Genome-wide prokaryotic promoter recognition based on sequence alignment kernel

Leo Gordon; Alexey Ya Chervonenkis; Alex J. Gammerman; Ilham Shahmuradov; Victor V. Solovyev

Genome-wide prokaryotic promoter recognition based on sequence alignment kernel

Leo Gordon^*, Alexey Ya Chervonenkis, Alex J. Gammerman, Ilham Shahmuradov, Victor V. Solovyev

^*Corresponding author for this work

Computational Bioscience Research Center

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

In this paper an application of Sequence Alignment Kernel for recognition of prokaryotic promoters with transcription start sites (TSS) is presented. An algorithm for computing this kernel in square time is described. Using this algorithm, a "promoter map" of E.coli genome has been computed. This is a curve reflecting the likelihood of every base of a given genomic sequence to be a TSS. A viewer showing the likelihood curve with positions of known and putative genes and known TSS has also been developed and made available online. Although the visual analysis of the promoter regions is very intuitive, we propose an automatic genome-wide promoter prediction scheme that simplifies the routine of checking the whole promoter map visually. Computational efficiency and speed issue are also discussed.

Original language	English (US)
Pages (from-to)	386-396
Number of pages	11
Journal	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	2810
State	Published - Dec 1 2003

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Cite this

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title = "Genome-wide prokaryotic promoter recognition based on sequence alignment kernel",

abstract = "In this paper an application of Sequence Alignment Kernel for recognition of prokaryotic promoters with transcription start sites (TSS) is presented. An algorithm for computing this kernel in square time is described. Using this algorithm, a {"}promoter map{"} of E.coli genome has been computed. This is a curve reflecting the likelihood of every base of a given genomic sequence to be a TSS. A viewer showing the likelihood curve with positions of known and putative genes and known TSS has also been developed and made available online. Although the visual analysis of the promoter regions is very intuitive, we propose an automatic genome-wide promoter prediction scheme that simplifies the routine of checking the whole promoter map visually. Computational efficiency and speed issue are also discussed.",

author = "Leo Gordon and Chervonenkis, {Alexey Ya} and Gammerman, {Alex J.} and Ilham Shahmuradov and Solovyev, {Victor V.}",

year = "2003",

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language = "English (US)",

volume = "2810",

pages = "386--396",

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Genome-wide prokaryotic promoter recognition based on sequence alignment kernel. / Gordon, Leo; Chervonenkis, Alexey Ya; Gammerman, Alex J. et al.
In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 2810, 01.12.2003, p. 386-396.

Research output: Contribution to journal › Article › peer-review

TY - JOUR

T1 - Genome-wide prokaryotic promoter recognition based on sequence alignment kernel

AU - Gordon, Leo

AU - Chervonenkis, Alexey Ya

AU - Gammerman, Alex J.

AU - Shahmuradov, Ilham

AU - Solovyev, Victor V.

PY - 2003/12/1

Y1 - 2003/12/1

N2 - In this paper an application of Sequence Alignment Kernel for recognition of prokaryotic promoters with transcription start sites (TSS) is presented. An algorithm for computing this kernel in square time is described. Using this algorithm, a "promoter map" of E.coli genome has been computed. This is a curve reflecting the likelihood of every base of a given genomic sequence to be a TSS. A viewer showing the likelihood curve with positions of known and putative genes and known TSS has also been developed and made available online. Although the visual analysis of the promoter regions is very intuitive, we propose an automatic genome-wide promoter prediction scheme that simplifies the routine of checking the whole promoter map visually. Computational efficiency and speed issue are also discussed.

AB - In this paper an application of Sequence Alignment Kernel for recognition of prokaryotic promoters with transcription start sites (TSS) is presented. An algorithm for computing this kernel in square time is described. Using this algorithm, a "promoter map" of E.coli genome has been computed. This is a curve reflecting the likelihood of every base of a given genomic sequence to be a TSS. A viewer showing the likelihood curve with positions of known and putative genes and known TSS has also been developed and made available online. Although the visual analysis of the promoter regions is very intuitive, we propose an automatic genome-wide promoter prediction scheme that simplifies the routine of checking the whole promoter map visually. Computational efficiency and speed issue are also discussed.

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JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Genome-wide prokaryotic promoter recognition based on sequence alignment kernel

Abstract

ASJC Scopus subject areas

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