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Introduction to System Biology Introduction to System Biology Dr. Carlo Cosentino School of Computer and Biomedical Engineering Department of Experimental and Clinical Medicine Università degli Studi Magna Graecia Catanzaro, Italy [email protected] http://bioingegneria.unicz.it/~cosentino Dr. Carlo Cosentino1 Carnegie Mellon University, Pittsburgh, 2008 Outline of the Lectures Ó Introduction to Systems Biology Ô Basic Principles Ô Biology in a nutshell Ô Getting experimental data Ó Modeling biochemical reactions Ô Deterministic Models Ô Stochastic Models Ó Biological Networks Ô Types of biological networks Ô Dynamical models of biological networks Ô Inference of biological networks Ó Analysis and Simulation of Biological Systems Ô A case-study: The cell cycle Ô Modeling the cell cycle Ô Analysis of biological models Ô Software tools Dr. Carlo Cosentino2 Carnegie Mellon University, Pittsburgh, 2008 Introduction to System Biology Ó Basic Principles Ó Biology in a nutshell Ó Experimental Techniques Dr. Carlo Cosentino3 Carnegie Mellon University, Pittsburgh, 2008 What is Systems Biology? Ó Systems biology is concerned with the study of biological functions and mechanisms, underpinning inter- and intra-cellular dynamical networks, by means of signal- and system-oriented approaches Ó “Life is an emergent, rather than an immanent and inherent, property of matter. Although it arises from the material world, it cannot be reduced to it” (E. Schrödinger) Ó “Science is built up of facts, as a house is with stones. But a collection of facts is no more a science than a heap of stones is a house” (H. Poincaré) Dr. Carlo Cosentino4 Carnegie Mellon University, Pittsburgh, 2008 Systems Biology Approach Ó A systems biology approach means Ô Investigating the components of cellular networks and their interactions Ô Applying experimental high-throughput and whole-genome techniques Ô Integrating computational and theoretical methods with experimental efforts Dr. Carlo Cosentino5 Carnegie Mellon University, Pittsburgh, 2008 An Iterative Approach Experiments Data Handling Modeling Dr. Carlo Cosentino6 Carnegie Mellon University, Pittsburgh, 2008 Main Related Disciplines Ó Biology! Ó Biotechnology Ó Mathematics and Statistics Ó Physics and Chemistry Ó Information Science Ó Engineering (Biomedical, Chemical, Computer, Systems & Control, Electronic) Ó … Dr. Carlo Cosentino7 Carnegie Mellon University, Pittsburgh, 2008 Foundations Ó Improved biological knowledge with the prospect of utilization in biotechnology and health care Ó New experimental techniques in genomics and proteomics Ó Classical mathematical modeling of biological processes Ó Computer power for simulation of complex systems Ó Storage and retrieval capability in large databases and data mining techniques Ó Internet as the medium for the widespread availability from multiple sources of knowledge Dr. Carlo Cosentino8 Carnegie Mellon University, Pittsburgh, 2008 Goals Ó Models to unveil mechanisms causing alterated phenotypes and devise novel therapies and drugs Ó Predictive tools to design cells with desired properties cheaply and reliably Ó Individualized and predictive medicine Dr. Carlo Cosentino9 Carnegie Mellon University, Pittsburgh, 2008 Models are not Real, though Reality can be Modeled Ó In almost any case, models are only rough representations of their biological counterparts Ó Nevertheless, models enable to Ô Elucidate network properties Ô Check the reliability of basic assumptions Ô Uncover lack of knowledge and requirements for clarification Ô Create large repository of current knowledge, formalized in a non- ambiguous way and including quantitative data Dr. Carlo Cosentino10 Carnegie Mellon University, Pittsburgh, 2008 What is a Model? Ó It depends on whom you ask… Ô Genetist: the mouse family Ts65DN serves as a model for human trisomy 21 Ô Chemist: a reaction network, described by dots (for metabolites) and arrows (for reactions) Ô Mathematician/Engineer: the same reaction network can be modeled by a system of nonlinear ODEs Ó Abstract representation of objects or processes that explains features of these objects or processes Dr. Carlo Cosentino11 Carnegie Mellon University, Pittsburgh, 2008 Mathematical Models Ó Biological processes can be described in mathematical terms, however Ô A biological object can be investigated by means of different experimental methods Ô Each biological process can be described through different (mathematical) models Ô The choice of a mathematical model or an algorithm depends on the problem, the purpose, and the intention of the investigator Ô Modeling has to reflect essential properties of the system: Different models may highlight different aspects of the same instance Dr. Carlo Cosentino12 Carnegie Mellon University, Pittsburgh, 2008 Model Development Ó Formulation of the problem: Ô Identify the specific questions that shall be answered, along with background, problem and hypotheses Ó Available Knowledge: Ô Check and collect quantitative and structural knowledge ÕComponents of the system ÕInteraction map and kind of interactions ÕExperimental results with respect to phenotypic responses against different stimuli (gene knockout, RNAi, environmental conditions) Dr. Carlo Cosentino13 Carnegie Mellon University, Pittsburgh, 2008 Model Development (cont’d) Ó Selection of model structure: Ô Level of description (atomistic, molecular, cellular, physiological) Ô Deterministic or stochastic model Ô Discrete or continuous variables Ô Static, dynamical, spatio-temporal dynamical Ó Robustness/Sensitivity Analysis: Ô Test the dependence of the system behavior on changes of the parameters ÕNumerical simulations ÕBifurcation analysis Dr. Carlo Cosentino14 Carnegie Mellon University, Pittsburgh, 2008 Model Development (cont’d) Ó Experimental Tests Ô Hypotheses driven Ô Choice of parameters to be measured, different types of experiments, number of samples and repetitions, … Ó Assessment of the agreement and divergences between experimental results and model behavior Ó Iterative refinement of the hypotheses (and of the model) Dr. Carlo Cosentino15 Carnegie Mellon University, Pittsburgh, 2008 Data Integration Ó Observation of biological phenomena is restricted to the granularity and precision of the available experimental techniques Ó A strong impulse to the development of a systematic approach in the last years has been given by the new high-throughput biotechnologies Ô Sequencing of human and other genomes (genomics) Ô Monitoring genome expression (transcriptomics) Ô Discovering protein-protein and -DNA interactions (proteomics) Ó Different types of information need to be integrated Dr. Carlo Cosentino16 Carnegie Mellon University, Pittsburgh, 2008 Issues in Data Integration Ó Data representation and storage: Ô (too) Many databases (GO, KEGG, PDB, Reactome…) Ô XML-like annotation languages (SBML, CellML) Ó Information retrieval Ô Tools for retrieving information from multiple remote DBs Ó Data correlation Ô Find the correlation between phenotypes and genomic/proteomic profiles Ô Statistics, data mining, pattern analysis, clustering, PCA, … Dr. Carlo Cosentino17 Carnegie Mellon University, Pittsburgh, 2008 Interdisciplinary Information Exchange Ó The interdisciplinary nature of systems biology requires the exchange of information among scientists from different fields Ó Mathematical formulas have to be made understandable for biologists Ó People acquainted with the rigid rules of mathematics and computers have to understand the diversity of biological objects and the uncertainty in the outcome of experiments Dr. Carlo Cosentino18 Carnegie Mellon University, Pittsburgh, 2008 Outline Ó Basic principles Ó Biology in a nutshell Ó Experimental techniques Dr. Carlo Cosentino19 Carnegie Mellon University, Pittsburgh, 2008 Branches of Biology Ó Biology is the science that deals with living organisms and their interrelationships between each other and their environment in light of the evolutionary origin Ô Biochemistry Ô Molecular biology Ô Genetics Ô Physiology Ô Morphology Ô Cytology Ô Ecology Ô … Dr. Carlo Cosentino20 Carnegie Mellon University, Pittsburgh, 2008 Prokaryotes and Eukaryotes Dr. Carlo Cosentino21 Carnegie Mellon University, Pittsburgh, 2008 Model Organisms Dr. Carlo Cosentino22 Carnegie Mellon University, Pittsburgh, 2008 Structure of the (Animal) Cell Nelson, Cox, Lehninger Principles of Biochemistry Dr. Carlo Cosentino23 Carnegie Mellon University, Pittsburgh, 2008 Composition and Sizes of Biological Objects Ó Biological compounds are prevalently composed of four basic components: C, N, O, H Ó Many compounds are made out of a set of few repeated basic blocks (nucleic acids, polypeptides, polymers) Dr. Carlo Cosentino24 Carnegie Mellon University, Pittsburgh, 2008 Biomolecules Classifications Ó Biomolecules can be divided into four families Ô Carbohydrates (energy storage) Ô Lipids (structure, signaling) Ô Proteins (catalysis, regulation, signaling, structure and support) Ô Nucleic acids (Information coding, regulation) Ó Each family has multiple functions (e.g. RNAs are coding polymers, but can also have regulatory functions, whereas some lipids act as hormones, i.e. signals) Ó Most molecules are made up of sub-complexes belonging to different families Dr. Carlo Cosentino25 Carnegie Mellon University, Pittsburgh, 2008 Nucleic Acids Ó Nucleic acids are polymers built up of covalently bound mononucleotides, they comprise DNA and RNA Ó DNA contains coding sequences (genes) for proteins and RNAs and non-coding sequences Ó Nucleotides are also important in energy transfer
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