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» Clustering Genes Using Heterogeneous Data Sources
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DILS
2005
Springer
13 years 11 months ago
Integrating Heterogeneous Microarray Data Sources Using Correlation Signatures
Abstract. Microarrays are one of the latest breakthroughs in experimental molecular biology. Thousands of different research groups generate tens of thousands of microarray gene e...
Jaewoo Kang, Jiong Yang, Wanhong Xu, Pankaj Chopra
IJON
2010
148views more  IJON 2010»
13 years 2 months ago
Integration of heterogeneous data sources for gene function prediction using decision templates and ensembles of learning machin
Several solutions have been proposed to exploit the availability of heterogeneous sources of biomolecular data for gene function prediction, but few attention has been dedicated t...
Matteo Re, Giorgio Valentini
KDD
2008
ACM
206views Data Mining» more  KDD 2008»
14 years 5 months ago
Identifying biologically relevant genes via multiple heterogeneous data sources
Selection of genes that are differentially expressed and critical to a particular biological process has been a major challenge in post-array analysis. Recent development in bioin...
Zheng Zhao, Jiangxin Wang, Huan Liu, Jieping Ye, Y...
BMCBI
2010
171views more  BMCBI 2010»
13 years 5 months ago
PyMix - The Python mixture package - a tool for clustering of heterogeneous biological data
Background: Cluster analysis is an important technique for the exploratory analysis of biological data. Such data is often high-dimensional, inherently noisy and contains outliers...
Benjamin Georgi, Ivan Gesteira Costa, Alexander Sc...
BIBM
2008
IEEE
217views Bioinformatics» more  BIBM 2008»
13 years 12 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 ...