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Zoomable Cell Matthias Reimann , Anne Tuukannen , Michael Schroeder

Fakultät Informatik. Zoomable Cell Matthias Reimann , Anne Tuukannen , Michael Schroeder Marcel Spehr , Dimitrij Schlesinger, Stefan Gumhold. Vision. Microscopy images. Protein interactions and 3D structures. 10.000nm. 1.000 nm. 100 nm. 10 nm. 1 nm. A. B. C. D. E. F.

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Zoomable Cell Matthias Reimann , Anne Tuukannen , Michael Schroeder

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  1. Fakultät Informatik • Zoomable Cell Matthias Reimann, Anne Tuukannen, Michael Schroeder Marcel Spehr, Dimitrij Schlesinger, Stefan Gumhold

  2. Vision Microscopyimages Protein interactions and 3D structures 10.000nm 1.000 nm 100 nm 10 nm 1 nm A B C D E F G H I Naturalcoordinatesystem Data Abstract cell Zoomable cell >200.000 images from scientific literature ? >48.000 3D proteinstructures from PDB

  3. Achievements • Protein interactions and 3D structures • Algorithmforconstraint-basedconstruction of large complexeswithusecase in histonemethyltransferase SET1(In Proteomics 2010)Novelty: constraincombinatorialexplosionwithproteininteractiondata • Networkvisualisationwith power graphswithdiseaseapplicationsNovelty: exploitingmodules in graphsforvisualisation(In Experimental Cell Research 2010, Neurological Research 2010, 2 submitted) • NaturalCoordinate System • DOG4DAG: Semi-automatedgeneration of term, definitions, and hierarchiesNovelty: First system to integrate all steps of ontologygeneration + Evaluation(In Bioinformatics 2010) • Microscopyimages • Image search and classificationwithnaturalcoordinatesystemNovelty: Image librarywith 1.3Mio images, Implementation of image similaritymeasures and filters, GoImagesystemwith 745000 images(manuscript in preparation)

  4. Contents • Constraint-basedmodelling of complexes • Image search and classificationwithnaturalcoordinatesystem • Limits and Perspectives

  5. Dim-5 protein Suv39-type histone K9 methyltransferase Histones and histonemethyltransferases • DNA is a longstringwoundaroundhistones • Histonesaremodifiedbyhistonemethyltransferases MolecularCellBiology, Lodishet al. Met Histone H3

  6. Interactions of SET1 subunits Positive Interactions Set1 - Bre2 Set1 - Shg1 Set1 - Ssp1 Set1 - Swd1 Set1 - Swd2 Set1 - Swd3 Bre2 - Bre2 Swd1 - Swd3 Swd2 - Swd2 Bre2 - Sdc1 Negative Interactions Set1 - Sdc1 Bre2 – Sdc1 – Bre2 AP/MS and Y2H Roguevet al. 2004 , Deheet al. JBC (2006)‏

  7. Workflow

  8. Constraints

  9. Model

  10. Contents • Constraint-basedmodelling of complexes • Image search and classificationwithnaturalcoordinatesystem • Limits and Perspectives

  11. Image search and classification • Currentengines: • Yale Image finder, (FigSearch), BioTextSearchEngine • No web • No filtering of graphs, tables, formulas, photos, etc. • ZoomableCell image search • 90% of imagesnotsuitable • Yahoo Boss API to retrieveseveralmillions of images • Bottom up approach: • Manual selection of 2.000 from 20.000 images • Expansion of seedimages to 745.000 imagesby image similarity • Image similarity • Gistscenedescriptor (960 image features) • Approximatenearestneighbourclustering

  12. 266 imagesfor Endoplasmicreticulum 2 out of 266 forrodents Similarimages

  13. Navigation in Large Information Spaces • Similarity based vector representation of images transforms problem into search scenario in high dimensions • Image features constitute space • Images are instances of space points • Usage of Kernel PCA permits consistent handling of similarities from different feature domains Similarity Measures di Combined Feature Space ϕ (dimensionality adjustable) Kernel PCA

  14. Image features

  15. Idea from Optimization Taxi-Cab Method: reduce to 1D minimization along ϕ axes User performs search interactively: Problem: sparsely sampled space Directed Search Strategies in ϕ ϕ2 x0 ϕ1 ϕ2 ϕ1

  16. Sample along each ϕ axis: as close as possible to axis reachability of all images Solution use Voronoi Regions of ϕ axes to assign all images filter out all images that can be reached indirectly over remaining images Directed Search Strategies in ϕ

  17. Results

  18. Star view and userfeedback

  19. Continuous zoom at different time steps and resolutions • Problem: Transforming one image into another by generating a sequence of intermediate images to achieve a seamless transition • As automatic as possible and user adjustable • Thin plate spline + optical flow

  20. Contributions, Limits, and Perspectives • Contributions: • Small scale, semi-automated, constraint-basedmodelling of complexespossible • Compact visualisation of proteininteractionnetworkswith power graphs • Imagesearch (library, textual and image similarity, navigation, learning) • Zooming • Limits: • Large-scale, automatedmodelling of complexesnotpossible • Additional dataneeded on structures, interactions, EM maps, localisation • Integration of coherent image data • Perspective: • Concreteapplication in fruitflydevelopment • Integratingvideomicroscopydata, manualannotation, protein and proteininteractiondata

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