Change search
ReferencesLink to record
Permanent link

Direct link
Prediction of transcription factor binding to DNA using rule induction methods
(Motion Vision)
2006 (English)In: Journal of Integrative Bioinformatics - JIB, ISSN 1613-4516, Vol. 3, no 2, 42- p.Article in journal (Refereed) Published
Abstract [en]

In this study, we seek to develop a predictive model for finding the strength of bindingbetween a particular transcription factor (TF) variant and a particular DNA target variant.The DNA binding paired domains of the Pax transcription factors, which are our mainfocus, show seemingly fuzzy and degenerate binding to various DNA targets, and paireddomain-DNA binding is not a problem well suited for previously proposed algorithms.Here, we introduce a simple way to use rule induction for predicting the strength of TFDNAbinding. We have created a dataset consisting of 597 example cases for paireddomain-DNA binding by collecting information about all published and quantifiedinteractions between TF and DNA sequence variants. Application of the rule inductionbased method on this dataset yields a high, although far from ideal accuracy of 69.7%(based on cross-validation), but perhaps more importantly, several useful rules forpredicting the binding strength have been found. Although the primary motivation forintroducing the rule induction based methods is the lack of efficient algorithms for paireddomain-DNA binding prediction, we also show that the method can be applied with somesuccess to a more well-studied TF-DNA binding prediction task involving the earlygrowth response (EGR) TF family.

Place, publisher, year, edition, pages
2006. Vol. 3, no 2, 42- p.
National Category
Bioinformatics (Computational Biology)
URN: urn:nbn:se:uu:diva-183602DOI: 10.2390/biecoll-jib-2006-42OAI: diva2:563437
3rd Integrative Bioinformatics Workshop, September 4-6th, 2006, Harpenden, United Kingdom
Available from: 2012-11-05 Created: 2012-10-30 Last updated: 2012-11-05Bibliographically approved

Open Access in DiVA

fulltext(352 kB)100 downloads
File information
File name FULLTEXT02.pdfFile size 352 kBChecksum SHA-512
Type fulltextMimetype application/pdf

Other links

Publisher's full text

Search in DiVA

By author/editor
Nordström, Karin
Bioinformatics (Computational Biology)

Search outside of DiVA

GoogleGoogle Scholar
Total: 100 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 285 hits
ReferencesLink to record
Permanent link

Direct link