children. Cell interactomics is here represented for the first time as a mixture of ‘classical’ states that determine molecular dynamics subject to Boltzmann statistics and ‘steady-state’, metabolic (multi-stable) manifolds, together with ‘configuration’ spaces of metastable quantum states emerging from complex quantum dynamics of interacting networks of biomolecules, such as proteins and nucleic acids that are now collectively defined as quantum interactomics. On the other hand, the time dependent evolution over several generations of cancer cells --that are generally known to undergo frequent and extensive genetic mutations and, indeed, suffer genomic transformations at the chromosome level (such as extensive chromosomal aberrations found in many colon cancers)-- cannot be correctly represented in the ‘standard’ terms of quantum automaton modules, as the normal somatic cells can. This significant difference at the cancer cell genomic level is therefore reflected in major changes in cancer cell interactomics often from one cancer cell ‘cycle’ to the next, and thus it requires substantial changes in the modeling strategies, mathematical tools and experimental designs aimed at understanding cancer mechanisms. Novel solutions to this important problem in carcinogenesis are proposed and experimental validation procedures are suggested. From a medical research and clinical standpoint, this approach has important consequences for addressing and preventing the development of cancer resistance to medical therapy in ongoing clinical trials involving stage III cancer patients, as well as improving the designs of future clinical trials for cancer treatments. KEYWORDS: Emergence of Life and Human Consciousness; Proteomics; Artificial Intelligence; Complex Systems Dynamics; Quantum Automata models and Quantum Interactomics; quantum-weave dynamic patterns underlying human consciousness; specific molecular processes underlying extensive memory, learning, anticipation mechanisms and human consciousness; emergence of human consciousness during the early brain development in children; Cancer cell ‘cycling’; interacting networks of proteins and nucleic acids; genetic mutations and chromosomal aberrations in cancers, such as colon cancer; development of cancer resistance to therapy; ongoing clinical trials involving stage III cancer patients’ possible improvements of the designs for future clinical trials and cancer treatments. date: 2010-07-12 date_type: published publication: Broad Research in Artificial Intelligence and Neuroscience, ISSN 2067-3957, volume: 1 number: 1 publisher: BRAIN: pagerange: 119-207 institution: University of Illinois at Urbana, IL. 61801, USA department: FSHN & NPRE Departments, AFC-NMR & NIR Microspectroscopy Facility refereed: TRUE referencetext: 1. Baianu, I.C. 2004a. Quantum Genetics in terms of Quantum Reversible Automata and Computation of Genetic Codes and Reverse Transcription.,Cogprints, UK, Accepted July 06, 2004. 2. Baianu, I.C. 2004b. Molecular Representations in Relational Biology and the Realization Conjecture. Cogprints and CERN Preprints. 3. Baianu, I.C. and Marinescu, M. 1968. Organismic Supercategories:I. Proposals for a General Unitary Theory of Systems., Bull. Math. Biophys., 30: 625-635. 4. Baianu, I. 1970. Organismic Supercategories: III. On Multistable Systems. Bull. Math. Biophys., 32: 539-561. 5. Baianu, I. 1971. Organismic Supercategories and Qualitative Dynamics of Systems. Bull. Math. Biophys., 33: 339-354. 6. Baianu, I. 1971. Categories, Functors and Automata Theory. The 4th Intl. Congress LMPS, August-Sept. 1971. 7. Baianu, I. and Scripcariu, D. 1973. On Adjoint Dynamical Systems. Bull. Math. Biology., 35: 475-486. 8. Baianu, I. 1973. "Some Algebraic Properties of (M, R)-Systems." Bull. Math. Biol., 35: 213-217. 9. Baianu, I. and Marinescu, M. 1974. A Functorial Construction of (M,R)-Systems. Rev. Roum. Math. Pures et Appl., 19: 389-392. 10. Baianu, I.C. 1977. A Logical Model of Genetic Activities in Lukasiewicz Algebras: The Non-Linear Theory., Bull. Math. Biol.,39:249-258. 11. Baianu, I.C. 1980. Natural Transformations of Organismic Structures. Bull.Math. Biology, 42:431-446. 12. Baianu, I.C.1983. Natural Transformations Models in Molecular Biology. SIAM Natl. Meeting, Denver, CO, USA. 13. Baianu, I.C. 1984. A Molecular-Set-Variable Model of Structural and Regulatory Activities in Metabolic and Genetic Systems., Fed. Proc. Amer. Soc. Experim. Biol. 43:917. 14. Baianu, I.C. 1987. Computer Models and Automata Theory in Biology and Medicine. In: "Mathematical Models in Medicine.",vol.7., M. Witten, Ed., Pergamon Press: New York, pp.1513-1577. 15. Carnap. R. 1938. "'The Logical Syntax of Language" New York: Harcourt, Brace and Co. 16. Cazanescu, D. 1967. On the Category of Abstract Sequential Machines. Ann. Univ. Buch., Maths & Mech. series, 16 (1):31-37. 17. Georgescu, G. and C. Vraciu 1970. "On the Characterization of Lukasiewicz Algebras." J Algebra, 16 4, 486-495. 18. Hilbert, D. and W. Ackerman. 1927. Grunduge.der Theoretischen Logik, Berlin: Springer. 19. McCulloch, W and W. Pitts. 1943. “A logical Calculus of Ideas Immanent in Nervous Activity” Ibid., 5, 115-133. 20. Pitts, W. 1943. “The Linear Theory of Neuron Networks” Bull. Math. Biophys., 5, 23-31. 21. Rosen, R.1958.a. ”A Relational Theory of Biological Systems” Bull. Math. Biophys., 20, 245-260. 22. Rosen, R. 1958a. The Representation of Biological Systems from the Standpoint of the Theory of Categories." Bull. Math. Biophys. 20: 317-341. 23. Rosen, Robert. 1964. Abstract Biological Systems as Sequential Machines, Bull. Math. Biophys., 26: 103-111; 239-246; 27:11-14;28:141-148. 24. Rosen, Robert. 1968. On Analogous Systems. Bull. Math. Biophys., 30: 481-492. 25. Rosen, Robert. 1973. On the Dynamical realization of (M,R)-Systems. Bull. Math. Biology., 35:1-10. 26. Russel, Bertrand and A.N. Whitehead, 1925. Principia Mathematica, Cambridge: Cambridge Univ. Press. 27. Warner, M. 1982. Representations of (M,R)-Systems by Categories of Automata., Bull. Math. Biol., 44:661-668. citation: Baianu, Prof. Dr. I.C. and Glazebrook, Prof. Dr. James F. (2010) Categorical Ontology of Complex Systems, Meta-Systems and Theory of Levels: The Emergence of Life, Human Consciousness and Society. [Journal (Paginated)] document_url: http://cogprints.org/7754/8/BRAINpp89ICBjfg242.pdf