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Applications for protein sequence–function evolution data: mRNA/protein expression analysis and coding SNP scoring tools

The vast amount of protein sequence data now available, together with accumulating experimental knowledge of protein function, enables modeling of protein sequence and function evolution. The PANTHER database was designed to model evolutionary sequence–function relationships on a large scale. There...

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Autores principales: Thomas, Paul D., Kejariwal, Anish, Guo, Nan, Mi, Huaiyu, Campbell, Michael J., Muruganujan, Anushya, Lazareva-Ulitsky, Betty
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1538848/
https://www.ncbi.nlm.nih.gov/pubmed/16912992
http://dx.doi.org/10.1093/nar/gkl229
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author Thomas, Paul D.
Kejariwal, Anish
Guo, Nan
Mi, Huaiyu
Campbell, Michael J.
Muruganujan, Anushya
Lazareva-Ulitsky, Betty
author_facet Thomas, Paul D.
Kejariwal, Anish
Guo, Nan
Mi, Huaiyu
Campbell, Michael J.
Muruganujan, Anushya
Lazareva-Ulitsky, Betty
author_sort Thomas, Paul D.
collection PubMed
description The vast amount of protein sequence data now available, together with accumulating experimental knowledge of protein function, enables modeling of protein sequence and function evolution. The PANTHER database was designed to model evolutionary sequence–function relationships on a large scale. There are a number of applications for these data, and we have implemented web services that address three of them. The first is a protein classification service. Proteins can be classified, using only their amino acid sequences, to evolutionary groups at both the family and subfamily levels. Specific subfamilies, and often families, are further classified when possible according to their functions, including molecular function and the biological processes and pathways they participate in. The second application, then, is an expression data analysis service, where functional classification information can help find biological patterns in the data obtained from genome-wide experiments. The third application is a coding single-nucleotide polymorphism scoring service. In this case, information about evolutionarily related proteins is used to assess the likelihood of a deleterious effect on protein function arising from a single substitution at a specific amino acid position in the protein. All three web services are available at .
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spelling pubmed-15388482006-08-18 Applications for protein sequence–function evolution data: mRNA/protein expression analysis and coding SNP scoring tools Thomas, Paul D. Kejariwal, Anish Guo, Nan Mi, Huaiyu Campbell, Michael J. Muruganujan, Anushya Lazareva-Ulitsky, Betty Nucleic Acids Res Article The vast amount of protein sequence data now available, together with accumulating experimental knowledge of protein function, enables modeling of protein sequence and function evolution. The PANTHER database was designed to model evolutionary sequence–function relationships on a large scale. There are a number of applications for these data, and we have implemented web services that address three of them. The first is a protein classification service. Proteins can be classified, using only their amino acid sequences, to evolutionary groups at both the family and subfamily levels. Specific subfamilies, and often families, are further classified when possible according to their functions, including molecular function and the biological processes and pathways they participate in. The second application, then, is an expression data analysis service, where functional classification information can help find biological patterns in the data obtained from genome-wide experiments. The third application is a coding single-nucleotide polymorphism scoring service. In this case, information about evolutionarily related proteins is used to assess the likelihood of a deleterious effect on protein function arising from a single substitution at a specific amino acid position in the protein. All three web services are available at . Oxford University Press 2006-07-01 2006-07-14 /pmc/articles/PMC1538848/ /pubmed/16912992 http://dx.doi.org/10.1093/nar/gkl229 Text en © The Author 2006. Published by Oxford University Press. All rights reserved
spellingShingle Article
Thomas, Paul D.
Kejariwal, Anish
Guo, Nan
Mi, Huaiyu
Campbell, Michael J.
Muruganujan, Anushya
Lazareva-Ulitsky, Betty
Applications for protein sequence–function evolution data: mRNA/protein expression analysis and coding SNP scoring tools
title Applications for protein sequence–function evolution data: mRNA/protein expression analysis and coding SNP scoring tools
title_full Applications for protein sequence–function evolution data: mRNA/protein expression analysis and coding SNP scoring tools
title_fullStr Applications for protein sequence–function evolution data: mRNA/protein expression analysis and coding SNP scoring tools
title_full_unstemmed Applications for protein sequence–function evolution data: mRNA/protein expression analysis and coding SNP scoring tools
title_short Applications for protein sequence–function evolution data: mRNA/protein expression analysis and coding SNP scoring tools
title_sort applications for protein sequence–function evolution data: mrna/protein expression analysis and coding snp scoring tools
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1538848/
https://www.ncbi.nlm.nih.gov/pubmed/16912992
http://dx.doi.org/10.1093/nar/gkl229
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