Verwandte Artikel zu Genome annotation and finding repetitive DNA elements
Inhaltsangabe
Bachelor Thesis from the year 2014 in the subject Computer Science - Bioinformatics, grade: 8.26, Lovely Professional University, Punjab, course: b.tech honors biotechnology, language: English, abstract: As the number of genomes sequenced is increasing at high rate, there is a need of gene prediction method which is quick, reliable, inexpensive. In such conditions, the computations tool will serve as an alternative to wet lab methods. The confidence level of annotation by the tool can be enhanced by preparing exhaustive training data sets. The aim is to develop a tool which will read data from a DNA sequence file in the fasta format and will annotate it. For this purpose Genome Database was used to retrieve the input data. PERL programming has been put to develop this tool for annotation. To increase the confidence level of annotation the data was validated from multiple sources. Perl script was written to find the promoter region, repeats, transcription factor binding site, base periodicity, and nucleotide frequency. The program written was also executed to identify repeats, poly (A) signals, CpG islands, ARS. The tool will annotate the DNA by predicting the gene structure based on the consensus sequences of important regulatory elements. The confidence level of annotation of the predicted gene, non-coding region, ARS, repeats etc. were checked by running test dataset. This test dataset was annotated data as reported by genome database and computational tools. Gene prediction of the non-coding regions as reported by genome database (SGD) were performed by existing tools; the regions identified as non-coding by these tools were then analyzed for presence of repeats. The BLAST was used to annotate on the basis of sequence similarity with the already annotated genes. GeneMark.hmm and FGENESH were used for gene prediction. In order to validate the predicted results, annotations of genome of Saccharomyces cerevisiae from SGD Database, and output of different comput
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Reseña del editor
Bachelor Thesis from the year 2014 in the subject Computer Science - Bioinformatics, grade: 8.26, Lovely Professional University, Punjab, course: b.tech honors biotechnology, language: English, abstract: As the number of genomes sequenced is increasing at high rate, there is a need of gene prediction method which is quick, reliable, inexpensive. In such conditions, the computations tool will serve as an alternative to wet lab methods. The confidence level of annotation by the tool can be enhanced by preparing exhaustive training data sets. The aim is to develop a tool which will read data from a DNA sequence file in the fasta format and will annotate it. For this purpose Genome Database was used to retrieve the input data. PERL programming has been put to develop this tool for annotation. To increase the confidence level of annotation the data was validated from multiple sources. Perl script was written to find the promoter region, repeats, transcription factor binding site, base periodicity, and nucleotide frequency. The program written was also executed to identify repeats, poly (A) signals, CpG islands, ARS. The tool will annotate the DNA by predicting the gene structure based on the consensus sequences of important regulatory elements. The confidence level of annotation of the predicted gene, non-coding region, ARS, repeats etc. were checked by running test dataset. This test dataset was annotated data as reported by genome database and computational tools. Gene prediction of the non-coding regions as reported by genome database (SGD) were performed by existing tools; the regions identified as non-coding by these tools were then analyzed for presence of repeats. The BLAST was used to annotate on the basis of sequence similarity with the already annotated genes. GeneMark.hmm and FGENESH were used for gene prediction. In order to validate the predicted results, annotations of genome of Saccharomyces cerevisiae from SGD Database, and output of different comput
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
Neu kaufen
Diesen Artikel anzeigen
EUR 17,95
Gratis für den Versand innerhalb von/der Deutschland
Versandziele, Kosten & DauerSuchergebnisse für Genome annotation and finding repetitive DNA elements
Beispielbild für diese ISBN
Genome annotation and finding repetitive DNA elements
Anbieter: Buchpark, Trebbin, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Zustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher. Bestandsnummer des Verkäufers 24781274/1
Anzahl: 1 verfügbar
Foto des Verkäufers
Genome annotation and finding repetitive DNA elements
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Bachelor Thesis from the year 2014 in the subject Computer Science - Bioinformatics, grade: 8.26, Lovely Professional University, Punjab, course: b.tech honors biotechnology, language: English, abstract: As the number of genomes sequenced is increasing at high rate, there is a need of gene prediction method which is quick, reliable, inexpensive. In such conditions, the computations tool will serve as an alternative to wet lab methods. The confidence level of annotation by the tool can be enhanced by preparing exhaustive training data sets. The aim is to develop a tool which will read data from a DNA sequence file in the fasta format and will annotate it. For this purpose Genome Database was used to retrieve the input data.PERL programming has been put to develop this tool for annotation. To increase the confidence level of annotation the data was validated from multiple sources. Perl script was written to find the promoter region, repeats, transcription factor binding site, base periodicity, and nucleotide frequency. The program written was also executed to identify repeats, poly (A) signals, CpG islands, ARS. The tool will annotate the DNA by predicting the gene structure based on the consensus sequences of important regulatory elements. The confidence level of annotation of the predicted gene, non-coding region, ARS, repeats etc. were checked by running test dataset. This test dataset was annotated data as reported by genome database and computational tools. Gene prediction of the non-coding regions as reported by genome database (SGD) were performed by existing tools; the regions identified as non-coding by these tools were then analyzed for presence of repeats. The BLAST was used to annotate on the basis of sequence similarity with the already annotated genes.GeneMark.hmm and FGENESH were used for gene prediction. In order to validate the predicted results, annotations of genome of Saccharomyces cerevisiae from SGD Database, and output of different computational tools viz, Emboss-CpGplot, PolyAh, REPFind, Promoter 2.0 Prediction Server were compared with the output of developed tool. The output generated was also used for validation and checking sensitivity of the tool. Such tools reduce the cost and time required for genome annotation and bridge the gap between sequenced and annotated data. The output generated by the developed tool was also used for validation and checking sensitivity of the tool. Such tools reduce the cost and time required for genome annotation and bridge the gap between sequenced and annotated data. Bestandsnummer des Verkäufers 9783656659815
Anzahl: 1 verfügbar
Foto des Verkäufers
Genome annotation and finding repetitive DNA elements
Anbieter: preigu, Osnabrück, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. Genome annotation and finding repetitive DNA elements | Renu Rawat | Taschenbuch | 44 S. | Englisch | 2014 | GRIN Verlag | EAN 9783656659815 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 105266183
Anzahl: 5 verfügbar
Foto des Verkäufers
Genome annotation and finding repetitive DNA elements
Verlag:
GRIN Verlag, GRIN Verlag Jun 2014, 2014
ISBN 10: 3656659818
ISBN 13: 9783656659815
Neu
Taschenbuch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. Neuware -Bachelor Thesis from the year 2014 in the subject Computer Science - Bioinformatics, grade: 8.26, Lovely Professional University, Punjab, course: b.tech honors biotechnology, language: English, abstract: As the number of genomes sequenced is increasing at high rate, there is a need of gene prediction method which is quick, reliable, inexpensive. In such conditions, the computations tool will serve as an alternative to wet lab methods. The confidence level of annotation by the tool can be enhanced by preparing exhaustive training data sets. The aim is to develop a tool which will read data from a DNA sequence file in the fasta format and will annotate it. For this purpose Genome Database was used to retrieve the input data. PERL programming has been put to develop this tool for annotation. To increase the confidence level of annotation the data was validated from multiple sources. Perl script was written to find the promoter region, repeats, transcription factor binding site, base periodicity, and nucleotide frequency. The program written was also executed to identify repeats, poly (A) signals, CpG islands, ARS. The tool will annotate the DNA by predicting the gene structure based on the consensus sequences of important regulatory elements. The confidence level of annotation of the predicted gene, non-coding region, ARS, repeats etc. were checked by running test dataset. This test dataset was annotated data as reported by genome database and computational tools. Gene prediction of the non-coding regions as reported by genome database (SGD) were performed by existing tools; the regions identified as non-coding by these tools were then analyzed for presence of repeats. The BLAST was used to annotate on the basis of sequence similarity with the already annotated genes. GeneMark.hmm and FGENESH were used for gene prediction. In order to validate the predicted results, annotations of genome of Saccharomyces cerevisiae from SGD Database, and output of different computational tools viz, Emboss-CpGplot, PolyAh, REPFind, Promoter 2.0 Prediction Server were compared with the output of developed tool. The output generated was also used for validation and checking sensitivity of the tool. Such tools reduce the cost and time required for genome annotation and bridge the gap between sequenced and annotated data. The output generated by the developed tool was also used for validation and checking sensitivity of the tool. Such tools reduce the cost and time required for genome annotation and bridge the gap between sequenced and annotated data.Books on Demand GmbH, Überseering 33, 22297 Hamburg 44 pp. Englisch. Bestandsnummer des Verkäufers 9783656659815
Anzahl: 2 verfügbar
Foto des Verkäufers
Genome annotation and finding repetitive DNA elements
Print-on-DemandAnbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Bachelor Thesis from the year 2014 in the subject Computer Science - Bioinformatics, grade: 8.26, Lovely Professional University, Punjab, course: b.tech honors biotechnology, language: English, abstract: As the number of genomes sequenced is increasing at high rate, there is a need of gene prediction method which is quick, reliable, inexpensive. In such conditions, the computations tool will serve as an alternative to wet lab methods. The confidence level of annotation by the tool can be enhanced by preparing exhaustive training data sets. The aim is to develop a tool which will read data from a DNA sequence file in the fasta format and will annotate it. For this purpose Genome Database was used to retrieve the input data.PERL programming has been put to develop this tool for annotation. To increase the confidence level of annotation the data was validated from multiple sources. Perl script was written to find the promoter region, repeats, transcription factor binding site, base periodicity, and nucleotide frequency. The program written was also executed to identify repeats, poly (A) signals, CpG islands, ARS. The tool will annotate the DNA by predicting the gene structure based on the consensus sequences of important regulatory elements. The confidence level of annotation of the predicted gene, non-coding region, ARS, repeats etc. were checked by running test dataset. This test dataset was annotated data as reported by genome database and computational tools. Gene prediction of the non-coding regions as reported by genome database (SGD) were performed by existing tools; the regions identified as non-coding by these tools were then analyzed for presence of repeats. The BLAST was used to annotate on the basis of sequence similarity with the already annotated genes.GeneMark.hmm and FGENESH were used for gene prediction. In order to validate the predicted results, annotations of genome of Saccharomyces cerevisiae from SGD Database, and output of different computational tools viz, Emboss-CpGplot, PolyAh, REPFind, Promoter 2.0 Prediction Server were compared with the output of developed tool. The output generated was also used for validation and checking sensitivity of the tool. Such tools reduce the cost and time required for genome annotation and bridge the gap between sequenced and annotated data. The output generated by the developed tool was also used for validation and checking sensitivity of the tool. Such tools reduce the cost and time required for genome annotation and bridge the gap between sequenced and annotated data. 44 pp. Englisch. Bestandsnummer des Verkäufers 9783656659815
Anzahl: 2 verfügbar
Beispielbild für diese ISBN
Genome annotation and finding repetitive DNA elements
Anbieter: California Books, Miami, FL, USA
Verkäuferbewertung 5 von 5 Sternen
Zustand: New. Bestandsnummer des Verkäufers I-9783656659815
Anzahl: Mehr als 20 verfügbar