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ProtoNet 6.0: organizing 10 million protein sequences in a compact hierarchical family tree
ProtoNet 6.0 (http://www.protonet.cs.huji.ac.il) is a data structure of protein families that cover the protein sequence space. These families are generated through an unsupervised bottom–up clustering algorithm. This algorithm organizes large sets of proteins in a hierarchical tree that yields high...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3245180/ https://www.ncbi.nlm.nih.gov/pubmed/22121228 http://dx.doi.org/10.1093/nar/gkr1027 |
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author | Rappoport, Nadav Karsenty, Solange Stern, Amos Linial, Nathan Linial, Michal |
author_facet | Rappoport, Nadav Karsenty, Solange Stern, Amos Linial, Nathan Linial, Michal |
author_sort | Rappoport, Nadav |
collection | PubMed |
description | ProtoNet 6.0 (http://www.protonet.cs.huji.ac.il) is a data structure of protein families that cover the protein sequence space. These families are generated through an unsupervised bottom–up clustering algorithm. This algorithm organizes large sets of proteins in a hierarchical tree that yields high-quality protein families. The 2012 ProtoNet (Version 6.0) tree includes over 9 million proteins of which 5.5% come from UniProtKB/SwissProt and the rest from UniProtKB/TrEMBL. The hierarchical tree structure is based on an all-against-all comparison of 2.5 million representatives of UniRef50. Rigorous annotation-based quality tests prune the tree to most informative 162 088 clusters. Every high-quality cluster is assigned a ProtoName that reflects the most significant annotations of its proteins. These annotations are dominated by GO terms, UniProt/Swiss-Prot keywords and InterPro. ProtoNet 6.0 operates in a default mode. When used in the advanced mode, this data structure offers the user a view of the family tree at any desired level of resolution. Systematic comparisons with previous versions of ProtoNet are carried out. They show how our view of protein families evolves, as larger parts of the sequence space become known. ProtoNet 6.0 provides numerous tools to navigate the hierarchy of clusters. |
format | Online Article Text |
id | pubmed-3245180 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-32451802012-01-10 ProtoNet 6.0: organizing 10 million protein sequences in a compact hierarchical family tree Rappoport, Nadav Karsenty, Solange Stern, Amos Linial, Nathan Linial, Michal Nucleic Acids Res Articles ProtoNet 6.0 (http://www.protonet.cs.huji.ac.il) is a data structure of protein families that cover the protein sequence space. These families are generated through an unsupervised bottom–up clustering algorithm. This algorithm organizes large sets of proteins in a hierarchical tree that yields high-quality protein families. The 2012 ProtoNet (Version 6.0) tree includes over 9 million proteins of which 5.5% come from UniProtKB/SwissProt and the rest from UniProtKB/TrEMBL. The hierarchical tree structure is based on an all-against-all comparison of 2.5 million representatives of UniRef50. Rigorous annotation-based quality tests prune the tree to most informative 162 088 clusters. Every high-quality cluster is assigned a ProtoName that reflects the most significant annotations of its proteins. These annotations are dominated by GO terms, UniProt/Swiss-Prot keywords and InterPro. ProtoNet 6.0 operates in a default mode. When used in the advanced mode, this data structure offers the user a view of the family tree at any desired level of resolution. Systematic comparisons with previous versions of ProtoNet are carried out. They show how our view of protein families evolves, as larger parts of the sequence space become known. ProtoNet 6.0 provides numerous tools to navigate the hierarchy of clusters. Oxford University Press 2012-01 2011-11-25 /pmc/articles/PMC3245180/ /pubmed/22121228 http://dx.doi.org/10.1093/nar/gkr1027 Text en © The Author(s) 2011. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Articles Rappoport, Nadav Karsenty, Solange Stern, Amos Linial, Nathan Linial, Michal ProtoNet 6.0: organizing 10 million protein sequences in a compact hierarchical family tree |
title | ProtoNet 6.0: organizing 10 million protein sequences in a compact hierarchical family tree |
title_full | ProtoNet 6.0: organizing 10 million protein sequences in a compact hierarchical family tree |
title_fullStr | ProtoNet 6.0: organizing 10 million protein sequences in a compact hierarchical family tree |
title_full_unstemmed | ProtoNet 6.0: organizing 10 million protein sequences in a compact hierarchical family tree |
title_short | ProtoNet 6.0: organizing 10 million protein sequences in a compact hierarchical family tree |
title_sort | protonet 6.0: organizing 10 million protein sequences in a compact hierarchical family tree |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3245180/ https://www.ncbi.nlm.nih.gov/pubmed/22121228 http://dx.doi.org/10.1093/nar/gkr1027 |
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