Analysis of computational approaches for motif discovery
<p>Abstract</p> <p>Recently, we performed an assessment of 13 popular computational tools for discovery of transcription factor binding sites (M. Tompa, N. Li, et al., "Assessing Computational Tools for the Discovery of Transcription Factor Binding Sites", Nature Biotechn...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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BMC
2006-05-01
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| Series: | Algorithms for Molecular Biology |
| Online Access: | http://www.almob.org/content/1/1/8 |
| _version_ | 1818834107868643328 |
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| author | Tompa Martin Li Nan |
| author_facet | Tompa Martin Li Nan |
| author_sort | Tompa Martin |
| collection | DOAJ |
| description | <p>Abstract</p> <p>Recently, we performed an assessment of 13 popular computational tools for discovery of transcription factor binding sites (M. Tompa, N. Li, et al., "Assessing Computational Tools for the Discovery of Transcription Factor Binding Sites", Nature Biotechnology, Jan. 2005). This paper contains follow-up analysis of the assessment results, and raises and discusses some important issues concerning the state of the art in motif discovery methods: 1. We categorize the objective functions used by existing tools, and design experiments to evaluate whether any of these objective functions is the right one to optimize. 2. We examine various features of the data sets that were used in the assessment, such as sequence length and motif degeneracy, and identify which features make data sets hard for current motif discovery tools. 3. We identify an important feature that has not yet been used by existing tools and propose a new objective function that incorporates this feature.</p> |
| first_indexed | 2024-12-19T02:29:34Z |
| format | Article |
| id | doaj.art-279a714983f64b118f9846681ed48f50 |
| institution | Directory Open Access Journal |
| issn | 1748-7188 |
| language | English |
| last_indexed | 2024-12-19T02:29:34Z |
| publishDate | 2006-05-01 |
| publisher | BMC |
| record_format | Article |
| series | Algorithms for Molecular Biology |
| spelling | doaj.art-279a714983f64b118f9846681ed48f502022-12-21T20:39:41ZengBMCAlgorithms for Molecular Biology1748-71882006-05-0111810.1186/1748-7188-1-8Analysis of computational approaches for motif discoveryTompa MartinLi Nan<p>Abstract</p> <p>Recently, we performed an assessment of 13 popular computational tools for discovery of transcription factor binding sites (M. Tompa, N. Li, et al., "Assessing Computational Tools for the Discovery of Transcription Factor Binding Sites", Nature Biotechnology, Jan. 2005). This paper contains follow-up analysis of the assessment results, and raises and discusses some important issues concerning the state of the art in motif discovery methods: 1. We categorize the objective functions used by existing tools, and design experiments to evaluate whether any of these objective functions is the right one to optimize. 2. We examine various features of the data sets that were used in the assessment, such as sequence length and motif degeneracy, and identify which features make data sets hard for current motif discovery tools. 3. We identify an important feature that has not yet been used by existing tools and propose a new objective function that incorporates this feature.</p>http://www.almob.org/content/1/1/8 |
| spellingShingle | Tompa Martin Li Nan Analysis of computational approaches for motif discovery Algorithms for Molecular Biology |
| title | Analysis of computational approaches for motif discovery |
| title_full | Analysis of computational approaches for motif discovery |
| title_fullStr | Analysis of computational approaches for motif discovery |
| title_full_unstemmed | Analysis of computational approaches for motif discovery |
| title_short | Analysis of computational approaches for motif discovery |
| title_sort | analysis of computational approaches for motif discovery |
| url | http://www.almob.org/content/1/1/8 |
| work_keys_str_mv | AT tompamartin analysisofcomputationalapproachesformotifdiscovery AT linan analysisofcomputationalapproachesformotifdiscovery |