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» Using Multiple Alignments to Improve Gene Prediction
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IEAAIE
2010
Springer
13 years 5 months ago
S.cerevisiae Complex Function Prediction with Modular Multi-Relational Framework
Gene functions is an essential knowledge for understanding how metabolism works and designing treatments for solving malfunctions. The Modular Multi-Relational Framework (MMRF) is ...
Beatriz García Jiménez, Agapito Lede...
NIPS
2003
13 years 8 months ago
Gene Expression Clustering with Functional Mixture Models
We propose a functional mixture model for simultaneous clustering and alignment of sets of curves measured on a discrete time grid. The model is specifically tailored to gene exp...
Darya Chudova, Christopher E. Hart, Eric Mjolsness...
BIB
2007
59views more  BIB 2007»
13 years 7 months ago
Statistically designing microarrays and microarray experiments to enhance sensitivity and specificity
Gene expression signatures from microarray experiments promise to provide important prognostic tools for predicting disease outcome or response to treatment. A number of microarra...
Jason C. Hsu, Jane Chang, Tao Wang, Eiríkur...
ACIIDS
2010
IEEE
170views Database» more  ACIIDS 2010»
13 years 5 months ago
On the Effectiveness of Gene Selection for Microarray Classification Methods
Microarray data usually contains a high level of noisy gene data, the noisy gene data include incorrect, noise and irrelevant genes. Before Microarray data classification takes pla...
Zhongwei Zhang, Jiuyong Li, Hong Hu, Hong Zhou
CSB
2005
IEEE
139views Bioinformatics» more  CSB 2005»
14 years 1 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. ...