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» Gene function prediction using labeled and unlabeled data
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BMCBI
2008
129views more  BMCBI 2008»
14 years 10 months ago
Mining phenotypes for gene function prediction
Background: Health and disease of organisms are reflected in their phenotypes. Often, a genetic component to a disease is discovered only after clearly defining its phenotype. In ...
Philip Groth, Bertram Weiss, Hans-Dieter Pohlenz, ...
CSB
2005
IEEE
133views Bioinformatics» more  CSB 2005»
15 years 3 months ago
Biological Pathway Prediction from Multiple Data Sources Using Iterative Bayesian Updating
There is a diversity of functional genomics data, such as gene expression data from microarray experiments, phenotypic data from gene deletion experiments, protein-protein interac...
Corey Powell, Joshua M. Stuart
CSB
2005
IEEE
139views Bioinformatics» more  CSB 2005»
15 years 3 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
2006
126views more  BMCBI 2006»
14 years 10 months ago
A Regression-based K nearest neighbor algorithm for gene function prediction from heterogeneous data
Background: As a variety of functional genomic and proteomic techniques become available, there is an increasing need for functional analysis methodologies that integrate heteroge...
Zizhen Yao, Walter L. Ruzzo
CSB
2005
IEEE
189views Bioinformatics» more  CSB 2005»
15 years 3 months ago
Learning Yeast Gene Functions from Heterogeneous Sources of Data Using Hybrid Weighted Bayesian Networks
We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
Xutao Deng, Huimin Geng, Hesham H. Ali