Shankar Subramaniam University of California at San Diego Data to Biology

UCSD-Bioinformatics & Systems Biology Group Many Dimensions of Biology Scales: Molecules, Networks, Cells, Tissues… Granularity: Structure, Function, Phenotype, Physiology… Development: Stem cells, Differentiation, Tissue Engineering… Species: Microorganisms, Unicellular Eukaryotes, Insects, Plants, Animals… Length/Time: fempto, nano, micro, …. Cell Processes: Metabolism, Regulation, Signaling… Models: Micro, Meso, Macro…. Model Systems: Microbes, Yeast, Worm/Fly, Plant, Mouse, Rat, Human

UCSD-Bioinformatics & Systems Biology Group Cell State1 State2State i Input Response State: genes, proteins, metabolites, ions…… The Parts List Problem! CELLULAR RESPONSE TO STIMULUS proteins peptides amino acids nucleotides retinoids Gene Expression

UCSD-Bioinformatics & Systems Biology Group Automated sequencing machines at the Center for Genome Research in the Whitehead Institute

Deconstructing Biology Analysis of components, interactions and phenotypes – in context Multiscale and high throughput measurements Integration of data and knowledge Coarse grained views of the system Understanding larger scale function Quantitative prediction of response to input at the systems level Study of dynamical behavior of systems Perturbation of components to produce changes in systemic response Building dynamical models of systems

Challenges in building biochemical models Complexity of proteomic states and interactions Integration of diverse data to infer biochemical interactions and modules Accounting for the temporal state of biochemical models

Papin, Gianchandani and Subramaniam, Current Opinions in Biotechnology 2004 DATA, MEASUREMENTS AND INTEGRATION

Characterizing Biochemical Models - Reconstruction Pradervand, Maurya and Subramaniam Genome Biology 2006

Basic Challenges for Systems Biology How will we define and characterize a biological system? How can we obtain the information on components of the system (qualitative and quantitative; static and dynamical)? Technologies and computational methods? What mechanisms can we infer from the system behavior? What are realistic models of a system? How can we measure/compute input-phenotype characteristics of the system? How will the model of the system be validated experimentally?

Biological Systems and Models - some Examples… The Genome as a System Guda et al. MITOPRED: a genome-scale method for prediction of nucleus-encoded mitochondrial proteins. Bioinformatics Jul 22;20(11): The Cell as a System Maurya et al. Systems biology of macrophages. Adv Exp Med Biol. 2007; 598: A Biological Process as a System Subramaniam et al. The Macrophage Lipidome Ogawa et al. Molecular Determinants of Crosstalk between Nuclear Receptors and Toll-like Receptors. Cell Sep 9;122(5): A Biochemical Pathway as a System Maurya MR and Subramaniam S. A kinetic model for calcium dynamics in RAW Cells: 1. Mechanisms, parameters and dose response. Biophysical Journal Aug; 93: A kinetic model for calcium dynamics in RAW Cells: 2. Knockdown response and long-term response. Biophysical Journal Aug; 93: A Functional Module as a System Bornheimer et al. Computational modeling reveals how interplay between components of a GTPase-cycle module regulates signal transduction. Proc Natl Acad Sci U S A Nov 9;101(45): Physiological Function as a System Avidor-Reiss et al. Decoding cilia function: defining specialized genes required for compartmentalized cilia biogenesis. Cell May 14;117(4): An Organ as a System Bhargav et al. Pathways associated with cardiomyogenesis from embryonic stem cells. A Disease as a System Sears et al., Insulin Resistance – A systems physiology study Proc. Natl. Acad. Sci