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Title: Kernel Methods for Chemical Compounds: From Classification to Design
Authors: AKUTSU, Tatsuya  kyouindb  KAKEN_id  orcid (unconfirmed)
NAGAMOCHI, Hiroshi  kyouindb  KAKEN_id
Author's alias: 阿久津, 達也
Keywords: chemoinformatics
kernel method
dynamic programming
graph detachment
Issue Date: Oct-2011
Publisher: IEICE(電子情報通信学会)
Journal title: IEICE Transactions on Information and Systems
Volume: E94-D
Issue: 10
Start page: 1846
End page: 1853
Abstract: In this paper, we briefly review kernel methods for analysis of chemical compounds with focusing on the authors' works. We begin with a brief review of existing kernel functions that are used for classification of chemical compounds and prediction of their activities. Then, we focus on the pre-image problem for chemical compounds, which is to infer a chemical structure that is mapped to a given feature vector, and has a potential application to design of novel chemical compounds. In particular, we consider the pre-image problem for feature vectors consisting of frequencies of labeled paths of length at most K. We present several time complexity results that include: NP-hardness result for a general case, polynomial time algorithm for tree structured compounds with fixed K, and polynomial time algorithm for K=1 based on graph detachment. Then we review practical algorithms for the pre-image problem, which are based on enumeration of chemical structures satisfying given constraints. We also briefly review related results which include efficient enumeration of stereoisomers of tree-like chemical compounds and efficient enumeration of outerplanar graphs.
Rights: (c) 2011 The Institute of Electronics, Information and Communication Engineers
DOI(Published Version): 10.1587/transinf.E94.D.1846
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