Introduction Lecture #1. Outline The systems biology paradigm What is a (biological) network? Why...
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Transcript of Introduction Lecture #1. Outline The systems biology paradigm What is a (biological) network? Why...
Outline
• The systems biology paradigm• What is a (biological) network?• Why build mathematical models for
simulation?• Key concepts in analysis of dynamic states• Fundamental approaches• Sources of data
The Systems Biology Paradigm:components -> networks -> computational models -> phenotypes
Palsson,BO; Systems Biology, Cambridge University Press 2006
What is a network?Networks are made up of chemical transformations
Networks have nodes and linksNetworks produce biological/physiological functions
Levels of knowledge about linksAbstract Specific
relationships(correlations)
influences(directional) mechanisms
chemicalmechanisms
kinetics &thermo.
What is a network?Networks can be a priori defined by function or defined based on High Throughput data
Bottom-up Network Reconstructions Represent a Biochemically, Genetically, and Genomically
(BiGG) Structured Knowledge Base
Global human metabolic network
Methylglyoxal metabolism
Acetone monooxygenase
Acetone
Cytochrome P450, family 2, subfamily E,
polypeptide 1
ReadsBase pairs
Contigs
Chromosomes
ReactionsCompounds
Gene-protein relationships
Pathways
Genome AnnotationComprehensively represents genetic material in all human cells
Network AnnotationComprehensively represents biochemical activities in all human cells
Hierarchical Levels of Detail in the 1D and 2DHuman Annotations
Why Build Models?(Jay Bailey, 1998)
1. To organize disparate information into a coherent whole
2. To think (and calculate) logically about what components and interactions are important in a complex system.
3. To discover new strategies4. To make important corrections to the conventional
wisdom5. To understand the essential qualitative features
Biotech Prog 14:8-20 (1998)
Networks Have States:steady, dynamic & physiological states
Basic Concepts in Dynamic Analysis:
1. Time constant; t1/2, , …
2. Aggregate variables, multi-scale analysis ATP2ATP+ADP “pools”
3. Transition from one steady state to another4. Graphical presentation of solution
The Two Fundamental Approaches
1. Simulation: 1) formulate equations using well-defined assumptions; 2) specify parameter values; 3) specify IC; 4) use a computer to solve the equations numerically (MatLab, Mathematica); 5) graph and analyze the results
1. Analysis: A model is a formal (mathematical) representation of the data/knowledge that you have about the process/phenomena that you are studying; can analyze model properties to examine how its different components interrelate or contribute to its properties
Assumptions Used in the Formulation of Dynamic Network Models
• Continuum assumption, i.e, do not deal with individual molecules, but treat medium as continuous
• Constant volume assumption• Ignore p/c factors, i.e., electroneutrality or osmotic
pressure• Finer spatial structure of cells and organelles is
ignoredmedium is homogeneous ~100nm• Constant temperature; isothermal (also isobaric)
Mathematical Representation:3 key matrices
S: Network topology/structurelinks between network components(numerically “perfect,” well-behaved and sparse)(biologically genomic origin)
G: Kinetic properties of individual links in the network;reciprocals of time constants(numerically challenging; very different order of magnitudein numerical values—ill conditioned, sparse)(biological origin is genetic)
J: The Jacobian matrix contains the dynamic propertiesof the network, J=S•G
1/1/min
1/1/hr
1, 2,…m
Summary
• The systems biology process has four basic steps• Biological networks can be reconstructed using disparate data• Dynamics states are characterized by: time constants, forming
aggregate variables, characteristic transitions• Dynamic analysis is a mathematical subject• Spectrum of times scales and formation of aggregate
variables are key issues• Dynamic models can be simulated or analyzed• There are notable assumptions in building dynamic models
that one needs to understand• The needed data is organized into two matrices