inducible protein degradation
During the course of my Ph.D., I developed three methods for
generating conditional alleles in S. cerevisiae. These systems will
be used together with genome-scale measurements to illuminate
the causal structures in biological networks.
Progress is also being made towards extending the technology
into mammalian cells, with the long term goal of determining
whether it will be suitable for creating novel therapeutics.
systems level biology
The production and analyses of large-scale experimental datasets
have led to the abstract representation of numerous types of
biological networks. These span the range from protein interaction
networks generated from two-hybrid and affinity purification data,
to metabolic and regulatory networks generated from organism
level measurements of RNA, protein and metabolite concentrations.
We have extended the classes of available large-scale datasets
to include the analyses of growth phenotypes of all 4,700 mutant
yeast deletion strains under 21 different media conditions. We
use these data to estimate the degree of pleiotropy in yeast and
demonstrate that it is significantly higher than can be explained by
random chance.
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