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CSB
2005
IEEE
139views Bioinformatics» more  CSB 2005»
10 years 7 months ago
Predicting gene function by combining expression and interaction data
In this study we combined the spurious protein interaction data from the Database of Interacting Proteins with the recently published gene expression data of S. cerevisiae grown w...
Rogier J. P. van Berlo, Lodewyk F. A. Wessels, S. ...
BMCBI
2010
179views more  BMCBI 2010»
10 years 1 months ago
A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties
Background: Genetic interaction profiles are highly informative and helpful for understanding the functional linkages between genes, and therefore have been extensively exploited ...
Zhuhong You, Zheng Yin, Kyungsook Han, De-Shuang H...
BMCBI
2007
128views more  BMCBI 2007»
10 years 1 months ago
Combining classifiers to predict gene function in Arabidopsis thaliana using large-scale gene expression measurements
Background: Arabidopsis thaliana is the model species of current plant genomic research with a genome size of 125 Mb and approximately 28,000 genes. The function of half of these ...
Hui Lan, Rachel Carson, Nicholas J. Provart, Antho...
BMCBI
2008
111views more  BMCBI 2008»
10 years 1 months ago
Information-based methods for predicting gene function from systematic gene knock-downs
Background: The rapid annotation of genes on a genome-wide scale is now possible for several organisms using high-throughput RNA interference assays to knock down the expression o...
Matthew T. Weirauch, Christopher K. Wong, Alexandr...
BMCBI
2008
160views more  BMCBI 2008»
10 years 1 months ago
Predicting cancer involvement of genes from heterogeneous data
Background: Systematic approaches for identifying proteins involved in different types of cancer are needed. Experimental techniques such as microarrays are being used to characte...
Ramon Aragues, Chris Sander, Baldo Oliva
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