Industriakademin 2005 10 27

Information about Industriakademin 2005 10 27

Published on February 6, 2008

Author: Hillary

Source: authorstream.com

Content

Utmaningar för bioinformatiken inom industri och akademi:  Utmaningar för bioinformatiken inom industri och akademi Per Kraulis Biovitrum AB Industriakademin, 27 okt 2005 Landskapet 1:  Landskapet 1 Homo sapiens genomet klart (nåja) Flera mammalie-genom, i användbart skick 1000 bakterie-genom (snart) Genidentifiering, annotering Proteinkodande gener identifierade Sköts av stora centra: inget för mindre grupper RNA-gener och reglering: mycket att göra Landskapet 2:  Landskapet 2 Expressionsanalys Mognande teknik och analysmetoder Nya applikationer/analyser? Proteomik Stora dataset, nya typer av data Ex: HPR www.proteinatlas.org Mycket att göra Landskapet 3:  Landskapet 3 Nätverksanalys Signalering Metabola nätverk Databaser, litteratur (text mining) Systembiologi Modeller av mekanismer, simulering Förklaring av förlopp Men: Prediktion! Varför så skralt? Förändring av fokus:  Förändring av fokus Struktur genom gener proteinsekvenser proteindomäner Processer förlopp nätverk signallering metabolism Bioinformatics Integrated Pharmacology, Biovitrum:  Bioinformatics Integrated Pharmacology, Biovitrum Sequence analysis Homologs Orthologs Splice variants Expression patterns Pathway analysis System effects Study design Readouts Biomarkers Drug discovery pipeline Target Lead Animal models In vivo studies CD In vitro Clinical Tes 1: Sekvensorienterad bioinformatik är rutin:  Tes 1: Sekvensorienterad bioinformatik är rutin Annotering finns i publika DB Verktyg finns tillgängliga Få uppenbara möjligheter till “lyft” Undantag RNA Fylogenetiska jämförelser Tes 2: Vissa behov ej uppfyllda:  Tes 2: Vissa behov ej uppfyllda Saknas: Annoteringssystem för små grupper med intresse för specifika gener/system Existerande produkter är “imperialistiska” Idéer: Modell: Dossier eller ‘best current view’ Editera: web eller specialverktyg Läs: web eller PDF Tes 3: Nya ‘drug targets’ från biologi, funktion (inte sekvens):  Tes 3: Nya ‘drug targets’ från biologi, funktion (inte sekvens) ‘Drug target hunting’ är passerat kapitel Tillbaka till cellbiologi, farmakologi, mm Hur kan bioinfo hjälpa experimentalisten? Ordna, systematisera litteraturen Designa experiment Välja ‘read-outs’ Handskas med data (DB motsv) Tes 4: (Bio)informatik krävs för systembiologi:  Tes 4: (Bio)informatik krävs för systembiologi Mekanistiska modeller standard (nåja) SBML, Reactome, KEGG, etc Men förloppen som ska simuleras? Datamodeller/databaser saknas! Initialvärden, randvillkor Kontext Dynamiska förändringar Tes 5: Bioinformatiken måste ta sig an biologiska förlopp:  Tes 5: Bioinformatiken måste ta sig an biologiska förlopp Förlopp (processer) är biologins hjärta Den temporala aspekten är central Ex: Vad händer när en cell stimuleras? Ex: Cell-cykeln: vilka komponenter, processer? Få databaser/datamodeller! Jmf: Geographical Information Systems (GIS), temporala aspekter forskas kring sedan 15 år Proto-Systems biology?:  Proto-Systems biology? If sufficient regularity can be found between molecular entities and logical and informational outcomes to allow appropriate databases to be built, then genomic and post-genomic data could be interrogated more effectively. … If successful, this approach would not require detailed kinetic analyses of all processes within cells, but rather rely on more cursory calculations to study phenomena of interest. Paul Nurse, ”Understanding cells”, Nature (424) 2003, 883. Computable information:  Computable information Free text Ontology Relational DB Keyword/value data Petri Net, logic Statecharts, UML Annotated text Unwritten Diff equ model Simulation Multiple levels and types in biology:  Multiple levels and types in biology Objects Molecules Complexes Compartments Cells Events Reactions Transport Signals Processes Millán & Ridley (2005) Theory Explanation Prediction:  (Computable) information Theory Explanation Prediction The predictions…:  The predictions… Roles of uncharacterized components Behavior after perturbation Suggest points of intervention; drug targets Part 1: Molecular data:  Part 1: Molecular data Molecular components Genomics, transcriptomics, proteomics, etc Molecular events Interactions Modifications Localisation Explicit data model required for DB! Part 2: Macroscopic processes:  Part 2: Macroscopic processes Describe macroscopic processes Simulations must be compared with something Goal-oriented description? What is required to achieve a specific state? Life processes as projects Goals, milestones Resource usage; scheduling Subprojects, tasks GeneCV concepts:  GeneCV concepts Entities Genes Proteins Molecules Complexes States Complexes, member of Modifications Location Transitions Creation Destruction Interactions Regulation Transport Ras p21 Chem: unmodified Location: cytosol Ras p21 Chem: farnesylated Location: membrane Statecharts:  Statecharts David Harel, 1987 Describe reactive computer systems Event-driven Responding to external and internal stimuli State-transition diagrams extended with: Hierarchy Orthogonality Communication Now part of UML Statecharts: states and events:  Statecharts: states and events On Off Error Reset Statecharts: state hierarchy:  Statecharts: state hierarchy Statecharts: state orthogonality:  Statecharts: state orthogonality Active On Off Error Reset Mode Debug Statecharts: conditions:  Statecharts: conditions Debug_command [User_is_admin] Modeling T-cell transformations Kam, Cohen, Harel 2001:  Modeling T-cell transformations Kam, Cohen, Harel 2001 Example: Lysine post-transl mod's:  Example: Lysine post-transl mod's www.reactome.org:  www.reactome.org CSHL, EBI, GO collaboration Entities Generic/concrete No explicit state; no hierarchy of states Events Hierarchy Molecular as well as macroscopic (processes) www.signaling-gateway.org:  www.signaling-gateway.org Alliance for Cell Signaling, AfCS Molecules Proteins States No hierarchy Molecular only; complexes are states Location is not state Transitions Conditions? GeneCV:  GeneCV The life of a biomolecule Molecular data only! Creation Maturation Transport Interactions Destruction Mendenhall & Hodge 1998

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