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CSB
2005
IEEE
189views Bioinformatics» more  CSB 2005»
11 years 5 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
BIBM
2008
IEEE
217views Bioinformatics» more  BIBM 2008»
11 years 6 months ago
Combining Hierarchical Inference in Ontologies with Heterogeneous Data Sources Improves Gene Function Prediction
The study of gene function is critical in various genomic and proteomic fields. Due to the availability of tremendous amounts of different types of protein data, integrating thes...
Xiaoyu Jiang, Naoki Nariai, Martin Steffen, Simon ...
BIBM
2008
IEEE
107views Bioinformatics» more  BIBM 2008»
11 years 6 months ago
A Functional Network of Yeast Genes Using Gene Ontology Information
In the post-genomic era, the organization of genes into networks has played an important role in characterizing the functions of individual genes and the interplay between them. I...
Erliang Zeng, Giri Narasimhan, Lisa Schneper, Kala...
BIBM
2008
IEEE
175views Bioinformatics» more  BIBM 2008»
11 years 6 months ago
Integrative Protein Function Transfer Using Factor Graphs and Heterogeneous Data Sources
We propose a novel approach for predicting protein functions of an organism by coupling sequence homology and PPI data between two (or more) species with multifunctional Gene Onto...
Antonina Mitrofanova, Vladimir Pavlovic, Bud Mishr...
SDM
2012
SIAM
252views Data Mining» more  SDM 2012»
9 years 2 months ago
Learning from Heterogeneous Sources via Gradient Boosting Consensus
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...
Xiaoxiao Shi, Jean-François Paiement, David...
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