Workshop

Bioinformatics and Computational Biology

Madrid, 25th-26th April 2002Auditorio BBVA

Paseo de la Castellana, 81

Coordinated by Alfonso Valencia and Roderic Guigó

Post genomic technologies

Functional Genomics /variability

- DNA arrays

- SNPs

Functional Genomics /variability

- DNA arrays

- SNPs

GenomeSequencing

Structural

Proteomics

BIOINFORMATICBIOINFORMATICSSBIOINFORMATICBIOINFORMATICSS

- evolution- cellular organization- genotyping

- new drugs- cellular factory- biotecnology

Proteomics

- mass. spec.

- yeast two hybrid

Proteomics

- mass. spec.

- yeast two hybrid

Protein-protein interaction networks

Literature

Red de interacción entre proteínas

Extraída de la literatura (Alma Bionformática)

Experimental (CellZome)

Bioinformatics and Computational Biology in 10 years

Integration in biology

Big challenges

Data management

2000 2010

2-hybrid system

Chemistry

Genomic information

Genes of interest

Gene identification

Physical interactions

ExpressionArrays

Similarity of expression patterns

Profiles of metabolic products

PhenotypesSNPs

Characterization of mutants

Biological resultsBiological results

Mass spec. for protein

complexes

Information integration

Functional relations

Comparative genomics

Bioinformatics and

Computational

Biology

Increasingly complex data

Complex data (integrated databases)

Data management(databases)

OntologiesInformation

extraction

Mol. Biol. data Genome information

PostGenomic technologyWWW

Next Generation Internet

1980 1990 2000 2010

Integrative Biology / Biomedicine / Environment

Distributed GRID computing

1. Precise, predictive model of transcription initiation and termination: ability to predict where and when transcription will occur in a genome

2. Precise, predictive model of RNA splicing/alternative splicing: ability to predict the splicing pattern of any primary transcript in any tissue

3. Precise, quantitative models of signal transduction pathways: ability to predict cellular responses to external stimuli

4. Determining effective protein:DNA, protein:RNA and protein:protein recognition codes

5. Accurate ab initio protein structure prediction

6. Rational design of small molecule inhibitors of proteins

7. Mechanistic understanding of protein evolution: understanding exactly how new protein functions evolve

8. Mechanistic understanding of speciation: molecular details of how speciation occurs

9. Continued development of effective gene ontologies - systematic ways to describe the functions of any gene or protein

10. Education: development of appropriate bioinformatics curricula for secondary, undergraduate and graduate education

Reprinted from Genome Technology, issue No. 17, January, 2002

Top 10 problems

VI Framework Programme (1)

PRIORITY THEMATIC AREAS OF RESEARCH IN FP6

1. Integrating and Strengthening the European Research Area 1.1.1 Genomics and biotechnology for healthThe sequencing of the human genome and many other genomes heralds a new age in human biology, offering unprecedented opportunities to improve human health and to stimulate industrial and economic activity. In making its contribution to realising these benefits, this theme will focus on integrating post-genomic research into the more established biomedical and biotechnological approaches, and will facilitate the integration of research capacities (both public and private) across Europe to increase coherence and achieve critical mass. Integrated multidisciplinary research, which enables a strong interaction between technology and biology, is vital in this theme for translating genome data into practical applications. In addition, an essential element will be to involve key stakeholders, for example, as appropriate industry, healthcare providers and physicians, policy makers, regulatory authorities, patient associations, and experts on ethical matters, etc in implementing the theme. Gender equity in the research will also be ensured.

This thematic priority area will stimulate and sustain multidisciplinary basic research to exploit the full potential of genome information to underpin applications to human health. The emphasis will be put on research aimed at bringing basic knowledge through to application, to enable real and consistent progress in medicine and improve the quality of life. This research may also have implications for research on areas such as agriculture and environment, which are addressed under other thematic priorities.

1.1.2 Information Society technologies1.1.3 Nanotechnologies and nanosciences, knowledge-based multi-functional materials and new production processes and devices1.1.4 Aeronautics and space1.1.5 Food Quality and Safety1.1.6 Sustainable development, global change and ecosystems1.1.7 Citizens and Governance in a Knowledge-based society

VI Framework Programme (1) 1.1.1.i Advanced genomics and its applications for health 1.1.1.i.a Fundamental knowledge and basic tools for functional genomics in all organismsThe strategic objective of this line is to foster the basic understanding of genomic information, developing the knowledge base, tools and resources needed to decipher the function of genes and gene products relevant to human health and to explore their iinteractions with each other and with their environment. Research actions will encompass the following:

Gene expression and proteomics: Developing high throughput tools and approaches for monitoring gene expression and protein profiles and for determining protein function and protein interactions.

Structural genomics: developing high throughput approaches for determining high-resolution 3-D structures of macromolecules.

Comparative genomics and population genetics: Research will focus on: developing model organisms and transgenic tools; developing genetic sepidemiology tools and standardised genotyping protocols.

Bioinformatics: The objectives are to enable researchers to access efficient tools for managing and interpreting the ever-increasing quantities of genome data and for making it available to the research community in an accessible and usable form. Research will focus on: developing bioinformatic tools and resources for data storage, mining and processing; developing computational biology approaches for in silico prediction of gene function and for the simulation of complex regulatory networks.

Multidisciplinary functional genomics approaches to basic biological processes: Research will focus on: elucidation of the mechanisms underlying fundamental cellular processes, to identify the genes involved and to decipher their biological functions in living organisms.

1.1.1.i.b Applications of knowledge and technologies in the field of genomics and biotechnology for health1.1.1.ii Combating major diseases1.1.1.ii.a Application-oriented genomic approaches to medical knowledge and technologies1.1.1.ii..b Combating cancer1.1.1.ii.c Confronting the major communicable diseases linked to poverty

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Año 1

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Operaciones básicas en desarrollo de fármacos

Compuestos cabeza de serie

Ensayos robotizables

Bioquímicos y celulares

Compuestos optimizados

Toxicidad /especificidad

Ensayos clínicos Fase III

Ensayos clínicos Fase I

Ensayos clínicos Fase II

Nuevos fármacosDianas terapeuticas

Síntesis química

Diseño racional

Comercialización

Inversión

Librerias de compuestos naturales

Compuestos purificados

Librerias combinatoriales

bioinfo

bioinfo

bioinfo

bioinfo

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1996 1997 1998 1999 2000 2001

Number ofcompoundsGlobal R&DBillion $

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25th AprilGenomics, proteomics and data integration Example Protein “functions”

Temple F. Smith, Boston University

Assembling puzzles by breaking them into smaller pieces

Pavel A. Pevzner, University of California, San Diego

The Evolution of Structure and Function in Protein Superfamilies

Christine Orengo, University College London

Predicting protein functions, pathways from genome sequences

Martijn A. Huynen, Nijmegen Center for Molecular Life Sciences

Statistical design and analysis of DNA microarray experiments

Sandrine Dudoit, University of California, Berkeley

Specificity in protein interactions

Rob Russell, European Molecular Biology Laboratory

26th AprilPrediction of orphan protein function

Soren Brunak, The Technical University of Denmark

Comparative modelling of protein structures: advances and pitfalls

Anna Tramontano, University of Rome “La Sapienza”

Comparative gene prediction

Roderic Guigó, Institut Municipal d’Investigació Mèdica

From Microarrays to Gene Networks

Jack Vilo, European Bioinformatics Institute

Structural Proteomics by Machine Learning Methods

Pierre Baldi, University of California, Irvine

Detecting genomic features under weak selective pressure: the example of codon usage in animals and plants

Laurent Duret, Université Claude Bernard–Lyon 1

Prediction of protein interaction network

Alfonso Valencia, Centro Nacional de Biotecnología

Evolution teaches protein structure prediction

Burkhard Rost, Columbia University

LA SEQÜÈNCIA DEL GENOMA HUMÀ

Computing at Celera Genomics

•200 teraflops•1000 vegades més potent que deep blue•Més potent que els 500 ordinadors més potents avui en dia

llei de Moore

creixement de les dades genòmiques