Promoter sequence of fibroin gene assigned by in vitro transcription
Sequence Analysis In Promoter Regions
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BioMed Central Page 1 of 1 (page number not for citation purposes) BMC Bioinformatics Open Access Poster presentation Sequence Analysis In Promoter Regions Jeremy Austin* Address: Cranfield University, Department of Analytical Science and Informatics (DASI). Cranfield University, Barton Rd, Silsoe, Bedfordshire, MK45 4DT, UK. Email: Jeremy Austin* - [email protected] * Corresponding author Gene Expression and RegulationAlgorithm Development A gene's promoter region is a prominent factor in deter- mining that gene's expression networks and cycle. The sig- nificant elements which determine the promoter's effect are generally discovered through laboratory methods. This project's aim is to develop high throughput sequence analysis methods for identifying the important promoter features and classifying promoters according to the occur- rence of these features. Saccharomyces Cervisiae, as one of the first fully sequenced organisms which also has publicly available expression data, was chosen as a case study for this work. Motifs of over-represented sequence segments were sought using a bespoke implementation of the Smith- Waterman algorithm running on the Cambridge-Cran- field high performance computer facility. The algorithm identifies all pairs of sequence segments whose similarity surpasses a given threshold. The found segments are then grouped by similarity, and those groups with a many members are the motifs which are over-represented. The motifs identified using this approach are compared to known transcription factor binding sites from the S. Cer- visiae Promoter Database. Most of the motifs produced are expected to correspond with binding sites; others could be new discoveries. Having validated the method on S. Cervisiae, it can then be used with some confidence to analyse promoters from other species, whose character- istics are less well understood. from BioSysBio: Bioinformatics and Systems Biology Conference Edinburgh, UK, 14–15 July 2005 Published: 21 September 2005 BMC Bioinformatics 2005, 6(Suppl 3):P2 <supplement> <title><p>BioSysBio: Bioinformatics and Systems Biology Conference</p></title> <note>Meeting abstracts – A single PDF containing all abstracts in this Supplement is available <a href="http://www.biomedcentral.com/content/files/pdf/1471-2105-6-S3-full.pdf">here</a>.</note> <url>http://www.biomedcentral.com/content/pdf/1471-2105-6-S3-info.pdf</url> </supplement>
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Transcript of Sequence Analysis In Promoter Regions
BioMed Central
Page 1 of 1(page number not for citation purposes)
BMC Bioinformatics
Open AccessPoster presentationSequence Analysis In Promoter RegionsJeremy Austin*
Address: Cranfield University, Department of Analytical Science and Informatics (DASI). Cranfield University, Barton Rd, Silsoe, Bedfordshire, MK45 4DT, UK.
Email: Jeremy Austin* - [email protected]
* Corresponding author
Gene Expression and RegulationAlgorithm DevelopmentA gene's promoter region is a prominent factor in deter-mining that gene's expression networks and cycle. The sig-nificant elements which determine the promoter's effectare generally discovered through laboratory methods.This project's aim is to develop high throughput sequenceanalysis methods for identifying the important promoterfeatures and classifying promoters according to the occur-rence of these features.
Saccharomyces Cervisiae, as one of the first fullysequenced organisms which also has publicly availableexpression data, was chosen as a case study for this work.Motifs of over-represented sequence segments weresought using a bespoke implementation of the Smith-Waterman algorithm running on the Cambridge-Cran-field high performance computer facility. The algorithmidentifies all pairs of sequence segments whose similaritysurpasses a given threshold. The found segments are thengrouped by similarity, and those groups with a manymembers are the motifs which are over-represented.
The motifs identified using this approach are compared toknown transcription factor binding sites from the S. Cer-visiae Promoter Database. Most of the motifs producedare expected to correspond with binding sites; otherscould be new discoveries. Having validated the methodon S. Cervisiae, it can then be used with some confidenceto analyse promoters from other species, whose character-istics are less well understood.
from BioSysBio: Bioinformatics and Systems Biology ConferenceEdinburgh, UK, 14–15 July 2005
Published: 21 September 2005
BMC Bioinformatics 2005, 6(Suppl 3):P2<supplement> <title><p>BioSysBio: Bioinformatics and Systems Biology Conference</p></title> <note>Meeting abstracts – A single PDF containing all abstracts in this Supplement is available <a href="http://www.biomedcentral.com/content/files/pdf/1471-2105-6-S3-full.pdf">here</a>.</note> <url>http://www.biomedcentral.com/content/pdf/1471-2105-6-S3-info.pdf</url> </supplement>
![Chandler Unified School District / Home Page · Web viewTranscription begins when [RNA / RNA polymerase] binds to the gene’s promoter. The promoter region contains the sequence](https://static.fdocuments.us/doc/165x107/6006f3e28ecd7a613e1d7184/chandler-unified-school-district-home-page-web-view-transcription-begins-when.jpg)
