9 th International Conference on Intelligent System for Molecular Biology

1. 9th International Conference on Intelligent System for Molecular Biology Tivoli Gardens, Copenhagen, Denmark July 19-26, 2001 Park, Ji-Yoon

2. Satellite Meetings(July 19-20) July 19 - The Open Source author’s contract : Steven Brenner - BioJava project report: Thomas Down and Matthew Pocock - Biopython project report: Andrew Dalke - BioCORBA project report: Jason Stajich - biok: Catherine Letondal - Lightning Talks: • OMG’s new Model Driven Architecture(MDA): Scott Markel • BioRuby: Yoshinori Okuju, Toshiaki Katayama, and Mitsuteru Nakao • Genquire: David Block • Generation and use of substitution matrices in Biopython: IDDo Friedberg and Brad Chapman

3. Satellite Meetings(July 19-20) July 20 : Biopathway - Bioperl project report: Hilmar Lapp - EnsEMBL project report: Arne Stabenau - Lightning Talks: • Bioperl-project: Ewan Birney • OpenBSA: Juha Muilu, Martin Senger and Alan Robinson • Genetic algorithm and neural network libraries: Brad Chapman • Mining gene expression information using a controlled hierarchical vocabulary : Peter van heusden • TFBS: Perl modules for transcription factor detection and analysis: Boris Lenhard - A tool suite for the Gene Ontology: Chris Mungall, Hohn Richter, Bradley Marshall, and Suzanna Lewis - DeCAL: A system for constructing comparative maps: Debra Goldberg, Jon Kleinberg, and Susan McCouch

4. Tutorial( July 21) * Morning Turorials: Sat July 21 8:30-12:30 [Statistical analysis of micro-arrays studies] : Emmanuel Lazaridis, University of South Florida Afternoon Turorials: Sat July 21 14:00-18:00 [Network genomics] : Christian Forst, Los Alamos National Laboratory

5. Sequence motifs, alignments and families: July 22 [Keynote: Protein folding, molecular evolution, and human disease] : Christopher M. Dobson, University of Oxford ►Protein misfolding in disease ►misfolded polypeptide → folded protein ↓ ↓ misfolding ↓ ↓ improper trafficking toxic folding degradation ►Asp67His: Amyloid formation(; aggregation) ►SH3 domain of PI3 kinase: Cross- structure

6. Sequence motifs, alignments and families: July 22 * An insight into domain combinations * Prediction of the coupling specificity of G protein coupled receptors to their G proteins * Improved prediction of the number of residue contacts in proteins by recurrent neural networks * Non-symmetric score matrices and the detection of homologous transmembrane proteins * Generating protein interaction maps from incomplete data: application to fold assignment

7. Sequence motifs, alignments and families: July 22 [Keynote - Structural Genomics] - Christopher M. Dobson, University of Oxford - Goal : All protein domains carry all functional families How many experimental structure? - Coordination of international programs in structural genomics - Pathways in expression profile * 0j-py: a software tool for low complexity proteins and protein domains : Michael J. Wise, Centre for Communications Systems Research →new tool for looking peptide * Separating real motifs from their artifacts * Feature selection for DNA methylation based cancer classification * An algorithm for finding signals of unknown length in DNA sequences

8. Networks and Modeling: July 23 [Keynote- Protein Interactions] : David Eisenberg, University of California, LosAngeles • Rossetta Stone - Fusion of functionally-linked domain - http:// dip.doe-mbi.ucla.edu • Phylogenic profile - correlated occurrence of pairs of proteins in genomes • Gene function • Database interacting protein • 3D domain swapping • Signaling path

9. Networks and Modeling: July 23 <Protein-protein interaction map inference using interacting domain profile pairs> : Jerome Wojcik, Vincent Schachter, Hybrigenics S.A ► Computational prediction of protein network ► IDPP(Interacting domain profile pair) method • Interacting domain cluster = vertics • Interacting domain profile pair = edge ►Assessment of predictive accuracy: reference data problem * Inferring subnetworks from perturbed expression profiles : http:// www.cs.huji.ac.il/labs/combio * Molecular classification of multiple tumor types : http:// geone.wi.mit.edu/MPR * Centralization: a new method for the normalization of gene expression data

10. Networks and Modeling: July 23 [ Centralization: a new method for the normalization of gene expression data ] * Housekeeping approach is questionable. * Basic assumption ; roughly the gene level expression no preffered direct of regulation - real data: differently & strongly regulation - total RNA vary: different cell state/tissue - different factors are summed - only subset of all gene measured - strongly expressed gene be regulated: main protein product * Advantage - more robus on real data - inexpensive alternative experiment - Easy Keynote- The phenomenon of the web: David Eisenberg, University of California, Los Angeles

11. Networks and Modeling: July 23 [Keynote- The phenomenon of the web] : David Eisenberg, University of California, Los Angeles http: // rana.lbl.gov http:// genome-www.standford. edu./microarray

12. Gene structure, Regulation, and Modeling: July 24 * Keynote- The Modern RNA world: many genes don’t encode proteins : Sean Eddy, Washington University * Promoter prediction in the human genome * Joint modeling of DNA sequence and physical properties to improve eukaryotic promoter recognition * Computational expansion of genetic networks * GENIES: a natural-language processing systems for the extraction of molecular pathways from journal articles * Designing better phages * Computational Analysis of RNA splicing * Disambiguating proteins, genes, and RNA in text: a machine learning approach * Gene recognition based on DAG shortest paths * An efficient algorithm for finding short approximate non-tandem repeats

13. Methods: July 25 * Keynote- Membrane proteins: From the computer to the bench and back: Gunnar von Heijne, Stockholm University * Design of a compartmentalized shotgun assembler for the human genome * Probabilistic approaches to the use of higher order clone relationships in physical map assembly: * Fragment assembly with double-barreled data * SCOPE: a probabilistic model for scoring tandem mass spectra against a peptide database * Probe selection algorithms with applications in the analysis of microbial communities * Fast optimal leaf ordering for hierarchical clustering * Separation of samples into their constituents using gene expression data

14. WEB: July 26 * Education in Bioinformatics: Current Trends and Issues. - Shoba Ranganathan * Opening Addresss: Bioinformatics Education - Looking to the Future: Russ Altman * The S* Life Science Informatics Alliance - Shoba Ranganathan * Bioinformatics BS at the Univerisity of California, Santa Cruz - Kevin Karplus * A Masters Degree in Bioinformatics in Switzerland - Patricia Palagi * Emerging US & UK Standards for Graduate Bioinformatics training - Linda Ellis

15. WEB: July 26 * Bioinformatics Course Delivery: Tools and Infrastructure. Siv Andersson(Chair) * Bioinformatics: Introducing the concept of “ evaluation-based” learning : Siv Andersson * Problem-oriented sequence analysis tool: Ueng-Cheng Yang * EMBER- A European Multimedia Bioinformatics Educational Resource: C. Victor Jongeneel * Virtual Reality and Visualization for Bioinformatics Education: YY Cai * Starting a new Bioinformatics Program. Phyllis Gardner(Chair) * Initiating a multi-disciplinary, trans-institutional program: A Dean’s perspective: Phyllis Gardner * Insights into starting a new Multi-disciplinary program: Betty Cheng

16. WEB: July 26 * Bioinformatics Training. Frederique Galisson(Chair) * The Canadian Bioinformatics Workshops: Stephen Herst * The BioNavigator Education Package- resources for practical instruction in bioinformatics: Bruno A. Gaeta * The Human Genome Mapping Project Resources Centre- Encouraging Bioinformatics Awareness: Lisa Mullan * Panel Discussion: Betty Cheng(Chair) The S* Life Science Informatics Alliance: Question Time: S* Team * Concluding Session: Closing Remarks. Shoba Ranganathan(Chair) Bioinformatics Education: Future trends and perspectives: Philip Bourne

18. Free Energy(∆ G ) Thermodynamic constant that gives the amount of energy required for or released by a reaction - kcal/mol - Reaction that require energy ; positive - Reation that release free energy ; negative - Energy must be released overall to form a base-paired structure - The stability of the structure is determined by the amount of energy released

19. Hairpin Structure

20. The Overall Free Energy of a double-stranded structure ∆ G total= ∆ G i + ∑ ∆ Gx + ∆ ∑ Gu ∆ Gi : the free energy for initiation of a double helix  Positive value: + 3.4 kcal/mol  It applied to intermolecular duplex formation ∑ ∆ Gx:the sum of the individual reactions involved in propagating the double helix as each base pair is added  the formation of each base pair releases energy ; negative ∑∆Gu: the sum of individual instances encountered as the double helix is propagated in which the opposing bases are not complementary  the energy required to hold these bases in an unpaired state ; positive

21. The Free Energy of formation for a potential base-paired region

22. Free Energy of Base Pairing