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  Semi-supervised learning for the identification of syn-expressed genes from fused microarray and in situ image data.

Costa, I. G., Krause, R., Opitz, L., & Schliep, A. (2007). Semi-supervised learning for the identification of syn-expressed genes from fused microarray and in situ image data. Whistler, Canada: BioMed Central Ltd.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-80F5-5 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-80F6-3
Genre: Proceedings
Alternative Title : BMC Bioinformatics

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1471-2105-8-S10-S3.pdf (Any fulltext), 3MB
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Costa, Ivan G.1, Author              
Krause, Roland1, Author              
Opitz, Lennard, Author
Schliep, Alexander1, Author              
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1Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433547              

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 Abstract: Background: Gene expression measurements during the development of the fly Drosophila melanogaster are routinely used to find functional modules of temporally co-expressed genes. Complimentary large data sets of in situ RNA hybridization images for different stages of the fly embryo elucidate the spatial expression patterns. Results: Using a semi-supervised approach, constrained clustering with mixture models, we can find clusters of genes exhibiting spatio-temporal similarities in expression, or syn-expression. The temporal gene expression measurements are taken as primary data for which pairwise constraints are computed in an automated fashion from raw in situ images without the need for manual annotation. We investigate the influence of these pairwise constraints in the clustering and discuss the biological relevance of our results. Conclusion: Spatial information contributes to a detailed, biological meaningful analysis of temporal gene expression data. Semi-supervised learning provides a flexible, robust and efficient framework for integrating data sources of differing quality and abundance.

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Language(s): eng - English
 Dates: 2007-12-21
 Publication Status: Published in print
 Pages: S1-S8
 Publishing info: Whistler, Canada : BioMed Central Ltd.
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Title: Neural Information Processing Systems (NIPS) workshop on New Problems and Methods in Computational Biology
Place of Event: Whistler, Canada
Start-/End Date: 2006-12-08 - 2006-12-08

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Title: Neural Information Processing Systems (NIPS) workshop on New Problems and Methods in Computational Biology
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Pages: S1-S8 Volume / Issue: - Sequence Number: - Start / End Page: - Identifier: -

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Title: BMC Bioinformatics
  Alternative Title : BMC Bioinformatics
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Pages: S1-S8 Volume / Issue: (8(Suppl 10)) Sequence Number: - Start / End Page: - Identifier: -