http://creativecommons.org/licenses/by-sa/2.0/

Bioinformatics

Prof:Rui Alvesralves@cmb.udl.es

973702406Dept Ciencies Mediques Basiques,

1st Floor, Room 1.08Website:http://web.udl.es/usuaris/pg193845/testsite/

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/Bioinfo/2010/

• There, you will find all the information about your tasks, links to bioinformatics resources, and the lecture.

• It will be up from tomorrow onwards.

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 (2-3 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%).

• Final exam where a problem will be posed to each of you and you will have to outline how you would solve it (20%).

• My discretion (10%).• CAUTION: YOU NEED TO HAVE AT LEAST 6 IN

EACH TASK, IN THE FINAL PAPER AND IN THE EXAM.

Index

• Why bioinformatics?• Ontologies & Classification

schemes• Databases and servers

Why Bioinformatics?Or

Things to do when it is raining and you want to have an integrated view about biological systems…

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

You’re 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

Understanding biological systems

I need more data!!! Why

don’t they give it to me

The “omics” revolution in molecular biology

• (We!!) Biologists want the data to make sense and they (we) want it now!!!

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 20 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

Programinglanguage(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

Programinglanguage(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 OntologyThe 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 AnnotationISS Inferred from Sequence SimilarityIEP Inferred from Expression PatternIMP Inferred from Mutant PhenotypeIGI Inferred from Genetic InteractionIPI Inferred from Physical InteractionIDA Inferred from Direct AssayRCA Inferred from Reviewed Computational AnalysisTAS Traceable Author StatementNAS Non-traceable Author StatementIC Inferred by CuratorND No biological Data availableDetailed 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

How close are we to have good, comprehensive & universally used

classifications?• Far!!!!!

• BMC Bioinformatics + Bioinformatics publish papers with proposals for new ontologies and classifications almost every month in one are or another of molecular biology.

• Wet lab molecular biologists still not won to the cause of single name for single entity…

• There is hope! The situation is much better than 5 years ago!!!

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• A simple bioinformatics class server

An example of WAMP• A simple bioinformatics class server

An example of WAMP• A simple bioinformatics class server

An example of WAMP• A simple bioinformatics class server

Wireless

Apache

An example of WAMP• The bioinformatics class server

Wireless

Apache

MySQL

PHP

How close are we to have good, comprehensive & universally used

data repositories?• Not far at all!!!!!

• NCBI, KEGG, Protein databank, SGD, Uniprot,….

• Problems:• Redundant data over many databases…• Conflicting information due to the use of different

data sources, standards, and classifications

A glimpse at a useful present

Data Sources

Data warehouse

Relational tools

Online analytical processing tools

Applications

A glimpse of a useful present

A glimpse of possible futures

A glimpse of possible futures

The future• Cloud computing

• Distributed computation

• Artificial inteligence methods to facilitate data search, analysis and mining

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.

A glimpse at a useful present