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AWG Medicine and Bioinformatics




                       F. Cazals
                          INRIA
3D and Knowledge in Medicine and
Bioinformatics
Medicine
  Geometric Modeling
      Diagnostic
      Therapy planning
          Surgery
          Radiotherapy
      Legal medicine
3D and Knowledge in Medicine and
Bioinformatics
Biology
    Docking
       Molecular surfaces and volumes
       Modeling molecular interfaces
       Modeling pockets and channels
       Databases (e.g. PDB), functional classifications
   Folding
       Conformers
       Atomic environments
       Folding styles
Geometry and Knowledge: Synergy
  Model: geometry and knowledge
  Geometry:
      At organ level: tissues (volumes and
      surfaces),
      interfaces (surfaces), relative
      positioning.
      At molecule level: atoms (locations,
      shape), bonds, secondary structure,
      domains.
  Knowledge:
      Anatomy, physiological and
      pathological parameters.
      Chemical and interaction types, affinity
      specificity of interactions.
Contacts
Medicine
  #contacts: 20
  #questionnaires: 12

Categories
   Methodology
       e.g., image segmentation, mesh generation,
       simulation
   Application
       e.g., organ or pathology-specific
   Integration
       environment suppliers, medical teams
Contacts
Biology
    #contacts: 20
    #questionnaires: 13
Categories
   Methodology
       e.g., shape matching and comparison, shape
       reconstruction
   Applications
       folding, docking, drug design
   Integration
       environment suppliers, pharma-companies, biological
       teams
Example Key Players in Medicine

   Methodology
       Applied mathematicians: e.g., model design for
       dynamic heart simulation.

   Application
       Electro-physiologist: computer aided diagnostic
       and recovery after heart attack.

   Integration
       Medical team: optimization of pacemaker
       placement, resection.
Example Key Players in Biology

   Methodology
       Biophysicist / applied mathematician: e.g.,
       algorithms for electrostatic calculations (Poisson-
       Boltzmann)‫‏‬
   Application
       Biophysicist into folding and misfolding (e.g.,
       amyeloid diseases)‫‏‬
   Integration
       Structural Modeling group: from bio-physical
       measurements to simulations
Scenario in Biomedicine
Simulating human articulations:
        bone resection
        Prosthesis placement
Parameters of interest:
         contact pressure within the
         cartilages
         forces during motion
         muscle biomechanics
Connection to physiology:
         material properties
         bone motion and geometry
Since the parameters are
stored in the ontology, the data
process is simplified.
Scenario in Biomedicine
Modeling anatomy
       patient-specific
       therapy planning
       e.g., air flow
       simulation
Parameters of interest:         segmentation of upper respiratory tract

       flow, pressure
       deformations
Connection to physiology:
       material properties
       geometry of upper
       respiratory tract
                             mesh generation
                             for simulation
Scenario in Bioinformatics
Docking two molecules involves:
        Homology modeling
        Rigid body docking
        Side chain placement
        Molecular dynamics simulations
Parameters of interest:
        Homology between proteins
        Known partners
        Rigid domains within protein
        Key residues
        Correlated motions
Connections to experiments
        Directed mutagenesis
        Affinity and specificity
        measurements (e.g. BIACORE)
Assessment
  Case 1: The problem description is complete
      Key parameters identified
      Geometric models effective for description and prediction
      Ex: articulations, zoo of protein folds
      Ontologies crucial to integrate
      Synergy needed between geometry, models and ontologies
  Case 2: Problem partially described
      Key parameters not yet identified
      Incomplete knowledge
      Hazardous extrapolation and prediction
      Ex: brain modeling, protein folding process
      Building blocks of models to be elaborated upon
      Integration will come next

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FOCUS K3D AWG Medicine and Bioinformatics

  • 1. AWG Medicine and Bioinformatics F. Cazals INRIA
  • 2. 3D and Knowledge in Medicine and Bioinformatics Medicine Geometric Modeling Diagnostic Therapy planning Surgery Radiotherapy Legal medicine
  • 3. 3D and Knowledge in Medicine and Bioinformatics Biology Docking Molecular surfaces and volumes Modeling molecular interfaces Modeling pockets and channels Databases (e.g. PDB), functional classifications Folding Conformers Atomic environments Folding styles
  • 4. Geometry and Knowledge: Synergy Model: geometry and knowledge Geometry: At organ level: tissues (volumes and surfaces), interfaces (surfaces), relative positioning. At molecule level: atoms (locations, shape), bonds, secondary structure, domains. Knowledge: Anatomy, physiological and pathological parameters. Chemical and interaction types, affinity specificity of interactions.
  • 5. Contacts Medicine #contacts: 20 #questionnaires: 12 Categories Methodology e.g., image segmentation, mesh generation, simulation Application e.g., organ or pathology-specific Integration environment suppliers, medical teams
  • 6. Contacts Biology #contacts: 20 #questionnaires: 13 Categories Methodology e.g., shape matching and comparison, shape reconstruction Applications folding, docking, drug design Integration environment suppliers, pharma-companies, biological teams
  • 7. Example Key Players in Medicine Methodology Applied mathematicians: e.g., model design for dynamic heart simulation. Application Electro-physiologist: computer aided diagnostic and recovery after heart attack. Integration Medical team: optimization of pacemaker placement, resection.
  • 8. Example Key Players in Biology Methodology Biophysicist / applied mathematician: e.g., algorithms for electrostatic calculations (Poisson- Boltzmann)‫‏‬ Application Biophysicist into folding and misfolding (e.g., amyeloid diseases)‫‏‬ Integration Structural Modeling group: from bio-physical measurements to simulations
  • 9. Scenario in Biomedicine Simulating human articulations: bone resection Prosthesis placement Parameters of interest: contact pressure within the cartilages forces during motion muscle biomechanics Connection to physiology: material properties bone motion and geometry Since the parameters are stored in the ontology, the data process is simplified.
  • 10. Scenario in Biomedicine Modeling anatomy patient-specific therapy planning e.g., air flow simulation Parameters of interest: segmentation of upper respiratory tract flow, pressure deformations Connection to physiology: material properties geometry of upper respiratory tract mesh generation for simulation
  • 11. Scenario in Bioinformatics Docking two molecules involves: Homology modeling Rigid body docking Side chain placement Molecular dynamics simulations Parameters of interest: Homology between proteins Known partners Rigid domains within protein Key residues Correlated motions Connections to experiments Directed mutagenesis Affinity and specificity measurements (e.g. BIACORE)
  • 12. Assessment Case 1: The problem description is complete Key parameters identified Geometric models effective for description and prediction Ex: articulations, zoo of protein folds Ontologies crucial to integrate Synergy needed between geometry, models and ontologies Case 2: Problem partially described Key parameters not yet identified Incomplete knowledge Hazardous extrapolation and prediction Ex: brain modeling, protein folding process Building blocks of models to be elaborated upon Integration will come next