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Bioinformatics
Prof:Rui Alvesralves@cmb.udl.es
973702406Dept Ciencies Mediques Basiques,
1st Floor, Room 1.08Website:http://web.udl.es/usuaris/pg193845/testsite/
Course Website:http://web.udl.es/usuaris/pg193845/Bioinformatics_2009/
Language of the course
• Mine: English
• Slides: English
• Webpage: English
• Yours: Whichever you choose as long as I understand it. ALWAYS ASK WHEN YOU DON’T UNDERSTAND SOMETHING!!
Web Page of the course
http://web.udl.es/usuaris/pg193845/Bioinformatics_2009/
• There, you will find all the information about your tasks, links to bioinformatics resources, and the lecture
Goals of this course
• Give you an integrated view of how to use computers and informatics to gain a systemic understanding of biological systems at the molecular level.
• Integrate bioinformatics, mathematical modelling and other areas of computational biology to save lab work and address problems that can not yet be solved at the lab.
Course Plan
• First part of the course (2 weeks): Broad introduction to bioinformatics and computational biology in molecular biology.
• Second part of the course: Problems for you to solve in group at home, + in-depth lectures about the different subjects you need to solve the problems.
Evaluation Plan • 5 tasks in groups of four. At the end of each task you
deliver a paper as a group. (overall, all tasks will account for 50% of final grade).
• Final paper presenting the whole story together (20%).• Individual discussion of the final paper with me (20%).• Class participation (10%).• CAUTION: YOU NEED TO HAVE AT LEAST 5/10 IN
EACH TASK, IN THE FINAL PAPER AND IN THE DISCUSSION.
Index
• Why bioinformatics?
• Ontologies & Classification schemes
• Databases and servers
Why Bioinformatics?
Prof:Rui Alvesralves@cmb.udl.es
973702406Dept Ciencies Mediques Basiques,
1st Floor, Room 1.08Website:http://web.udl.es/usuaris/pg193845/testsite/
What obvious problems do large scale sets create?
•Imagine the 6 500 000 000 human beings born within the last 130 years and still alive.•By and large a majority of them has had and education.•What problems need solving to ensure that education?
Knowledge1 – Organize Knowledge2 – Organize its transmission
First problem: organizing knowledge
•We do not need to know all there is to know in order to be productive in society•Furthermore we can not learn everything at the same time.•Problem: How to organize knowledge into bite-sized packages that can be consecutively parceled out, and from which one can build upon?
Organizing knowledge
Communication(Read, write, count)
Humanities
Sciences
…
Second problem: organizing the transmission of knowledge
•The school system is a way in which the most people can be trained with the least societal effort
Not effective
School and Books are the servers and databases of educating people
Users
Database
Server
New Server:
You
Hey, it’s raining!!! Why don’t we try and figure out how all the little molecular pieces in a cell work
together?!?!?!
Understanding biological systems
We were WRONG!!!!!
I need more data!!! How do I plan what to
do now?
The “omics” revolution in molecular biology
•Over many decades, a huge amount of biological data has accumulated.
•Unlike the “KNOWLEDGE” we discussed before, this data is not well organized and the connections between the different parcels of data are obscure.
•The omics revolution has compounded this problem 1000 fold because data now accumulates faster than ever.
What is the “omics” revolution in molecular biology?
•The omics revolution is a period of about ten years in which
several different technologies that can be applied to study
the complement molecular landscape of cells!!!
•Genomics
•Proteomics
•Metabolomics
•Et caeteromics
The “omics” revolution in molecular biology
•(We!!) Biologists want the data to make sense and they want it now!!!
Understanding biological systems
I need more data!!! Why
don’t they give it to me
Comparison between the two problems
People organized the Knowledge transmission system and its connections over milenia of trial and error.
It is impossible for people to organize the biological knowledge brought about by omics in the 10 years that have passed since the beginning of the omics era.
Why?
•Data is not well classified.
•Data is not well connected.
•Data is not well understood.
•Not enough people to do it in a short amount of time.
New types of servers and databases are required for very fast organization and
data mining
Users
Database
Server
BIOINFORMATICS!!
• Development and application of computational/informatic tools to the solution of biological problems
• The Standard of internet Bioinformatics:
What is Bioinformatics?
L A M PINUX
PACHE
Y
SQL
ERL
HPYTHON
Operating system
Internet server Database
server
Programing
language(s)
• JAVA facilitates that the servers launch a smaller number of processes by using the client’s machines for calculus and allowing for a larger number of simultaneous connections.
• TOMCAT “talks” very well with JAVA.
The standards are changing
L T M JINUX
OMCAT
Y
SQL
AVA
Operating system
Internet server Database
server
Programing
language(s)
What does a computer need to be effective?
•Well classified data•Ontologies, Classification schemes
•Well organized data•Databases, servers
•Good users
Index
• Why bioinformatics?
• Ontologies & Classification schemes
• Databases and servers
Ontologies and classification schemes for data
Prof:Rui Alvesralves@cmb.udl.es
973702406Dept Ciencies Mediques Basiques,
1st Floor, Room 1.08Website:http://web.udl.es/usuaris/pg193845/testsite/
Biological Classification Schemes
• What is an Ontology (in the Biological sense)?
A set of definitions of controlled vocabularies with hierarchical relationships to one another, that can easily be dealt with by computers
What are Bio-Ontologies?
Biological Ontologies (Bio-ontologies) can be defined as a complex
hierarchical structure in which biological concepts are
described by their meanings (definitions) and relationships to
each other.
There are many Bio-Ontologies available and in use by databases.
The Plant Ontology, along with other ontologies such as the
Gene Ontology, are included in the open source Open
Biological Ontologies project at Sourceforge.
http://obofoundry.org/
The Gene Ontology
The most well-known example of a bio-ontology is the Gene Ontology
(GO; http://www.geneontology.org) which describes three
biological domains: cellular component (where the gene product
locates), molecular function (what the gene product does) and
biological process (the cellular, developmental or physiological
events the gene product is involved in).
GO are used to describe gene products. Because these descriptions are
independent of species-specific nomenclature and uniformly
applied, it is possible to make meaningful and efficient
comparisons of genes across diverse taxa.
Three “Super Categories of GO
• Molecular Function (what)– Tasks performed at the molecular level
• Biological Process (why)– How it pertains to the organism
• Cellular Component (where)– Its location
Example
• Gene Name: BRCA1
• Molecular Function: protein binding
• Biological Process: DNA Replication and Chromosome Cycle
• Cellular Component: nucleus
Structure of GO
• How to define the relationship between concepts?• Example: How to relate the terms: “cell” “nucleus”
“membrane”
How is GO Annotated?
• Manual– Humans sifting through primary literature
• Electronic– Assign GO Terms using already existing
information in databases.
Evidence Code for GO Annotation
IEA Inferred from Electronic Annotation
ISS Inferred from Sequence Similarity
IEP Inferred from Expression Pattern
IMP Inferred from Mutant Phenotype
IGI Inferred from Genetic Interaction
IPI Inferred from Physical Interaction
IDA Inferred from Direct Assay
RCA Inferred from Reviewed Computational Analysis
TAS Traceable Author Statement
NAS Non-traceable Author Statement
IC Inferred by Curator
ND No biological Data available
Detailed info available from:
http://www.geneontology.org/doc/GO.evidence.html
How to use GO in data analysis
• Simple Queries• Find over-represented GO categories in a list of
genes– Search Biological “Themes”
• Binning– Obtain a broad view of the distribution of major GO
terms in a list of genes.
• Clustering Genes on GO terms– Group together functionally related genes based on
GO terms.
GO Tools
• NetFlix – Get GO Annotation
• AmiGO – Browser and Simple Queries
• GoTermMapper – Binning(Go Slim)
• GeneToolBox – – Finding over-represented GO categories– Clustering based on similar GO terms – Query for Gene with Similar Function.
GO is not very good
• EC numbers
• Protein classification schemes
• TF classification schemes
• Transport proteins classification schemes
• Etc.
The EC number database
The BRENDA database
The TF classification database
The signal transduction classification database
The transport proteins classification database
All these classifications are reminiscente of the Dewey classification system for books!!!! (Remember public libraries?)
A general protein classification database
What does a computer need to be effective?
•Well classified data•Ontologies, Classification schemes
•Well organized data•Databases, servers
Index
• Why bioinformatics?
• Ontologies & Classification schemes
• Databases and servers
Databases & Servers
Prof:Rui Alvesralves@cmb.udl.es
973702406Dept Ciencies Mediques Basiques,
1st Floor, Room 1.08Website:http://web.udl.es/usuaris/pg193845/testsite/
What is a Database?
• A database is a collection of data organized in such a way that it is easy to store in a computer and to mine by appropriate software
• A database is usually organized as a set of tables in which information about an object is stored
• The tables are related to each other in different ways.
What does database technology allow?
•Making information useful
•Avoiding "accidental disorganisation”
•Making information easily accessible and integrated with the rest of our work
S(tructured)Q(uery)L(anguange)
• ANSI (American National Standards Institute) standard computer language for accessing and manipulating database systems.
• SQL statements are used to retrieve and update data in a database.
• Includes:– Data Manipulation Language (DML)– Data Definition Language (DDL)
Web Databases
• Data is accessible through Internet• Have different underlying database models• Example: biological databases
– Molecular data: NCBI, Swissprot, PDB, KEGG, GO
– Protein interaction : DIP , BIND– Organism specific: Mouse , Worm, Yeast– Literature: Pubmed– Disease: OMIM
How to make databases useful
• Attach it to a server
• Let people use to mine for knowledge
An example of WAMP•The bioinformatics class server
An example of WAMP•The bioinformatics class server
An example of WAMP•The bioinformatics class server
An example of WAMP•The bioinformatics class server
Wireless
An example of WAMP•The bioinformatics class server
Wireless
Summary
• Why bioinformatics:– Because there is simply too much data out there
for human being to deal with without computer assistance.
– Because many of the calculations to extract knowledge from the data would take too long without computers.
• How to do bioinformatics:– Organize data well using appropriate
classification systems.– Use databases and server technology.