Building: Arnold R. Meyer Institute of Biological Sciences
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|Design principles of biological networks
The adaptation of cells to the changing environment requires sophisticated information processing, which is mediated by networks of interacting genes and proteins. Identifying the principles that govern the design and function of those networks is a central goal of modern research. Our lab is using theoretical and computational tools to investigate system-level properties of biological networks. Wet-lab experiments validate and extend theoretical results.
One approach is to study small and well-characterized networks. Our goal here is to understand the biological constraints that are imposed on a particular system, and the impact of those constraints on the structural design of the network. Currently we are focusing on networks that mediate patterning during the development of the fruit-fly Drosophila. In particular, we are interested in the robustness property of those systems, namely their ability to buffer alteration in gene dosage and changes in environmental conditions such as temperature or availability of nutrients. Those requirements imposed strict constraints on the structure of the underlying patterning network.
A second research direction explores the organization of the cellular transcription program. This is now becoming possible due to the revolutionary new DNA-chips technology. DNA chips measure the expression levels of all genes simultaneously, providing a panoramic perspective of the cellular transcription states. This technology is being used by an increasing number of laboratories, and a large dataset describing "snap-shots" of genome-wide expression profiles is now available. One of the main challenges is to devise methods that will "reverse engineer" the underlying genetic network from the observed expression data.
In our lab, we analyze existing microarray data of diverse organisms, ranging from yeast to human. We develop novel algorithms that overcome well-recognized drawback of common techniques. In parallel, we perform novel microarray experiments design to reveal novel system-level properties of the underlying transcription network. Those experiments are done in the yeast s. cerevisiae.
N. Barkai, and S. Leibler. Robustness in Simple Biochemical Networks. Nature, 387, 913 (1997). PDF Version
N. Barkai, M. Rose and N. Wingreen. Protease Helps Yeast Find Mating Partners. Nature, 396, 422-423 (1998) PDF Version
U. Alon, M. Surette, N. Barkai and S. Leibler. Robustness in Bacterial Chemotaxis. Nature, 397, 168-171 (1999) PDF Version
N. Barkai and S. Leibler. Circadian clocks limited by noise. Nature, 403, 267-688 (2000) PDF Version
N. Barkai, U. Alon and S. Leibler, Robust Amplification in Adaptive Signal Transduction network. C. R. Acad. Sci. SÚr. IV 2, 871-877 (2001)
JM. Vilar, HY. Kueh, N. Barkai and S. Leibler. Mechanisms of noise-resistance in genetic oscillators. PNAS, 99, 5988-5992 (2002) PDF Version
A. Eldar, R. Dorfman, D. Weiss, H. Ashe, B-Z. Shilo and N. Barkai. Robustness of Morphogen Gradients in Early Embryonic Patterning. Nature, 419, 304-308. (2002) PDF Version
J. Ihmels, G. Friedlander, S. Bergmann, O. Sarig and N. Barkai. Revealing Modular Organization in the Yeast Transcriptional Network. Nature Genetics, 31, 370-377 (2002) PDF Version
Department of Molecular Genetics
Last Updated: 10 August 2008