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COMPLEX SYSTEMS BIOLOGY of MAMMALIAN CELL CYCLE SIGNALING in CANCER by JAYANT AVVA Submitted in Partial Fulfillment of the Requi COMPLEX SYSTEMS BIOLOGY OF MAMMALIAN CELL CYCLE SIGNALING IN CANCER by JAYANT AVVA Submitted in partial fulfillment of the requirements For the degree of Doctor of Philosophy Dissertation Advisor: Dr. Sree N. Sreenath Department of Electrical Engineering and Computer Science CASE WESTERN RESERVE UNIVERSITY May, 2011 CASE WESTERN RESERVE UNIVERSITY SCHOOL OF GRADUATE STUDIES We hereby approve the thesis/dissertation of JAYANT AVVA candidate for the PhD degree *. (signed) SREE N. SREENATH (chair of the committee) KENNETH A. LOPARO VIRA CHANKONG MIHAJLO D. MESAROVIC JAMES W. JACOBBERGER (date) 12/01/2010 *We also certify that written approval has been obtained for any proprietary material contained therein. Copyright © 2011 by Jayant Avva All rights reserved Table of Contents LIST OF TABLES .................................................................................................vi LIST OF FIGURES .............................................................................................. vii ACKNOWLEDGEMENTS .....................................................................................xi ABSTRACT ........................................................................................................ xiii 1. INTRODUCTION ....................................................................................... 1 1.1. Overview ................................................................................................. 1 1.2. Chapter Organization .............................................................................. 1 1.3. Motivation ................................................................................................ 1 1.3.1. Cell Cycle ...................................................................................... 5 1.4. Computational models ............................................................................. 6 1.4.1. Necessity of dynamics ................................................................... 6 1.4.2. Paucity of organized time profile data in cell signaling .................. 7 1.4.3. Extracting dynamics out of statically sampled data ..................... 11 1.5. State of the art ....................................................................................... 13 1.6. Thesis contribution ................................................................................ 16 1.7. Thesis organization ............................................................................... 18 2. BACKGROUND ....................................................................................... 20 2.1. Overview ............................................................................................... 20 2.2. Chapter Organization ............................................................................ 20 2.3. Introduction ............................................................................................ 21 2.4. Systems Biology .................................................................................... 21 2.4.1. Different types of System Biologies ............................................. 22 2.4.2. Complex Systems Biology ........................................................... 25 2.4.3. Hierarchical and multi-level paradigm- concepts and significance ... .................................................................................................... 27 2.5. Cross-level causality .............................................................................. 29 2.5.1. Multiscale modeling ..................................................................... 32 2.6. Modeling ................................................................................................ 33 2.6.1. Importance of modeling ............................................................... 33 2.6.2. Contextual view of types of models in cancer biology studies ..... 34 2.6.3. Mathematical and Computational Models .................................... 36 i 2.6.4. Phenomenological vs. Mechanistic Models ................................. 37 2.6.5. Static vs. Dynamic Models ........................................................... 37 2.6.6. Deterministic vs. Probabilistic Models.......................................... 38 2.6.7. Dominant relationship modeling: Unmodeled dynamics .............. 39 2.6.8. Modeling Approaches: How does one go about modeling ........... 40 2.6.9. Modeling errors and rectification .................................................. 42 2.6.10. Mathematical formalism ............................................................... 43 2.6.10.1. Use of mass action modeling: An example ............................. 44 2.6.10.2. General system modeling: Using mass action modeling ......... 46 2.6.11. Calibration and Validation ............................................................ 49 2.7. Role of Data in Building Predictive Models ............................................ 54 2.7.1. Data measurement introduction ................................................... 55 2.7.2. Data measurement processes ..................................................... 60 2.7.3. Western Blotting .......................................................................... 61 2.7.4. Flow Cytometry ............................................................................ 66 2.8. Data driven systems biology thinking .................................................... 71 2.8.1. In vivo data .................................................................................. 71 2.8.2. Ex vivo data ................................................................................. 72 2.8.3. In vitro data .................................................................................. 73 2.8.4. Measurement decisions ............................................................... 74 3. TIME PROFILE EXTRACTION FROM WET LAB DATA ......................... 79 3.1. Overview ............................................................................................... 79 3.2. Chapter Organization ............................................................................ 79 3.3. Introduction ............................................................................................ 80 3.4. Importance of cytometry data ................................................................ 81 3.5. State of the art ....................................................................................... 82 3.5.1. Classification/comparison of time profile data generation methods . .................................................................................................... 82 3.5.2. Need for our method .................................................................... 83 3.6. Dynamic time profile extraction methodology ........................................ 84 3.6.1. Generic methodology................................................................... 85 3.6.1.1. Experimental setup ................................................................... 85 3.6.1.2. Pre-processing .......................................................................... 87 3.6.1.3. Phase-specific processing ........................................................ 88 ii 3.6.1.4. Postprocessing ......................................................................... 89 3.6.1.5. Replicated filtered data ............................................................. 91 3.6.1.6. Testing the methodology for repeatability ................................. 91 3.6.2. Application to K562 cells .............................................................. 92 3.6.2.1. Experimental setup ................................................................... 92 3.6.2.2. Pre-processing .......................................................................... 94 3.6.2.3. Phase-specific processing ........................................................ 96 3.6.2.4. G1 and S Phase Time Course .................................................. 98 3.6.2.5. G2 Phase Time Course ............................................................ 99 3.6.2.6. M Phase Time Course ............................................................ 103 3.6.3. Postprocessing .......................................................................... 106 3.6.3.1. Single color correction ............................................................ 106 3.6.3.2. Practical issues ....................................................................... 109 3.6.3.3. Testing methodology for reproducibility .................................. 112 3.6.3.4. Testing methodology on MOLT4 cell line data ........................ 115 3.6.3.5. Reproduced filtered data ......................................................... 117 3.6.3.6. Theoretical formulation of data variation ................................. 119 3.7. CytoSys – a software for time profile extraction .................................. 122 3.7.1. Introduction ................................................................................ 122 3.7.2. Data Input .................................................................................. 124 3.7.3. Data Structure ........................................................................... 124 3.7.4. Processing protocol ................................................................... 125 3.7.5. File Structure in CytoSys ........................................................... 126 3.7.6. Salient Features ........................................................................ 127 3.7.6.1. Gaussian fits to data ..............................................................
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