An Algorithm for Identifying Novel Targets of Transcription Factor Families: Application to Hypoxia-inducible Factor 1 Targets
Efficient and effective analysis of the growing genomic databases requires the development of adequate computational tools. We introduce a fast method based on the suffix tree data structure for predicting novel targets of hypoxia-inducible factor 1 (HIF-1) from huge genome databases. The suffix tre...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2009-01-01
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| Series: | Cancer Informatics |
| Subjects: | |
| Online Access: | http://www.la-press.com/an-algorithm-for-identifying-novel-targets-of-transcription-factor-fam-a1340 |
| _version_ | 1831602430784045056 |
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| author | Yue Jiang Bojan Cukic Donald A. Adjeroh Heath D. Skinner Jie Lin Qingxi J. Shen Bing-Hua Jiang |
| author_facet | Yue Jiang Bojan Cukic Donald A. Adjeroh Heath D. Skinner Jie Lin Qingxi J. Shen Bing-Hua Jiang |
| author_sort | Yue Jiang |
| collection | DOAJ |
| description | Efficient and effective analysis of the growing genomic databases requires the development of adequate computational tools. We introduce a fast method based on the suffix tree data structure for predicting novel targets of hypoxia-inducible factor 1 (HIF-1) from huge genome databases. The suffix tree data structure has two powerful applications here: one is to extract unknown patterns from multiple strings/sequences in linear time; the other is to search multiple strings/sequences using multiple patterns in linear time. Using 15 known HIF-1 target gene sequences as a training set, we extracted 105 common patterns that all occur in the 15 training genes using suffix trees. Using these 105 common patterns along with known subsequences surrounding HIF-1 binding sites from the literature, the algorithm searches a genome database that contains 2,078,786 DNA sequences. It reported 258 potentially novel HIF-1 targets including 25 known HIF-1 targets. Based on microarray studies from the literature, 17 putative genes were confirmed to be upregulated by HIF-1 or hypoxia inside these 258 genes. We further studied one of the potential targets, COX-2, in the biological lab; and showed that it was a biologically relevant HIF-1 target. These results demonstrate that our methodology is an effective computational approach for identifying novel HIF-1 targets. |
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| format | Article |
| id | doaj.art-db4e26fee4b3468c817e3f12d05fe7fc |
| institution | Directory Open Access Journal |
| issn | 1176-9351 |
| language | English |
| last_indexed | 2024-12-18T15:19:51Z |
| publishDate | 2009-01-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Cancer Informatics |
| spelling | doaj.art-db4e26fee4b3468c817e3f12d05fe7fc2022-12-21T21:03:25ZengSAGE PublishingCancer Informatics1176-93512009-01-0177589An Algorithm for Identifying Novel Targets of Transcription Factor Families: Application to Hypoxia-inducible Factor 1 TargetsYue JiangBojan CukicDonald A. AdjerohHeath D. SkinnerJie LinQingxi J. ShenBing-Hua JiangEfficient and effective analysis of the growing genomic databases requires the development of adequate computational tools. We introduce a fast method based on the suffix tree data structure for predicting novel targets of hypoxia-inducible factor 1 (HIF-1) from huge genome databases. The suffix tree data structure has two powerful applications here: one is to extract unknown patterns from multiple strings/sequences in linear time; the other is to search multiple strings/sequences using multiple patterns in linear time. Using 15 known HIF-1 target gene sequences as a training set, we extracted 105 common patterns that all occur in the 15 training genes using suffix trees. Using these 105 common patterns along with known subsequences surrounding HIF-1 binding sites from the literature, the algorithm searches a genome database that contains 2,078,786 DNA sequences. It reported 258 potentially novel HIF-1 targets including 25 known HIF-1 targets. Based on microarray studies from the literature, 17 putative genes were confirmed to be upregulated by HIF-1 or hypoxia inside these 258 genes. We further studied one of the potential targets, COX-2, in the biological lab; and showed that it was a biologically relevant HIF-1 target. These results demonstrate that our methodology is an effective computational approach for identifying novel HIF-1 targets.http://www.la-press.com/an-algorithm-for-identifying-novel-targets-of-transcription-factor-fam-a1340Algorithmtranscription factorHIF-1target identification |
| spellingShingle | Yue Jiang Bojan Cukic Donald A. Adjeroh Heath D. Skinner Jie Lin Qingxi J. Shen Bing-Hua Jiang An Algorithm for Identifying Novel Targets of Transcription Factor Families: Application to Hypoxia-inducible Factor 1 Targets Cancer Informatics Algorithm transcription factor HIF-1 target identification |
| title | An Algorithm for Identifying Novel Targets of Transcription Factor Families: Application to Hypoxia-inducible Factor 1 Targets |
| title_full | An Algorithm for Identifying Novel Targets of Transcription Factor Families: Application to Hypoxia-inducible Factor 1 Targets |
| title_fullStr | An Algorithm for Identifying Novel Targets of Transcription Factor Families: Application to Hypoxia-inducible Factor 1 Targets |
| title_full_unstemmed | An Algorithm for Identifying Novel Targets of Transcription Factor Families: Application to Hypoxia-inducible Factor 1 Targets |
| title_short | An Algorithm for Identifying Novel Targets of Transcription Factor Families: Application to Hypoxia-inducible Factor 1 Targets |
| title_sort | algorithm for identifying novel targets of transcription factor families application to hypoxia inducible factor 1 targets |
| topic | Algorithm transcription factor HIF-1 target identification |
| url | http://www.la-press.com/an-algorithm-for-identifying-novel-targets-of-transcription-factor-fam-a1340 |
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