We are working on prediction protein function on a global scale,
primarily through analysis of large gene expression datasets. Our theoretical
work is complemented by collaboration with experimentalists and development
of new software tools.
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Integration of large genomic datasets has been used to
derive information on
protein-protein interactions, with the aid of a new algorithm for
detecting new relationships
from expression profiles.
[ papers ]
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We have also investigated the relationship of gene expression data to
protein structure and function
and protein abundance, primarily
in the yeast genome.
[ papers ]
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ExpressYourself is our online
platform for microarray data processing, which provides an intuitive graphical
interface for background correction, normalization, scoring, and quality
assessment of hybridization data.
[ citation ]
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We have studied subcellular localization of yeast proteins
based on expression levels using
Bayesian network prediction, and in conjunction with experimental
methods such as transposon mutagenisis.
[ papers ]
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As a part of the
Yale Center for Excellence in Genome Sciences and the
Yale Center for Genomics and Proteomics, the lab is working on large-scale
analyses of transcriptional activity and regulation, principally in
the human and yeast genomes, in collaboration with a number of other labs.
[ papers ]
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