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CVPR
2005
IEEE
16 years 3 months ago
Joint Nonparametric Alignment for Analyzing Spatial Gene Expression Patterns in Drosophila Imaginal Discs
To compare spatial patterns of gene expression, one must analyze a large number of images as current methods are only able to measure a small number of genes at a time. Bringing i...
Parvez Ahammad, Cyrus L. Harmon, Ann Hammonds, Sha...
BMCBI
2006
216views more  BMCBI 2006»
15 years 1 months ago
Machine learning approaches to supporting the identification of photoreceptor-enriched genes based on expression data
Background: Retinal photoreceptors are highly specialised cells, which detect light and are central to mammalian vision. Many retinal diseases occur as a result of inherited dysfu...
Haiying Wang, Huiru Zheng, David Simpson, Francisc...
CVPR
2003
IEEE
16 years 3 months ago
Learning Bayesian Network Classifiers for Facial Expression Recognition using both Labeled and Unlabeled Data
Understanding human emotions is one of the necessary skills for the computer to interact intelligently with human users. The most expressive way humans display emotions is through...
Ira Cohen, Nicu Sebe, Fabio Gagliardi Cozman, Marc...
BMCBI
2008
166views more  BMCBI 2008»
15 years 1 months ago
Learning transcriptional regulatory networks from high throughput gene expression data using continuous three-way mutual informa
Background: Probability based statistical learning methods such as mutual information and Bayesian networks have emerged as a major category of tools for reverse engineering mecha...
Weijun Luo, Kurt D. Hankenson, Peter J. Woolf
WWW
2010
ACM
15 years 8 months ago
A scalable machine-learning approach for semi-structured named entity recognition
Named entity recognition studies the problem of locating and classifying parts of free text into a set of predefined categories. Although extensive research has focused on the de...
Utku Irmak, Reiner Kraft