Bioinformatic tools for DNA/protein sequence analysis, functional assignment of genes and protein classification
Abstract. The development of efficient DNA sequencing methods has led to the achievement of the DNA sequence of entire genomes from (to date) 55 prokaryotes, 5 eukaryotic organisms and 10 eukaryotic chromosomes. Thus, an enormous amount of DNA sequence data is available and even more will be forthco...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Rehm, B. [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2001 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer-Verlag 2001 |
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| Übergeordnetes Werk: |
Enthalten in: Applied microbiology and biotechnology - Springer-Verlag, 1984, 57(2001), 5-6 vom: Dez., Seite 579-592 |
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| Übergeordnetes Werk: |
volume:57 ; year:2001 ; number:5-6 ; month:12 ; pages:579-592 |
| Links: |
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| DOI / URN: |
10.1007/s00253-001-0844-0 |
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OLC2050692854 |
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| 520 | |a Abstract. The development of efficient DNA sequencing methods has led to the achievement of the DNA sequence of entire genomes from (to date) 55 prokaryotes, 5 eukaryotic organisms and 10 eukaryotic chromosomes. Thus, an enormous amount of DNA sequence data is available and even more will be forthcoming in the near future. Analysis of this overwhelming amount of data requires bioinformatic tools in order to identify genes that encode functional proteins or RNA. This is an important task, considering that even in the well-studied Escherichia coli more than 30% of the identified open reading frames are hypothetical genes. Future challenges of genome sequence analysis will include the understanding of gene regulation and metabolic pathway reconstruction including DNA chip technology, which holds tremendous potential for biomedicine and the biotechnological production of valuable compounds. The overwhelming volume of information often confuses scientists.This review intends to provide a guide to choosing the most efficient way to analyze a new sequence or to collect information on a gene or protein of interest by applying current publicly available databases and Web services. Recently developed tools that allow functional assignment of genes, mainly based on sequence similarity of the deduced amino acid sequence, using the currently available and increasing biological databases will be discussed. | ||
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10.1007/s00253-001-0844-0 doi (DE-627)OLC2050692854 (DE-He213)s00253-001-0844-0-p DE-627 ger DE-627 rakwb eng 570 VZ 12 ssgn BIODIV DE-30 fid Rehm, B. verfasserin aut Bioinformatic tools for DNA/protein sequence analysis, functional assignment of genes and protein classification 2001 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 2001 Abstract. The development of efficient DNA sequencing methods has led to the achievement of the DNA sequence of entire genomes from (to date) 55 prokaryotes, 5 eukaryotic organisms and 10 eukaryotic chromosomes. Thus, an enormous amount of DNA sequence data is available and even more will be forthcoming in the near future. Analysis of this overwhelming amount of data requires bioinformatic tools in order to identify genes that encode functional proteins or RNA. This is an important task, considering that even in the well-studied Escherichia coli more than 30% of the identified open reading frames are hypothetical genes. Future challenges of genome sequence analysis will include the understanding of gene regulation and metabolic pathway reconstruction including DNA chip technology, which holds tremendous potential for biomedicine and the biotechnological production of valuable compounds. The overwhelming volume of information often confuses scientists.This review intends to provide a guide to choosing the most efficient way to analyze a new sequence or to collect information on a gene or protein of interest by applying current publicly available databases and Web services. Recently developed tools that allow functional assignment of genes, mainly based on sequence similarity of the deduced amino acid sequence, using the currently available and increasing biological databases will be discussed. Deduce Amino Acid Sequence Bioinformatic Tool Biotechnological Production Genome Sequence Analysis Hypothetical Gene Enthalten in Applied microbiology and biotechnology Springer-Verlag, 1984 57(2001), 5-6 vom: Dez., Seite 579-592 (DE-627)129942634 (DE-600)392453-1 (DE-576)015507750 0175-7598 nnns volume:57 year:2001 number:5-6 month:12 pages:579-592 https://doi.org/10.1007/s00253-001-0844-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_11 GBV_ILN_21 GBV_ILN_23 GBV_ILN_31 GBV_ILN_40 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_130 GBV_ILN_147 GBV_ILN_252 GBV_ILN_267 GBV_ILN_2018 GBV_ILN_2360 GBV_ILN_4012 GBV_ILN_4046 GBV_ILN_4082 GBV_ILN_4277 GBV_ILN_4307 GBV_ILN_4310 AR 57 2001 5-6 12 579-592 |
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10.1007/s00253-001-0844-0 doi (DE-627)OLC2050692854 (DE-He213)s00253-001-0844-0-p DE-627 ger DE-627 rakwb eng 570 VZ 12 ssgn BIODIV DE-30 fid Rehm, B. verfasserin aut Bioinformatic tools for DNA/protein sequence analysis, functional assignment of genes and protein classification 2001 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 2001 Abstract. The development of efficient DNA sequencing methods has led to the achievement of the DNA sequence of entire genomes from (to date) 55 prokaryotes, 5 eukaryotic organisms and 10 eukaryotic chromosomes. Thus, an enormous amount of DNA sequence data is available and even more will be forthcoming in the near future. Analysis of this overwhelming amount of data requires bioinformatic tools in order to identify genes that encode functional proteins or RNA. This is an important task, considering that even in the well-studied Escherichia coli more than 30% of the identified open reading frames are hypothetical genes. Future challenges of genome sequence analysis will include the understanding of gene regulation and metabolic pathway reconstruction including DNA chip technology, which holds tremendous potential for biomedicine and the biotechnological production of valuable compounds. The overwhelming volume of information often confuses scientists.This review intends to provide a guide to choosing the most efficient way to analyze a new sequence or to collect information on a gene or protein of interest by applying current publicly available databases and Web services. Recently developed tools that allow functional assignment of genes, mainly based on sequence similarity of the deduced amino acid sequence, using the currently available and increasing biological databases will be discussed. Deduce Amino Acid Sequence Bioinformatic Tool Biotechnological Production Genome Sequence Analysis Hypothetical Gene Enthalten in Applied microbiology and biotechnology Springer-Verlag, 1984 57(2001), 5-6 vom: Dez., Seite 579-592 (DE-627)129942634 (DE-600)392453-1 (DE-576)015507750 0175-7598 nnns volume:57 year:2001 number:5-6 month:12 pages:579-592 https://doi.org/10.1007/s00253-001-0844-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_11 GBV_ILN_21 GBV_ILN_23 GBV_ILN_31 GBV_ILN_40 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_130 GBV_ILN_147 GBV_ILN_252 GBV_ILN_267 GBV_ILN_2018 GBV_ILN_2360 GBV_ILN_4012 GBV_ILN_4046 GBV_ILN_4082 GBV_ILN_4277 GBV_ILN_4307 GBV_ILN_4310 AR 57 2001 5-6 12 579-592 |
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10.1007/s00253-001-0844-0 doi (DE-627)OLC2050692854 (DE-He213)s00253-001-0844-0-p DE-627 ger DE-627 rakwb eng 570 VZ 12 ssgn BIODIV DE-30 fid Rehm, B. verfasserin aut Bioinformatic tools for DNA/protein sequence analysis, functional assignment of genes and protein classification 2001 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 2001 Abstract. The development of efficient DNA sequencing methods has led to the achievement of the DNA sequence of entire genomes from (to date) 55 prokaryotes, 5 eukaryotic organisms and 10 eukaryotic chromosomes. Thus, an enormous amount of DNA sequence data is available and even more will be forthcoming in the near future. Analysis of this overwhelming amount of data requires bioinformatic tools in order to identify genes that encode functional proteins or RNA. This is an important task, considering that even in the well-studied Escherichia coli more than 30% of the identified open reading frames are hypothetical genes. Future challenges of genome sequence analysis will include the understanding of gene regulation and metabolic pathway reconstruction including DNA chip technology, which holds tremendous potential for biomedicine and the biotechnological production of valuable compounds. The overwhelming volume of information often confuses scientists.This review intends to provide a guide to choosing the most efficient way to analyze a new sequence or to collect information on a gene or protein of interest by applying current publicly available databases and Web services. Recently developed tools that allow functional assignment of genes, mainly based on sequence similarity of the deduced amino acid sequence, using the currently available and increasing biological databases will be discussed. Deduce Amino Acid Sequence Bioinformatic Tool Biotechnological Production Genome Sequence Analysis Hypothetical Gene Enthalten in Applied microbiology and biotechnology Springer-Verlag, 1984 57(2001), 5-6 vom: Dez., Seite 579-592 (DE-627)129942634 (DE-600)392453-1 (DE-576)015507750 0175-7598 nnns volume:57 year:2001 number:5-6 month:12 pages:579-592 https://doi.org/10.1007/s00253-001-0844-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_11 GBV_ILN_21 GBV_ILN_23 GBV_ILN_31 GBV_ILN_40 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_130 GBV_ILN_147 GBV_ILN_252 GBV_ILN_267 GBV_ILN_2018 GBV_ILN_2360 GBV_ILN_4012 GBV_ILN_4046 GBV_ILN_4082 GBV_ILN_4277 GBV_ILN_4307 GBV_ILN_4310 AR 57 2001 5-6 12 579-592 |
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Bioinformatic tools for DNA/protein sequence analysis, functional assignment of genes and protein classification |
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Abstract. The development of efficient DNA sequencing methods has led to the achievement of the DNA sequence of entire genomes from (to date) 55 prokaryotes, 5 eukaryotic organisms and 10 eukaryotic chromosomes. Thus, an enormous amount of DNA sequence data is available and even more will be forthcoming in the near future. Analysis of this overwhelming amount of data requires bioinformatic tools in order to identify genes that encode functional proteins or RNA. This is an important task, considering that even in the well-studied Escherichia coli more than 30% of the identified open reading frames are hypothetical genes. Future challenges of genome sequence analysis will include the understanding of gene regulation and metabolic pathway reconstruction including DNA chip technology, which holds tremendous potential for biomedicine and the biotechnological production of valuable compounds. The overwhelming volume of information often confuses scientists.This review intends to provide a guide to choosing the most efficient way to analyze a new sequence or to collect information on a gene or protein of interest by applying current publicly available databases and Web services. Recently developed tools that allow functional assignment of genes, mainly based on sequence similarity of the deduced amino acid sequence, using the currently available and increasing biological databases will be discussed. © Springer-Verlag 2001 |
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Abstract. The development of efficient DNA sequencing methods has led to the achievement of the DNA sequence of entire genomes from (to date) 55 prokaryotes, 5 eukaryotic organisms and 10 eukaryotic chromosomes. Thus, an enormous amount of DNA sequence data is available and even more will be forthcoming in the near future. Analysis of this overwhelming amount of data requires bioinformatic tools in order to identify genes that encode functional proteins or RNA. This is an important task, considering that even in the well-studied Escherichia coli more than 30% of the identified open reading frames are hypothetical genes. Future challenges of genome sequence analysis will include the understanding of gene regulation and metabolic pathway reconstruction including DNA chip technology, which holds tremendous potential for biomedicine and the biotechnological production of valuable compounds. The overwhelming volume of information often confuses scientists.This review intends to provide a guide to choosing the most efficient way to analyze a new sequence or to collect information on a gene or protein of interest by applying current publicly available databases and Web services. Recently developed tools that allow functional assignment of genes, mainly based on sequence similarity of the deduced amino acid sequence, using the currently available and increasing biological databases will be discussed. © Springer-Verlag 2001 |
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Abstract. The development of efficient DNA sequencing methods has led to the achievement of the DNA sequence of entire genomes from (to date) 55 prokaryotes, 5 eukaryotic organisms and 10 eukaryotic chromosomes. Thus, an enormous amount of DNA sequence data is available and even more will be forthcoming in the near future. Analysis of this overwhelming amount of data requires bioinformatic tools in order to identify genes that encode functional proteins or RNA. This is an important task, considering that even in the well-studied Escherichia coli more than 30% of the identified open reading frames are hypothetical genes. Future challenges of genome sequence analysis will include the understanding of gene regulation and metabolic pathway reconstruction including DNA chip technology, which holds tremendous potential for biomedicine and the biotechnological production of valuable compounds. The overwhelming volume of information often confuses scientists.This review intends to provide a guide to choosing the most efficient way to analyze a new sequence or to collect information on a gene or protein of interest by applying current publicly available databases and Web services. Recently developed tools that allow functional assignment of genes, mainly based on sequence similarity of the deduced amino acid sequence, using the currently available and increasing biological databases will be discussed. © Springer-Verlag 2001 |
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