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  PALMA: mRNA to Genome Alignments using Large Margin Algorithms

Schulze, U., Hepp, B., Ong, C., & Rätsch, G. (2007). PALMA: mRNA to Genome Alignments using Large Margin Algorithms. Bioinformatics, 23(15), 1892-1900. doi:10.1093/bioinformatics/btm275.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-CDBD-6 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-CB9A-B
Genre: Journal Article

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Schulze, U1, Author
Hepp, B, Author
Ong, CS1, 2, 3, Author              
Rätsch, G1, Author              
Affiliations:
1Friedrich Miescher Laboratory, Max Planck Society, Max-Planck-Ring 9, 72076 Tübingen, DE, ou_2575692              
2Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
3Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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 Abstract: Motivation: Despite many years of research on how to properly align sequences in the presence of sequencing errors, alternative splicing and micro-exons, the correct alignment of mRNA sequences to genomic DNA is still a challenging task. Results: We present a novel approach based on large margin learning that combines accurate plice site predictions with common sequence alignment techniques. By solving a convex optimization problem, our algorithm – called PALMA – tunes the parameters of the model such that true alignments score higher than other alignments. We study the accuracy of alignments of mRNAs containing artificially generated micro-exons to genomic DNA. In a carefully designed experiment, we show that our algorithm accurately identifies the intron boundaries as well as boundaries of the optimal local alignment. It outperforms all other methods: for 5702 artificially shortened EST sequences from C. elegans and human it correctly identifies the intron boundaries in all except two cases. The best other method is a recently proposed method called exalin which misaligns 37 of the sequences. Our method also demonstrates robustness to mutations, insertions and deletions, retaining accuracy even at high noise levels. Availability: Datasets for training, evaluation and testing, additional results and a stand-alone alignment tool implemented in C++ and python are available at http://www.fml.mpg.de/raetsch/projects/palma.

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 Dates: 2007-05
 Publication Status: Published in print
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 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1093/bioinformatics/btm275
BibTex Citekey: 4498
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Title: Bioinformatics
Source Genre: Journal
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Publ. Info: Oxford : Oxford University Press
Pages: - Volume / Issue: 23 (15) Sequence Number: - Start / End Page: 1892 - 1900 Identifier: ISSN: 1367-4803
CoNE: https://pure.mpg.de/cone/journals/resource/954926969991