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Scoring functions for transcription factor binding site prediction
BACKGROUND: Transcription factor binding site (TFBS) prediction is a difficult problem, which requires a good scoring function to discriminate between real binding sites and background noise. Many scoring functions have been proposed in the literature, but it is difficult to assess their relative pe...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2005
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1140076/ https://www.ncbi.nlm.nih.gov/pubmed/15807889 http://dx.doi.org/10.1186/1471-2105-6-84 |
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author | Friberg, Markus von Rohr, Peter Gonnet, Gaston |
author_facet | Friberg, Markus von Rohr, Peter Gonnet, Gaston |
author_sort | Friberg, Markus |
collection | PubMed |
description | BACKGROUND: Transcription factor binding site (TFBS) prediction is a difficult problem, which requires a good scoring function to discriminate between real binding sites and background noise. Many scoring functions have been proposed in the literature, but it is difficult to assess their relative performance, because they are implemented in different software tools using different search methods and different TFBS representations. RESULTS: Here we compare how several scoring functions perform on both real and semi-simulated data sets in a common test environment. We have also developed two new scoring functions and included them in the comparison. The data sets are from the yeast (S. cerevisiae) genome. Our new scoring function LLBG (least likely under the background model) performs best in this study. It achieves the best average rank for the correct motifs. Scoring functions based on positional bias performed quite poorly in this study. CONCLUSION: LLBG may provide an interesting alternative to current scoring functions for TFBS prediction. |
format | Text |
id | pubmed-1140076 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2005 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-11400762005-05-25 Scoring functions for transcription factor binding site prediction Friberg, Markus von Rohr, Peter Gonnet, Gaston BMC Bioinformatics Research Article BACKGROUND: Transcription factor binding site (TFBS) prediction is a difficult problem, which requires a good scoring function to discriminate between real binding sites and background noise. Many scoring functions have been proposed in the literature, but it is difficult to assess their relative performance, because they are implemented in different software tools using different search methods and different TFBS representations. RESULTS: Here we compare how several scoring functions perform on both real and semi-simulated data sets in a common test environment. We have also developed two new scoring functions and included them in the comparison. The data sets are from the yeast (S. cerevisiae) genome. Our new scoring function LLBG (least likely under the background model) performs best in this study. It achieves the best average rank for the correct motifs. Scoring functions based on positional bias performed quite poorly in this study. CONCLUSION: LLBG may provide an interesting alternative to current scoring functions for TFBS prediction. BioMed Central 2005-04-04 /pmc/articles/PMC1140076/ /pubmed/15807889 http://dx.doi.org/10.1186/1471-2105-6-84 Text en Copyright © 2005 Friberg et al; licensee BioMed Central Ltd. |
spellingShingle | Research Article Friberg, Markus von Rohr, Peter Gonnet, Gaston Scoring functions for transcription factor binding site prediction |
title | Scoring functions for transcription factor binding site prediction |
title_full | Scoring functions for transcription factor binding site prediction |
title_fullStr | Scoring functions for transcription factor binding site prediction |
title_full_unstemmed | Scoring functions for transcription factor binding site prediction |
title_short | Scoring functions for transcription factor binding site prediction |
title_sort | scoring functions for transcription factor binding site prediction |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1140076/ https://www.ncbi.nlm.nih.gov/pubmed/15807889 http://dx.doi.org/10.1186/1471-2105-6-84 |
work_keys_str_mv | AT fribergmarkus scoringfunctionsfortranscriptionfactorbindingsiteprediction AT vonrohrpeter scoringfunctionsfortranscriptionfactorbindingsiteprediction AT gonnetgaston scoringfunctionsfortranscriptionfactorbindingsiteprediction |