Workshop Bioinformatics and Computational Biology

1. WorkshopBioinformatics and Computational Biology Madrid, 25th-26th April 2002Auditorio BBVAPaseo de la Castellana, 81 Coordinated by Alfonso Valencia and Roderic Guigó

2. Literature - evolution - cellular organization - genotyping - new drugs - cellular factory - biotecnology Post genomic technologies Genome Proteomics - mass. spec. - yeast two hybrid Sequencing Structural Proteomics Functional Genomics / variability - DNA arrays - SNPs BIOINFORMATICS Protein-protein interaction networks

3. Red de interacción entre proteínas Extraída de la literatura (Alma Bionformática) Experimental (CellZome)

4. Big challenges Integration in biology Data management 2000 2010 Bioinformatics and Computational Biology in 10 years

5. Information integration Comparative genomics Expression Arrays Genomic information Functional relations Similarity of expression patterns Chemistry Gene identification Profiles of metabolic products Genes of interest Bioinformatics and Computational Biology Physical interactions 2-hybrid system Characterization of mutants Mass spec. for protein complexes Biological results Phenotypes SNPs

6. Increasingly complex data Data management (databases) Complex data (integrated databases) Ontologies Information extraction Mol. Biol. data Genome information WWW PostGenomic technology Next Generation Internet Distributed GRID computing Integrative Biology / Biomedicine / Environment 1980 1990 2000 2010

7. Top 10 problems • Precise, predictive model of transcription initiation and termination: ability to predict where and when transcription will occur in a genome • Precise, predictive model of RNA splicing/alternative splicing: ability to predict the splicing pattern of any primary transcript in any tissue • Precise, quantitative models of signal transduction pathways: ability to predict cellular responses to external stimuli • Determining effective protein:DNA, protein:RNA and protein:protein recognition codes • Accurate ab initio protein structure prediction • Rational design of small molecule inhibitors of proteins • Mechanistic understanding of protein evolution: understanding exactly how new protein functions evolve • Mechanistic understanding of speciation: molecular details of how speciation occurs • Continued development of effective gene ontologies - systematic ways to describe the functions of any gene or protein • Education: development of appropriate bioinformatics curricula for secondary, undergraduate and graduate education Reprinted from Genome Technology, issue No. 17, January, 2002

8. 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 health The 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 technologies 1.1.3 Nanotechnologies and nanosciences, knowledge-based multi-functional materials and new production processes and devices 1.1.4 Aeronautics and space 1.1.5 Food Quality and Safety 1.1.6 Sustainable development, global change and ecosystems 1.1.7 Citizens and Governance in a Knowledge-based society

9. 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 organisms The 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 health 1.1.1.ii Combating major diseases 1.1.1.ii.a Application-oriented genomic approaches to medical knowledge and technologies 1.1.1.ii..b Combating cancer 1.1.1.ii.c Confronting the major communicable diseases linked to poverty

10. bioinfo Librerias de compuestos naturales Compuestos purificados Año 1 9 8 Síntesis química 7 6 Ensayos clínicos Fase III 2 Librerias combinatoriales bioinfo 5 3 4 Ensayos clínicos Fase II bioinfo Diseño racional Ensayos clínicos Fase I bioinfo Inversión Operaciones básicas en desarrollo de fármacos Comercialización Dianas terapeuticas Nuevos fármacos Ensayos robotizables Bioquímicos y celulares Compuestos cabeza de serie Toxicidad / especificidad Compuestos optimizados

11. 25th April Genomics, 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

12. 26th April Prediction 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

13. LA SEQÜÈNCIA DEL GENOMA HUMÀ

14. Computing at Celera Genomics

15. 200 teraflops • 1000 vegades més potent que deep blue • Més potent que els 500 ordinadors més potents avui en dia

16. llei de Moore

17. creixement de les dades genòmiques