Rattei, T.* ; Tischler, P.* ; Götz, S.* ; Jehl, M.A.* ; Hoser, J.D.S.* ; Arnold, R.* ; Conesa, A.* ; Mewes, H.-W.
     
    
        
SIMAP - a comprehensive database of pre-calculated protein sequence similarities, domains, annotations and clusters.
    
    
        
    
    
        
        Nucleic Acids Res. 38, 1, D223-D226 (2010)
    
    
    
      
      
	
	    The prediction of protein function as well as the reconstruction of evolutionary genesis employing sequence comparison at large is still the most powerful tool in sequence analysis. Due to the exponential growth of the number of known protein sequences and the subsequent quadratic growth of the similarity matrix, the computation of the Similarity Matrix of Proteins (SIMAP) becomes a computational intensive task. The SIMAP database provides a comprehensive and up-to-date pre-calculation of the protein sequence similarity matrix, sequence-based features and sequence clusters. As of September 2009, SIMAP covers 48 million proteins and more than 23 million non-redundant sequences. Novel features of SIMAP include the expansion of the sequence space by including databases such as ENSEMBL as well as the integration of metagenomes based on their consistent processing and annotation. Furthermore, protein function predictions by Blast2GO are pre-calculated for all sequences in SIMAP and the data access and query functions have been improved. SIMAP assists biologists to query the up-to-date sequence space systematically and facilitates large-scale downstream projects in computational biology. Access to SIMAP is freely provided through the web portal for individuals (http://mips.gsf.de/simap/) and for programmatic access through DAS (http://webclu.bio.wzw.tum.de/das/) and Web-Service (http://mips.gsf.de/webservices/services/SimapService2.0?wsdl).
	
	
	    
	
       
      
	
	    
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        Publication type
        Article: Journal article
    
 
    
        Document type
        Scientific Article
    
 
    
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        Keywords
        OCEAN SAMPLING EXPEDITION; BLAST2GO; GENOMICS; MATRIX
    
 
    
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        Language
        english
    
 
    
        Publication Year
        2010
    
 
    
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        HGF-reported in Year
        2010
    
 
    
    
        ISSN (print) / ISBN
        0305-1048
    
 
    
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        1362-4962
    
 
    
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	    Volume: 38,  
	    Issue: Database Issue,  
	    Pages: D223-D226,  
	    Article Number: ,  
	    Supplement: 1 
	
    
 
    
        
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            Oxford University Press
        
 
        
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        Reviewing status
        Peer reviewed
    
 
     
    
        POF-Topic(s)
        30505 - New Technologies for Biomedical Discoveries
    
 
    
        Research field(s)
        Enabling and Novel Technologies
    
 
    
        PSP Element(s)
        G-503700-001
    
 
    
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        Erfassungsdatum
        2010-03-19