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Functional annotation of hypothetical proteins – A review
The complete human genome sequences in the public database provide ways to understand the blue print of life. As of June 29, 2006, 27 archaeal, 326 bacterial and 21 eukaryotes is complete genomes are available and the sequencing for 316 bacterial, 24 archaeal, 126 eukaryotic genomes are in progress....
Autores principales: | , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Biomedical Informatics Publishing Group
2006
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1891709/ https://www.ncbi.nlm.nih.gov/pubmed/17597916 |
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author | Sivashankari, Selvarajan Shanmughavel, Piramanayagam |
author_facet | Sivashankari, Selvarajan Shanmughavel, Piramanayagam |
author_sort | Sivashankari, Selvarajan |
collection | PubMed |
description | The complete human genome sequences in the public database provide ways to understand the blue print of life. As of June 29, 2006, 27 archaeal, 326 bacterial and 21 eukaryotes is complete genomes are available and the sequencing for 316 bacterial, 24 archaeal, 126 eukaryotic genomes are in progress. The traditional biochemical/molecular experiments can assign accurate functions for genes in these genomes. However, the process is time-consuming and costly. Despite several efforts, only 50-60 % of genes have been annotated in most completely sequenced genomes. Automated genome sequence analysis and annotation may provide ways to understand genomes. Thus, determination of protein function is one of the challenging problems of the post-genome era. This demands bioinformatics to predict functions of un-annotated protein sequences by developing efficient tools. Here, we discuss some of the recent and popular approaches developed in Bioinformatics to predict functions for hypothetical proteins. |
format | Text |
id | pubmed-1891709 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2006 |
publisher | Biomedical Informatics Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-18917092007-06-27 Functional annotation of hypothetical proteins – A review Sivashankari, Selvarajan Shanmughavel, Piramanayagam Bioinformation Hypothesis The complete human genome sequences in the public database provide ways to understand the blue print of life. As of June 29, 2006, 27 archaeal, 326 bacterial and 21 eukaryotes is complete genomes are available and the sequencing for 316 bacterial, 24 archaeal, 126 eukaryotic genomes are in progress. The traditional biochemical/molecular experiments can assign accurate functions for genes in these genomes. However, the process is time-consuming and costly. Despite several efforts, only 50-60 % of genes have been annotated in most completely sequenced genomes. Automated genome sequence analysis and annotation may provide ways to understand genomes. Thus, determination of protein function is one of the challenging problems of the post-genome era. This demands bioinformatics to predict functions of un-annotated protein sequences by developing efficient tools. Here, we discuss some of the recent and popular approaches developed in Bioinformatics to predict functions for hypothetical proteins. Biomedical Informatics Publishing Group 2006-12-29 /pmc/articles/PMC1891709/ /pubmed/17597916 Text en © 2005 Biomedical Informatics Publishing Group This is an open-access article, which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original author and source are credited. |
spellingShingle | Hypothesis Sivashankari, Selvarajan Shanmughavel, Piramanayagam Functional annotation of hypothetical proteins – A review |
title | Functional annotation of hypothetical proteins – A review |
title_full | Functional annotation of hypothetical proteins – A review |
title_fullStr | Functional annotation of hypothetical proteins – A review |
title_full_unstemmed | Functional annotation of hypothetical proteins – A review |
title_short | Functional annotation of hypothetical proteins – A review |
title_sort | functional annotation of hypothetical proteins – a review |
topic | Hypothesis |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1891709/ https://www.ncbi.nlm.nih.gov/pubmed/17597916 |
work_keys_str_mv | AT sivashankariselvarajan functionalannotationofhypotheticalproteinsareview AT shanmughavelpiramanayagam functionalannotationofhypotheticalproteinsareview |