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Database Modeling in Bioinformatics

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Title: Database Modeling in Bioinformatics Author: Beate Marx Last modified by: mulder Created Date: 9/23/1999 3:45:52 PM Document presentation format – PowerPoint PPT presentation

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Title: Database Modeling in Bioinformatics


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The Proteome Analysis Database http//www.ebi.ac.
uk/proteome/
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The Proteome Analysis Database - aims at
integrating information from a variety of
sources that will together facilitate the
classification of the proteins in complete
proteome sets.
Structural information includes amino acid
composition for each of the proteomes and links
are provided to HSSP, the Homology derived
Secondary Structure of Proteins, and PDB, the
Protein Data Bank, for individual proteins from
each of the proteomes.
Functional classification using Gene Ontology
(GO) is available.
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Complete proteome sets for each organism have
been assembled from SPTR (SWISS-PROT TrEMBL
TrEMBLnew) database to be wholly non-redundant
at the sequence level.
Archaeal, bacterial and the A. thaliana and S.
cerevisiae proteome sets A standard procedure
based on tracking protein identifiers from the
nucleotide sequence database EMBL-Bank is used.
D. melanogaster, C. elegans and H. sapiens
proteome sets There are no unique identifiers in
EMBL-Bank that allow the identification of all
genome-project sequences for these organisms.
Each of these organisms is treated separately as
a special case.
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Proteome sets Where an organism contains more
than 1 genomic component (chromosomes,
organelles, plasmids etc.), the set of proteins
encoded by each are combined, and any redundant
members are removed from the composite set.
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For D. melanogaster proteins, the complete set of
are those predicted from the Celera genomic
sequence. Each entry is tagged on entry into
TrEMBL.
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CHROMOSOME TABLES Map proteins to chromosomes
for yeast and human. The information needed to
make protein-chromosome mappings is distributed
over several databases. Resources are pooled to
make mappings.
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30 biggest clusters
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Gene OntologyTM Consortium produces a dynamic
controlled vocabulary that can be applied to
all eukaryotes.
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The Proteome Analysis Database
Currently integrates data on 44 complete
proteomes eukaryotes 5 organisms archaea
8 organisms bacteria 31 organisms
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InterPro covers 31 to 67 of the proteins from
each of the complete genomes.
Eukaryote
Arabidopsis thaliana 65.5 Caenorhabditis
elegans 64.0 Drosophila melanogaster
67.8 Saccharomyces cerevisiae 61.7 Homo
sapiens 71.8 of the incomplete proteome
(SWISS-PROT and TrEMBL) 59.7 of the
complete proteome (SWISS-PROT, TrEMBL and
Ensembl)
Bacteria
For example Bacillus subtilis
61.9 Xylella fastidiosa
47.5 Mycobacterium tuberculosis
64.7 Rickettsia prowazekii 73.5
Archaea
Halobacterium sp. NRC-1 57.2 Pyrococcus
abyssi 66.2
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CluSTr covers the four complete eukaryotic
genomes and the incomplete human genome data
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Summary
The Proteome Analysis Database provides a broad
view of the proteome data classified according to
signatures describing particular sequence motifs
and sequence similarities and affords the
option of examining various specific details
like structure or functional classification.
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Publication Apweiler R., Biswas M., Fleischmann
W., Kanapin A., Karavidopoulou Y., Kersey P.,
Kriventseva E.V., Mittard V., Mulder N., Phan
I., Zdobnov E. "Proteome Analysis
Database online application of
InterPro and CluSTr for the functional
classification of proteins in whole
genomes." Nucleic Acids Res.
29(1)44-48(2001)
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The SWISS-PROT group at the EBI
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