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CIDANE: Comprehensive Isoform Discovery and Abundance Estimation

  • Stefan CanzarEmail author
  • Sandro Andreotti
  • David Weese
  • Knut Reinert
  • Gunnar W. Klau
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9029)

Abstract

High-throughput sequencing of cellular RNA (RNA-seq) allows to assess the set of all RNA molecules, the transcriptome, produced by a cell at a high resolution, under various conditions. The assembly of short sequencing reads to full-length transcripts, however, poses profound challenges to bioinformatics tools.

Keywords

Integer Linear Programming Abundance Estimation Result Optimization Problem Lasso Regression Regularization Path 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

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    Li, J.J., Jiang, C.R., Brown, J.B., Huang, H., Bickel, P.J.: Sparse linear modeling of next-generation mRNA sequencing (RNA-Seq) data for isoform discovery and abundance estimation. Proceedings of the National Academy of Sciences 108(50), 19867–19872 (2011). http://www.pnas.org/content/108/50/19867.abstract CrossRefGoogle Scholar
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    Li, W., Feng, J., Jiang, T.: IsoLasso: A LASSO regression approach to RNA-seq based transcriptome assembly. Journal of Computational Biology 18(11), 1693–1707 (2011)CrossRefMathSciNetGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Stefan Canzar
    • 1
    • 2
    Email author
  • Sandro Andreotti
    • 3
  • David Weese
    • 3
  • Knut Reinert
    • 3
  • Gunnar W. Klau
    • 4
  1. 1.Center for Computational BiologyJohns Hopkins University School of MedicineBaltimoreUSA
  2. 2.Toyota Technological Institute at ChicagoChicagoUSA
  3. 3.Department of Mathematics and Computer Science, Institute of Computer ScienceFreie Universität BerlinBerlinGermany
  4. 4.Life SciencesCentrum Wiskunde & Informatica (CWI)AmsterdamThe Netherlands

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