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2012-10-22_Proseminar-Bioinformatics_Schönhofer-Dominik_Biological-Databases

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Dominik Schönhofer

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Transcript of 2012-10-22_Proseminar-Bioinformatics_Schönhofer-Dominik_Biological-Databases

Dominik Schönhofer
2012.10.22 Biological Databases What are
Databases? 1.1 What is a Database? - organized collection of information.
- information stored in computer readable form
- In bioinformatics mostly types of SQL or XML in use A "database" is build out of two parts: The Database (DB): The Database Management System (DBMS) - function is to save information efficient
in terms of performance, availability and security.
- has to control all reading an writing access
on the database
- database language for defining, manipulating or
query the database 1.4 A simple example for
using a database to handle biological information: 1.3 Databases in biology or "what makes a database to an biological one?" - the contents Slide 1 Genes and Genomes RNA Database Protein sequences Metabolic pathways 5.1 Database access 5.2 The front end - nowadays a mostly graphical interface
- interacts with the DBMS to access the DB

- allows interaction between user and DB
-> the user can insert, query and view data

- different front ends can access the same DB
- how information will be interpreted depends
on the front end - access for users is mostly possible via an
browser application (front end)
- access to most databases in
molecular biology is free of charge
- often users can only read the data
- it needs extended modification rights if
external users should curate data 6 Links "The utility of a database depends on the quality of its links as well as on its contents"
(Lesk, 2008, S. 157) - internal links, to navigate around the DB
-> also allows to analyze selected data

- external links, to connect to other DB's 7.2 Database interoperability ENTREZ - an example for an meta database - french sec. pers. plur. for "Come in!"
- an integrated search an retrieval system
- a single query and user interface
- searches more than 25 DB's, like
PubMed, GenBank, NCBI, OMIM, ...
- several services like email notifications
or illustration of received data 7.1 Database interoperability Some questions need to appeal multiple
DB's at once. How to deal with that? - several databases can be merged into a
single one
or
- developing methods that allow
dissection and distribution of query's
and recombination of responses http://nar.oxfordjournals.org (lists 1380 DB's in 2012) 8.1 Data mining - knowledge discovery: description or
explanation of regularities in data

- successful forecasting 8.2 Statistical
techniques - Classification algorithms
- Clustering algorithms
-Principal component analysis
-> Hidden Markov Model for
detecting homologous
sequences 8.3 Artificial neural networks e.g. prediction of secondary structure 8.4 Support vector machines - used for classification of
objects
- Large Margin Classifier
- used in supervised machine
learning 2 Databases contents - most DB's created for an
circumscribed subject
- DB's can contain overlapping material
- primary an secondary DB's
-> primary: gathered the data
-> secondary: recombined or
reformatted data from primary DB's 1.2 Organization of DB's two types of DB's in common use: - hierarchical structure (XML):
-> multiple level clustering
-> evolutionary relationships

- relational database (SQL):
-> tables
-> theoretic operators

- flat files 4 Quality control 3 Creation and annotation - data will be supplied by
professionals (e.g. gene sequence)

- also part of an entry can be:
-> Reference information
-> Interpretative information
-> Links errors are difficult to extirpate... - 'get it right the first time'
-> let authors create their entry's!
- removing them when detected
-> let examine entry's by professionals
-> correct errors in the master copy
- if other DB's assimilated errors
-> Knowbots or offer 'health checks' Quality control Creation Contents Access Links Interoperability Thanks for your attention! Slide 2 Slide 3 Slide 5 Slide 6 Slide 7 Slide 8 Slide 9 Slide 10 Slide 11 Slide 12 Slide 13 Slide 14 Slide 15 Slide 16 Slide 17 Slide 18 Slide 19 Slide 16 References - Lesk A (2008) Introduction to Bioinformatics, 3th ed.
Oxford: Oxford University Press
- Zvelebil M et al. (2008) Understanding Bioinformatics.
New York: Garland Science, Taylor & Francis Group, LLC
- Westhead D, Parish J (2002) Bioinformatics.
Guildford: Biddles Ltd
- http://de.wikipedia.org/wiki/Datenbank (18. Oct. 2012)
- http://en.wikipedia.org/wiki/Database (18. Oct. 2012)
- http://de.wikipedia.org/wiki/Relationale_Datenbank (18. Oct. 2012)
- http://de.wikipedia.org/wiki/Front-End (18. Oct. 2012)
- http://en.wikipedia.org/wiki/Entrez (18. Oct. 2012)
- http://de.wikipedia.org/wiki/Data_Mining (18. Oct. 2012)
- http://mips.helmholtz-muenchen.de/cider (18. Oct. 2012)
- http://mips.helmholtz-muenchen.de/HSC (18. Oct. 2012)
- http://dev.mysql.com/doc/refman/5.6/en/ (20. Oct. 2012)
- https://kb.askmonty.org/en/ (20. Oct. 2012) [1] http://en.wikipedia.org/wiki/File:UPlogo1.png (18. Oct. 2012) [2] http://en.wikipedia.org/wiki/File:KEGG_database_logo.gif (18. Oct. 2012)
[3] http://static.ensembl.org/i/e-ensembl.png (18. Oct. 2012) [4] http://www.mirbase.org/images/mirbase-logo-blue-web.png (18. Oct. 2012) mips.helmholtz-muenchen.de/HSC (18. Oct. 2012)
mips.helmholtz-muenchen.de/cider (18. Oct. 2012) mips.helmholtz-muenchen.de/cider (18. Oct. 2012) [1] [2] [3] [4] Slide 4
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