Systems Biology Lecture 1 history, introduction and definitions. Pawan Dhar

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1 Systems Biology Lecture 1 history, introduction and definitions Pawan Dhar

2 Historical context Dominant approach Physiology Molecular biology Focus of study Paradigmatic discovery Functioning of organs and metabolism Homeostasis Identification and functioning of cellular components DNA discovery, Whole genome Sequencing Limitations of approach Inability to identify / modify cellular components Inability to explain how components interact to produce phenotype N.Chomsky. Systems Biology Meeting, MIT, Boston Jan 8-9, 2004

3 Future timeline years? Another years or more We know gene products of major pathways Identify all the interactions among proteins in the pathway Quantitative understanding of biology. Major how and why questions resolved N.Chomsky. Systems Biology Meeting, MIT, Boston Jan 8-9, 2004

4 The genesis of systems biology 1940s: Nobert Wiener - Father of Cybernetics 1960s, 70s: Biochemical system theory, Metabolic control theory Mid 1990s: Systems Biology - Leroy Hood

5 Defintion and complexity Systems Biology is defined by assays, data types, global assays and the types of data integrations Hypothesis driven Global Quantitative Integrative Iterative Dynamic Multiscale Cross-disciplinary Levels of biological complexity - DNA - RNA - Proteins - Protein-protein & protein DNA Interactions - Pathways - Networks - Cells & tissue - Organs & Systems - Organisms - Population - Ecology Bottomline: System is really where you draw the box! Leroy Hood. Systems Biology Meeting, MIT, Boston Jan 8-9, 2004

6 Fundamental Concepts What is : What is a: system model modeling Simulation step path pathway Network? Validation Measurement Experimentation Step: 1 reaction event Path: 1 entry, 1 exit Pathway: 1 entry, 1-many exits Network: many entries, many exits Computational modeling

My initiation into Systems Biology The E-Cell System GLC GLCtr Glycolysis 2,3DPG HCO 3 ATP ADP CAH H + H + HCO 3 CO 2

TK2 R5PI Pentose phosphate pathway ALD E4P TA S7P TK1 Donnan ratio DHAP TPI GA3P GAPDH NAD NADH Pi H + AMP ATP ADE PRPP

Nucleotide metabolism mosm VOL AMP AMPase IMP ADO Pi IMPase ADA INO PNPase HX Pi AK HXtr EN ADP PEP ATPase PK ATP NADH

7 My initiation into Systems Biology The E-Cell System GLC GLCtr Glycolysis 2,3DPG HCO 3 ATP ADP CAH H + H + HCO 3 CO 2 CO 2 HK G6P GLC G6PDH GL6P 6PGLase GO6P 6PGODH Ru5P PGI NADP GSSGR NADPH F6P ATP GSH X5PI PFK GSHox GSSG ADP X5P FDP TK2 R5PI Pentose phosphate pathway ALD E4P TA S7P TK1 Donnan ratio DHAP TPI GA3P GAPDH NAD NADH Pi H + AMP ATP ADE PRPP DPGM PRPPsyn R5P 1,3DPG PGK DPGase 3PG Pi PGM 2PG ADP ATP ADP ATP ADPRT Pi Pi AMPDA Pi Pi PRM APK HGPRT Pi R1P Nucleotide metabolism mosm VOL AMP AMPase IMP ADO Pi IMPase ADA INO PNPase HX Pi AK HXtr EN ADP PEP ATPase PK ATP NADH Membrane transport ADE ATP ADP ADEtr Na+ K+ ADE PYR LDH NAD PYRtr LAC Na/K Pump Na + PYR LACtr K + LAC K + K + Na + Na + mosm VOL HX

8 Where are we now? Grid version released in

9 Why is it difficult to model cellular transactions? Qualitative biology Inaccuracy of data Incompleteness of data Memory Sensing Feedback Communication Toggle switches (feedback loops +/-), amplifiers, resistors and oscillators, bistable states, unstable states, attractors, hysteresis? Where do cells derive their robustness from? Sci.Am. Jan 2004 issue

10 Problem What we understand Biological chemistry, Transmission of genetic information What we don t understand? Biological complexity The best non-living equivalent of life (for in-silico modeling) Emergent phenomena Heavy usage of mathematics! Mathematics: Usually approach driven, not problem driven

11 From fusion to confusion computational & Intellectual Assuming 5 parameters / protein 30,000 genes = 150,000 parameters space (PS) Cell physiology = 1 point in this PS Dynamics of regulation Change 1 point in PS 5000 genes respond Equivalent to parameters change Q1: How do cells find safe paths between continuously changing physiological states? Q2: Hidden Laws of Biological Complexity?

12 The why files? Unanswered questions Q1.Why model pathways, networks, cells and tissues? Q2: Has Systems Biology gone far beyond its intended meaning? Q3: Experimental Systems Biology vs. Computational Systems Biology Q1. What are the initial and boundary conditions in biological systems? Q2: Is there a broader set of primitives one can use in biology? Q3. Can a simple rule give rise to complex biological patterns? Q4. How are networks generated from molecular interactions? Q5. Rules that generate a combination of scale-free / modular network? Q7: The big one: How do organisms handle information 6 orders of magnitude apart?

13 Challenges Requirements Number of components - enormous Rules of how they fit together? Principles of complex and robust behavior Biology Math Comp Science Physics Engineering Training new breed of biologists who understand nonbiological concepts!! Systems Biology is NOT a subculture of Mathematical Biosciences! 3 billion years of metabolism and 1 billion year of Cell biology : 3500 fold HTS : 3500 more! Leroy Hood. Systems Biology Meeting, MIT, Boston Jan 8-9, 2004

14 Our Modeling strategy Biological knowledge Conceptual Model Analytical Model Rate Equations Constraints Guess missing parameters Add lots of assumptions! Computer simulation Match in-silico & in-vivo Revise Use model for diagnostic purposes Validated model Make predictions Explain nonintuitive phenomenon

15 t a D a M Classic State-ofthe-art o l e d Wish list

16 Reading material Leroy Hood Group Drug Discov Today May 15;8(10): Mech Ageing Dev Jan;124(1):9-16. Nature Jan 23;421(6921): Review Annu Rev Genomics Hum Genet. 2001;2: Review. Tomita Group - Japan E-Cell publication: Bioinformatics (1999) 15(1): BII Artificial Life and Robotics (2002) 6: Complex Systems Science in Biomedicine (Kluver, in press) Encyclopedia of Molecular cell biology and Molecular Medicine (Wiley-Verlag) The Ecell Book. Kluver-Landes Bioessays Jan;26(1): Others De Jong. J Comput Biol. 2002;9(1): Hoefstadt et al. In Silico Biol. 1998;1(1): Caltech group: Bioinformatics Mar 1;19(4):

arxiv: v1 [q-bio.mn] 12 Jul 2011

arxiv: v1 [q-bio.mn] 12 Jul 2011 Computing fluxes and chemical potential distributions in biochemical networks: energy balance analysis of the human red blood cell Daniele De Martino, Matteo Figliuzzi, Andrea De Martino, and Enzo Marinari