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  A Linear Programming Approach for Molecular QSAR analysis

Saigo, H., Kadowaki, T., & Tsuda, K. (2009). A Linear Programming Approach for Molecular QSAR analysis. In T. Gärtner, G. Garriga, & T. Meinl (Eds.), MLG 2006: Proceedings of the International Workshop on Mining and Learning with Graphs in conjunction with ECML/PKDD 2006 (pp. 85-96). Konstanz, Germany: Bibliothek der Universität Konstanz.

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MLG-2006-Saigo.pdf (Any fulltext), 207KB
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 Creators:
Saigo, H1, 2, Author              
Kadowaki, T, Author
Tsuda, K1, 2, Author              
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: Small molecules in chemistry can be represented as graphs. In a quantitative structure-activity relationship (QSAR) analysis, the central task is to find a regression function that predicts the activity of the molecule in high accuracy. Setting a QSAR as a primal target, we propose a new linear programming approach to the graph-based regression problem. Our method extends the graph classification algorithm by Kudo et al. (NIPS 2004), which is a combination of boosting and graph mining. Instead of sequential multiplicative updates, we employ the linear programming boosting (LP) for regression. The LP approach allows to include inequality constraints for the parameter vector, which turns out to be particularly useful in QSAR tasks where activity values are sometimes unavailable. Furthermore, the efficiency is improved significantly by employing multiple pricing.

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 Dates: 2009
 Publication Status: Published in print
 Pages: -
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 Rev. Type: -
 Identifiers: BibTex Citekey: 4160
 Degree: -

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Title: International Workshop on Mining and Learning with Graphs 2006 (MLG 2006)
Place of Event: Berlin, Germany
Start-/End Date: 2006-09-18

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Title: MLG 2006: Proceedings of the International Workshop on Mining and Learning with Graphs in conjunction with ECML/PKDD 2006
Source Genre: Proceedings
 Creator(s):
Gärtner, T, Editor
Garriga, GC, Editor
Meinl, T, Editor
Affiliations:
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Publ. Info: Konstanz, Germany : Bibliothek der Universität Konstanz
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 85 - 96 Identifier: -