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  Mutagenetic tree Fisher kernel improves prediction of HIV drug resistance from viral genotype

Sing, T., & Beerenwinkel, N. (2007). Mutagenetic tree Fisher kernel improves prediction of HIV drug resistance from viral genotype. In B. Schölkopf, J. C. Platt, & T. Hofmann (Eds.), Advances in Neural Information Processing Systems 19 (pp. 1297-1304). Cambridge, Mass.: MIT Press.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-000F-1FF9-7 Version Permalink: https://hdl.handle.net/11858/00-001M-0000-0024-A56E-D
Genre: Conference Paper

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 Creators:
Sing, Tobias1, Author           
Beerenwinkel, Niko1, Author           
Affiliations:
1Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society, ou_40046              

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 Abstract: Starting with the work of Jaakkola and Haussler, a variety of approaches have been proposed for coupling domain-specific generative models with statistical learning methods. The link is established by a kernel function which provides a similarity measure based inherently on the underlying model. In computational biology, the full promise of this framework has rarely ever been exploited, as most kernels are derived from very generic models, such as sequence profiles or hidden Markov models. Here, we introduce the MTreeMix kernel, which is based on a generative model tailored to the underlying biological mechanism. Specifically, the kernel quantifies the similarity of evolutionary escape from antiviral drug pressure between two viral sequence samples. We compare this novel kernel to a standard, evolution-agnostic amino acid encoding in the prediction of HIV drug resistance from genotype, using support vector regression. The results show significant improvements in predictive performance across 17 anti-HIV drugs. Thus, in our study, the generative-discriminative paradigm is key to bridging the gap between population genetic modeling and clinical decision making.

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Language(s): eng - English
 Dates: 2007
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: eDoc: 356657
Other: Local-ID: C12573CC004A8E26-845535906AEB88E6C12572880055BEE4-SingNIPS2006
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Title: Twenteenth Annual Conference on Neural Information Processing Systems
Place of Event: Vancouver, BC, Canada
Start-/End Date: 2006-12-04 - 2006-12-07

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Title: Advances in Neural Information Processing Systems 19
  Abbreviation : NIPS 2006
Source Genre: Proceedings
 Creator(s):
Schölkopf, Bernhard1, Editor
Platt, John C.1, Editor
Hofmann, Thomas1, Editor
Affiliations:
1 External Organizations, ou_persistent22            
Publ. Info: Cambridge, Mass. : MIT Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 1297 - 1304 Identifier: ISBN: 0-262-19568-2