Combining discrete and probabilistic methods improves accuracy in sequence modeling

被引：0

作者：

Gudjonsson, L ^{[1
]}

Laurio, K ^{[1
]}

Olsson, B ^{[1
]}

机构：

[1] Univ Skovde, Dept Comp Sci, S-54128 Skovde, Sweden

来源：

PROCEEDINGS OF THE FIFTH JOINT CONFERENCE ON INFORMATION SCIENCES, VOLS 1 AND 2 | 2000年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Current approaches to the problem of modeling protein sequence families use either discrete or probabilistic methods. In this paper we present an approach for combining these two types of methods to derive hybrid models. We show that hybrid models - using discrete patterns for conserved regions and probabilistic hidden Markov models for variable regions - give increased classification accuracy when compared to pure discrete or probabilistic models.

引用

页码：A790 / A793

页数：4

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