Extracting Best Consensus Motifs from Positive and Negative Examples

Erika Tateishi, Osamu Maruyama, Satoru Miyano

研究成果: Contribution to journalArticle

抜粋

We define the best consensus motif (BCM) problem motivated by the problem of extracting motifs from nucleic acid and amino acid sequences. A type over an alphabetΣ is a familyΩ of subsets of Σ. A motif π of type Ω is a stringπ=π_1…π_n of motif components, each of which stands for an element in Ω. The BCM problem for Ω is, given a yes-no sample S={(α^<(1)>, β^<(1)>),...,(α^<(m)>, β^<(m)>)} of pairs of strings inΣ with α^<(i)>≠β^<(i)> for 1≤i≤m, to find a motif π of type Ω that maximizes the number of good pairs in S, where (α^<(i)>,β^<(i)>) is good forπ if π accepts α^<(i)> and rejects β^<(i)>. We prove that the BCM problem is NP-complete even for a very simple type Ω_1={z|φ≠z⊆Σ}, which is used, in practice, for describing protein motifs in the PROSITE database. We also show that the NP-completeness of the problem does not change for the type Ω_∞=Ω_1∪{Σ+}∪{Σ^<(i, j)>|1≤i≤j}, whereΣ^<(i, j)> is the set of strings over Σ of length between i and j. Furthermore, for the BCM problem forΩ_1, we provide a polynomial-time greedy algorithm based on the probabilistic method. Its performance analysis shows an explicit approximation ratio of the algorithm.
元の言語英語
ページ(範囲)55-64
ページ数10
ジャーナルIEICE technical report. Theoretical foundations of Computing
95
発行部数344
出版物ステータス出版済み - 10 27 1995

フィンガープリント Extracting Best Consensus Motifs from Positive and Negative Examples' の研究トピックを掘り下げます。これらはともに一意のフィンガープリントを構成します。

  • これを引用