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» Using Multiple Alignments to Improve Gene Prediction
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137
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KBS
2006
79views more  KBS 2006»
15 years 3 months ago
Using multiple and negative target rules to make classifiers more understandable
One major goal for data mining is to understand data. Rule based methods are better than other methods in making mining results comprehensible. However, the current rule based cla...
Jiuyong Li, Jason Jones
121
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BMCBI
2007
126views more  BMCBI 2007»
15 years 3 months ago
Including probe-level uncertainty in model-based gene expression clustering
Background: Clustering is an important analysis performed on microarray gene expression data since it groups genes which have similar expression patterns and enables the explorati...
Xuejun Liu, Kevin K. Lin, Bogi Andersen, Magnus Ra...
137
Voted
IBPRIA
2007
Springer
15 years 9 months ago
Robust Multiple-People Tracking Using Colour-Based Particle Filters
Robust and accurate people tracking is a key task in many promising computer-vision applications. One must deal with non-rigid targets in open-world scenarios, whose shape and appe...
Daniel Rowe, Ivan Huerta Casado, Jordi Gonzà...
140
Voted
MDAI
2005
Springer
15 years 9 months ago
Cancer Prediction Using Diversity-Based Ensemble Genetic Programming
Combining a set of classifiers has often been exploited to improve the classification performance. Accurate as well as diverse base classifiers are prerequisite to construct a good...
Jin-Hyuk Hong, Sung-Bae Cho
139
Voted
BMCBI
2007
147views more  BMCBI 2007»
15 years 3 months ago
Statistical analysis and significance testing of serial analysis of gene expression data using a Poisson mixture model
Background: Serial analysis of gene expression (SAGE) is used to obtain quantitative snapshots of the transcriptome. These profiles are count-based and are assumed to follow a Bin...
Scott D. Zuyderduyn