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» Learning Methods for DNA Binding in Computational Biology
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BMCBI
2010
173views more  BMCBI 2010»
14 years 11 months ago
The Yeast Resource Center Public Image Repository: A large database of fluorescence microscopy images
Background: There is increasing interest in the development of computational methods to analyze fluorescent microscopy images and enable automated large-scale analysis of the subc...
Michael Riffle, Trisha N. Davis
BMCBI
2010
176views more  BMCBI 2010»
14 years 11 months ago
TargetSpy: a supervised machine learning approach for microRNA target prediction
Background: Virtually all currently available microRNA target site prediction algorithms require the presence of a (conserved) seed match to the 5' end of the microRNA. Recen...
Martin Sturm, Michael Hackenberg, David Langenberg...
NECO
2007
127views more  NECO 2007»
14 years 10 months ago
Visual Recognition and Inference Using Dynamic Overcomplete Sparse Learning
We present a hierarchical architecture and learning algorithm for visual recognition and other visual inference tasks such as imagination, reconstruction of occluded images, and e...
Joseph F. Murray, Kenneth Kreutz-Delgado
CORR
2012
Springer
170views Education» more  CORR 2012»
13 years 7 months ago
What Cannot be Learned with Bethe Approximations
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
Uri Heinemann, Amir Globerson
BMCBI
2008
138views more  BMCBI 2008»
14 years 11 months ago
Systematic identification of yeast cell cycle transcription factors using multiple data sources
Background: Eukaryotic cell cycle is a complex process and is precisely regulated at many levels. Many genes specific to the cell cycle are regulated transcriptionally and are exp...
Wei-Sheng Wu, Wen-Hsiung Li