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Resource:EVEREST - EVolutionary Ensembles of REcurrent SegmenTs

Name: Resource:EVEREST - EVolutionary Ensembles of REcurrent SegmenTs
Description: EVEREST is an automatic process of identifying and classifying of protein domains. Users can search for specific proteins using Protein ID or name, browse through protein families, and upload/download protein sequence data. EVEREST combines methodologies from the fields of finite metric spaces, machine learning and statistical modeling and achieves state of the art results.
The process begins by constructing a database of protein segments that emerge in an all vs. all pairwise sequence comparison. It then proceeds to cluster these segments into putative domain families, choosing the best putative families using machine learning techniques, and creating a statistical model for each of the chosen families. This procedure is then iterated: The aforementioned statistical models are used to scan all protein sequences, to recreate a segment database and to cluster them again. Performance was evaluated by comparing with Pfam and SCOP.
Abbreviation: EVEREST
Parent Organization: Hebrew University of Jerusalem; Jerusalem; Israel
Resource Type(s): Database
Resource: Resource
URL: http://www.everest.cs.huji.ac.il
*Id: nif-0000-02822
Keywords: protein domain, protein domain classification, protein domain identification
Link to OWL / RDF: Download this content as OWL/RDF

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Facts about Resource:EVEREST - EVolutionary Ensembles of REcurrent SegmenTsRDF feed
AbbrevEVEREST  +
CurationStatusuncurated  +
DefiningCitationhttp://www.everest.cs.huji.ac.il  +
DefinitionEVEREST is an automatic process of identif EVEREST is an automatic process of identifying and classifying of protein domains. Users can search for specific proteins using Protein ID or name, browse through protein families, and upload/download protein sequence data. EVEREST combines methodologies from the fields of finite metric spaces, machine learning and statistical modeling and achieves state of the art results.
The process begins by constructing a database of protein segments that emerge in an all vs. all pairwise sequence comparison. It then proceeds to cluster these segments into putative domain families, choosing the best putative families using machine learning techniques, and creating a statistical model for each of the chosen families. This procedure is then iterated: The aforementioned statistical models are used to scan all protein sequences, to recreate a segment database and to cluster them again. Performance was evaluated by comparing with Pfam and SCOP.
ted by comparing with Pfam and SCOP.
Has default formThis property is a special property in this wiki.Resource  +
Has roleDatabase  +
Idnif-0000-02822  +
Is part ofHebrew University of Jerusalem; Jerusalem; Israel  +
KeywordsProtein domain  +, Protein domain classification  +, and Protein domain identification  +
LabelResource:EVEREST - EVolutionary Ensembles of REcurrent SegmenTs  +
ModifiedDate20 June 2013  +
Page has default formThis property is a special property in this wiki.Resource  +
SuperCategoryResource  +