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» Gene function prediction using labeled and unlabeled data
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BMCBI
2010
135views more  BMCBI 2010»
15 years 4 months ago
Simple and flexible classification of gene expression microarrays via Swirls and Ripples
Background: A simple classification rule with few genes and parameters is desirable when applying a classification rule to new data. One popular simple classification rule, diagon...
Stuart G. Baker
PAKDD
2005
ACM
180views Data Mining» more  PAKDD 2005»
15 years 9 months ago
Conditional Random Fields for Transmembrane Helix Prediction
Abstract. It is estimated that 20% of genes in the human genome encode for integral membrane proteins (IMPs) and some estimates are much higher. IMPs control a broad range of event...
Lior Lukov, Sanjay Chawla, W. Bret Church
125
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AAAI
2010
15 years 5 months ago
G-Optimal Design with Laplacian Regularization
In many real world applications, labeled data are usually expensive to get, while there may be a large amount of unlabeled data. To reduce the labeling cost, active learning attem...
Chun Chen, Zhengguang Chen, Jiajun Bu, Can Wang, L...
BMCBI
2010
104views more  BMCBI 2010»
14 years 11 months ago
A systematic study of genome context methods: calibration, normalization and combination
Background: Genome context methods have been introduced in the last decade as automatic methods to predict functional relatedness between genes in a target genome using the patter...
Luciana Ferrer, Joseph M. Dale, Peter D. Karp
BMCBI
2006
202views more  BMCBI 2006»
15 years 4 months ago
Integrated biclustering of heterogeneous genome-wide datasets for the inference of global regulatory networks
Background: The learning of global genetic regulatory networks from expression data is a severely under-constrained problem that is aided by reducing the dimensionality of the sea...
David J. Reiss, Nitin S. Baliga, Richard Bonneau