Biological Databases

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Biological Databases

• By Lim Yun PingE mail yunping_at_chitre.net
• National University of Singapore

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Overview

• Introduction
• What is a database
• What type of databases can we access
• What roles do they play
• What type of information can we get from them
• How do we access these information

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What is a database ?

• Convenient method of vast amount of information
• Allows for proper storing, searching retrieving
  of data.
• Before analyzing them we need to assemble them
  into central, shareable resources

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Why databases ?

• Means to handle and share large volumes of
  biological data
• Support large-scale analysis efforts
• Make data access easy and updated
• Link knowledge obtained from various fields of
  biology and medicine

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Different Database Types

• depends on the nature of information stored
• (sequences, 2D gel or 3D structure images)
• manner of storage (flat files, tables in a
  relational database, etc)
• In this course we are concerned more about the
  different types of databases rather than the
  particular storage

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Features

• Most of the databases have a web-interface to
  search for data
• Common mode to search is by Keywords
• User can choose to view the data or save to your
  computer
• Cross-references help to navigate from one
  database to another easily

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Biological Databases
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Types Of Biological Databases Accessible

• There are many different types of database but
  for routine sequence analysis, the following are
  initially the most important
• Primary databases
• Secondary databases
• Composite databases

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Primary databases

• Contain sequence data such as nucleic acid or
  protein
• Example of primary databases include

• Protein Databases
• SWISS-PROT
• TREMBL
• PIR

• Nucleic Acid Databases
• EMBL
• Genbank
• DDBJ

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Secondary databases

• Or sometimes known as pattern databases
• Contain results from the analysis of the
  sequences in the primary databases
• Example of secondary databases include

• PROSITE
• Pfam
• BLOCKS
• PRINTS

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Composite databases

• Combine different sources of primary databases.
• Make querying and searching efficient and without
  the need to go to each of the primary databases.
• Example of composite databases include

• NRDB Non-Redundant DataBase
• OWL

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NCBI http//www.ncbi.nlm.nih.gov/ NCBI, at the
NIH campus, USA
EMBL http//www.embl-heidelberg.de/ European
Molecular Biology Laboratory, UK
DDBJ
DDBJ http//www.ddbj.nig.ac.jpDNA Databank of
Japan
Nucleic acid Databases
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The International Sequence Database Collaboration
GenBank
EMBL
DDBJ
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The International Sequence Database Collaboration

• These three databases have collaborated since
  1982. Each database collects and processes new
  sequence data and relevant biological information
  from scientists in their region e.g. EMBL
  collects from Europe, GenBank from the USA.
• These databases automatically update each other
  with the new sequences collected from each
  region, every 24 hours. The result is that they
  contain exactly the same information, except for
  any sequences that have been added in the last 24
  hours.
• This is an important consideration in your choice
  of database. If you need accurate and up to date
  information, you must search an up to date
  database.

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Amount Of Data Grows Rapidly

• As of June 2003, there were 32528249295 bases
• in 25592865 sequence

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How to access them

• Main Sites
• NCBI http//www.ncbi.nlm.nih.gov/
• EMBL http//www.embl-heidelberg.de/
• DDBJ http//www.ddbj.nig.ac.jp

• full release every two months
• incremental and cumulative updates daily
• available only through internet
  ftp//ftp.ncbi.nih.gov/genbank/
• 66.3 Gigabytes of data

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The Internet and WWW
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NCBI http//www.ncbi.nlm.nih.gov/ NCBI, a
division of NLM at the NIH campus, USA
EXPASY http//www.expasy.org Swiss Institute
of Bioinformatics
Kyoto Encyclopedia of Genes and
Genomes http//www.genome.ad.jp/kegg/kegg2.html
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• National Centre for Biotechnology Information
• Established in 1988 as a national resource for
  molecular biology information, NCBI creates
  public databases, conducts research in
  computational biology, develops software tools
  for analyzing genome data, and disseminates
  biomedical information all for the better
  understanding of molecular processes affecting
  human health and disease.http//www.ncbi.nlm.nih
  .gov/

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Entrez

• Entrez is a search and retrieval system that
  integrates information from databases at NCBI.

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BNIP
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Brief description of the sequence.
Accession Number Unique identifier
Source Organisms common name
Formal scientific name
Contains information on the publications such as
the authors, and topic titles of the journals
that discuss the data reported in the record.
Contains the contact information of the submitter

• Contains the information about the genes, gene
  products and regions of biological significance
  reported in the sequence
• length of sequence
• scientific name of the source organism
• Taxon ID number, Map location

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Coding sequence (region of the nucleotides that
correspond to the sequence of amino acid). This
is also the location that contains the start and
stop codon.
Region of biological interest
The amino acid translation corresponding to the
nucleotide coding sequence
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How to understand the output
Unique Identifiers Each entry in a database
must have a unique identifier EMBL Identifier
(ID) GENBANK Accession Number (AC) Other
information is stored along with the
sequence. Each piece of information is written on
it's own line, with a code defining the line. For
example, DE, description OS, organism species
AC, accession number. Relevant biological
information is usually described in the feature
table (FT).
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Genbank Flat File Format

• Refer to Summary Description of the Genbank
  Flat File Format
• Or
• http//www.ncbi.nlm.nih.gov/Sitemap/samplerecord.h
  tml

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ExPASy

• Expert Protein Analysis System proteomics server
  of the Swiss Institute of Bioinformatics (SIB)
• dedicated to the analysis of protein sequences
  and structures http//www.expasy.org/

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Databases on the Expasy server

• SWISS-PROT and TrEMBL - Protein knowledgebase
• PROSITE - Protein families and domains
• SWISS-2DPAGE - Two-dimensional polyacrylamide gel
  electrophoresis
• ENZYME - Enzyme nomenclature
• SWISS-3DIMAGE - 3D images of proteins and other
  biological macromolecules
• SWISS-MODEL Repository - Automatically generated
  protein models

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SWISS-PROT

• A curated protein sequence database which
  strives to provide a high level of annotations
  (such as the description of the function of a
  protein, its domains structure,
  post-translational modifications, variants,
  etc.), a minimal level of redundancy and high
  level of integration with other
  databaseshttp//tw.expasy.org/sprot/

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TrEMBL

• Computer-annotated supplement to SWISS-PROT

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ENZYME

• Enzyme nomenclature database
• http//tw.expasy.org/enzyme/

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ENZYME Database

• A repository of information relative to the
  nomenclature of enzymes
• Describes each type of characterized enzyme for
  which an EC (Enzyme Commission) number has been
  provided

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Access to ENZYME

• by EC number
• by enzyme class
• by description (official name) or alternative
  name(s)
• by chemical compound
• by cofactor

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K E G G

• Kyoto Encyclopedia of Genes and Genomes
• http//www.genome.ad.jp/kegg/kegg2.html

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A structured database containing information
about metabolic pathways in many organisms.
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KEGG

• Part of the GenomeNet database system
• Linked to all accessible databases by search
  engines LIGAND BRITE

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Link to other pathways
Enzyme
Compound
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Summary

• Biological databases represent an invaluable
  resource in support of biological research.
• We can learn much about a particular molecule by
  searching databases and using available analysis
  tools.
• A large number of databases are available for
  that task. Some databases are very general while
  some are very specialised. For best results we
  often need to access multiple databases.

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• Common database search methods include keyword
  matching, sequence similarity, motif searching,
  and class searching
• The problems with using biological databases
  include incomplete information, data spread over
  multiple databases, redundant information,
  various errors, sometimes incorrect links, and
  constant change.

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• Database standards, nomenclature, and naming
  conventions are not clearly defined for many
  aspects of biological information. This makes
  information extraction more difficult
• Retrieval systems help extract rich information
  from multiple databases. Examples include Entrez
  and SRS.
• Formulating queries is a serious issue in
  biological databases. Often the quality of
  results depends on the quality of the queries.
• Access to biological databases is so important
  that today virtually every molecular biological
  project starts and ends with querying biological
  databases.

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The End