Reverse Engineering Biological Circuits
Thursday, March 9, 2006
Presented By
Presented by the Systems Biology Discussion Group, IBM and the National Centers for Biomedical Computing (NCBC) program (a component of the National Institutes of Health Roadmap for Medical Research)
Organizers: Gustavo Stolovitzky, IBM; and Andrea Califano, Columbia University
The Systems Biology Discussion Group aims to explore the complex and often dynamic interdependencies between gene regulation, cellular signaling, and cellular metabolism. Meetings of the group focus on on-going efforts to formulate complex functional queries about the cell, in a genomic context, to explore them in silico, and to produce testable hypothesis about the physiological impact of individual gene manipulations.
Program
Gustavo Stolovitzky, IBM; and Andrea Califano, Columbia University, "DREAMing: the 'Database for Reverse Engineering Analyses and Methods' Project."
John Moult, University of Maryland, "Lessons from a Decade of Critical Assessment of Structure Prediction (CASP)."
Marc Vidal, Harvard University, "Interactome Networks."
Abstracts
"DREAMing: the 'Database for Reverse Engineering Analyses and Methods' Project"
Gustavo Stolovitzky and Andrea Califano
To organize the sea of methods developed to disentangle the connectivity maps within the cell and help the community understand the merits and pitfalls of one method versus the other, a group of systems biologists have started what we call the DREAM (Database of Reverse Engineering Analysis and Methods) project. The DREAM project is composed of two inter-related thrusts. On the one hand, we will create a repository of data, methods and tools to reverse engineer signaling, gene regulatory, metabolic, and developmental networks. The second thrust consists of periodic conferences in which a DREAM steering committee will curate data-sets (actual measurements of different data types, as well as data produced in-silico) of known but undisclosed network topology and parameters. The participants in this exercise will be tasked to use reverse engineering algorithms to infer the connectivity of the network underlying the curated data sets. In this way, we expect to enhance our understanding of the limitations and potential of specific methods as well as of the whole conception of reverse engineering from integrated data sets of cellular networks.
"Lessons from a Decade of Critical Assessment of Structure Prediction (CASP)"
John Moult
For the past decade, a series of community wide experiments have assessed the state of the art in the prediction of protein structure. The results have provide a detailed picture of what has been achieved in the field, where we are making progress, and what major problems remain. In this talk, I will focus on the principles and procedures used in CASP, and lessons learned about the strengths and limitations of community wide assessment in general.
"Interactome Networks"
Marc Vidal
Despite the considerable success of molecular biology to understand diseases such as cancer, many fundamental questions remain unanswered. Most importantly, since the majority of gene products in the cell mediate their function together with other gene products, biological processes should be considered as complex networks of interconnected components. In other words, for any normal biological process, or any disease mechanism, such as cancer, one might consider a "systems approach" in which the behavior and function of such networks are studied as a whole, in addition to studying some of its components individually. The draft of the human genome sequence is likely to help such a transition from molecular biology to systems biology.
Our laboratory uses a model organism, the nematode C. elegans, to study the role of protein networks in development and, doing so, develop the concepts and technologies needed for a transition to systems