University of California at San Diego Shankar Subramaniam University of California at San Diego Data to Biology

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

CELLULAR RESPONSE TO STIMULUS State1 State2 State i Input Response proteins peptides amino acids nucleotides retinoids Gene Expression State: genes, proteins, metabolites, ions…… The Parts List Problem! UCSD-Bioinformatics & Systems Biology Group

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

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

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

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. 2004 Jul 22;20(11):1785-94. The Cell as a System Maurya et al. Systems biology of macrophages. Adv Exp Med Biol. 2007; 598: 62-79. A Biological Process as a System Subramaniam et al. The Macrophage Lipidome. 2008. Ogawa et al. Molecular Determinants of Crosstalk between Nuclear Receptors and Toll-like Receptors. Cell. 2005 Sep 9;122(5):707-21. A Biochemical Pathway as a System Maurya MR and Subramaniam S. A kinetic model for calcium dynamics in RAW 264.7 Cells: 1. Mechanisms, parameters and dose response. Biophysical Journal. 2007 Aug; 93: 709-728. A kinetic model for calcium dynamics in RAW 264.7 Cells: 2. Knockdown response and long-term response. Biophysical Journal. 2007 Aug; 93: 729-740. 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. 2004 Nov 9;101(45):15899-904. Physiological Function as a System Avidor-Reiss et al. Decoding cilia function: defining specialized genes required for compartmentalized cilia biogenesis. Cell. 2004 May 14;117(4):527-39. 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. 2009.