Dissertation/Thesis
Algorithms and tools for splicing junction donor recognition in genomic DNA sequences
| Τίτλος: | Algorithms and tools for splicing junction donor recognition in genomic DNA sequences |
|---|---|
| Συγγραφείς: | Yin, Maisheng |
| Πηγή: | Theses |
| Στοιχεία εκδότη: | Digital Commons @ NJIT |
| Έτος έκδοσης: | 1997 |
| Συλλογή: | Digital Commons @ New Jersey Institute of Technology (NJIT) |
| Θεματικοί όροι: | Genetic engineering, Nucleotide sequence--Computer programs, DNA, Computer Sciences |
| Περιγραφή: | The consensus sequences at splicing junctions in genomic DNA are required for pre-mRNA breaking and rejoining which must be carried out precisely. Programs currently available for identification or prediction of transcribed sequences from within genomic DNA are far from being powerful enough to elucidate genomic structure completely[4]. In this research, we develop a degenerate pattern match algorithm for 5' splicing site (Donor Site) recognition. Using the Motif models we developed, we can mine out the degenerate pattern information from the consensus splicing junction sequences. Our experimental results show that, this algorithm can correctly recognize 93% of the total donor sites at the right positions in the test DNA group. And more than 91% of the donor sites the algorithm predicted are correct. These precision rates are higher than the best existing donor classification algorithm[25]. This research made a very important progress toward our full gene structure detection algorithm development. |
| Τύπος εγγράφου: | Thesis |
| Περιγραφή αρχείου: | application/pdf |
| Γλώσσα: | unknown |
| Relation: | https://digitalcommons.njit.edu/theses/1051; https://digitalcommons.njit.edu/context/theses/article/2050/viewcontent/njit_etd1997_112.pdf |
| Διαθεσιμότητα: | https://digitalcommons.njit.edu/theses/1051 https://digitalcommons.njit.edu/context/theses/article/2050/viewcontent/njit_etd1997_112.pdf |
| Αριθμός Καταχώρησης: | edsbas.343BBD1B |
| Βάση Δεδομένων: | BASE |
| FullText | Text: Availability: 0 CustomLinks: – Url: https://digitalcommons.njit.edu/theses/1051# Name: EDS - BASE (ns324271) Category: fullText Text: View record from BASE |
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| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Algorithms and tools for splicing junction donor recognition in genomic DNA sequences – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Yin%2C+Maisheng%22">Yin, Maisheng</searchLink> – Name: TitleSource Label: Source Group: Src Data: Theses – Name: Publisher Label: Publisher Information Group: PubInfo Data: Digital Commons @ NJIT – Name: DatePubCY Label: Publication Year Group: Date Data: 1997 – Name: Subset Label: Collection Group: HoldingsInfo Data: Digital Commons @ New Jersey Institute of Technology (NJIT) – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Genetic+engineering%22">Genetic engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Nucleotide+sequence--Computer+programs%22">Nucleotide sequence--Computer programs</searchLink><br /><searchLink fieldCode="DE" term="%22DNA%22">DNA</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Sciences%22">Computer Sciences</searchLink> – Name: Abstract Label: Description Group: Ab Data: The consensus sequences at splicing junctions in genomic DNA are required for pre-mRNA breaking and rejoining which must be carried out precisely. Programs currently available for identification or prediction of transcribed sequences from within genomic DNA are far from being powerful enough to elucidate genomic structure completely[4]. In this research, we develop a degenerate pattern match algorithm for 5' splicing site (Donor Site) recognition. Using the Motif models we developed, we can mine out the degenerate pattern information from the consensus splicing junction sequences. Our experimental results show that, this algorithm can correctly recognize 93% of the total donor sites at the right positions in the test DNA group. And more than 91% of the donor sites the algorithm predicted are correct. These precision rates are higher than the best existing donor classification algorithm[25]. This research made a very important progress toward our full gene structure detection algorithm development. – Name: TypeDocument Label: Document Type Group: TypDoc Data: Thesis – Name: Format Label: File Description Group: SrcInfo Data: application/pdf – Name: Language Label: Language Group: Lang Data: unknown – Name: NoteTitleSource Label: Relation Group: SrcInfo Data: https://digitalcommons.njit.edu/theses/1051; https://digitalcommons.njit.edu/context/theses/article/2050/viewcontent/njit_etd1997_112.pdf – Name: URL Label: Availability Group: URL Data: https://digitalcommons.njit.edu/theses/1051<br />https://digitalcommons.njit.edu/context/theses/article/2050/viewcontent/njit_etd1997_112.pdf – Name: AN Label: Accession Number Group: ID Data: edsbas.343BBD1B |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.343BBD1B |
| RecordInfo | BibRecord: BibEntity: Languages: – Text: unknown Subjects: – SubjectFull: Genetic engineering Type: general – SubjectFull: Nucleotide sequence--Computer programs Type: general – SubjectFull: DNA Type: general – SubjectFull: Computer Sciences Type: general Titles: – TitleFull: Algorithms and tools for splicing junction donor recognition in genomic DNA sequences Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Yin, Maisheng IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 1997 Identifiers: – Type: issn-locals Value: edsbas – Type: issn-locals Value: edsbas.oa Titles: – TitleFull: Theses Type: main |
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