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» Gene function prediction using labeled and unlabeled data
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BMCBI
2010
135views more  BMCBI 2010»
15 years 7 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»
16 years 1 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
AAAI
2010
15 years 9 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»
15 years 2 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 7 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