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BMCBI
2008
100views more  BMCBI 2008»
13 years 4 months ago
High-precision high-coverage functional inference from integrated data sources
Background: Information obtained from diverse data sources can be combined in a principled manner using various machine learning methods to increase the reliability and range of k...
Bolan Linghu, Evan S. Snitkin, Dustin T. Holloway,...
BIBM
2008
IEEE
217views Bioinformatics» more  BIBM 2008»
13 years 11 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 ...
RECOMB
2006
Springer
14 years 5 months ago
Integrated Protein Interaction Networks for 11 Microbes
We have combined four different types of functional genomic data to create high coverage protein interaction networks for 11 microbes. Our integration algorithm naturally handles s...
Balaji S. Srinivasan, Antal F. Novak, Jason Flanni...
CSB
2005
IEEE
189views Bioinformatics» more  CSB 2005»
13 years 10 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
BMCBI
2006
126views more  BMCBI 2006»
13 years 4 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