Seminar agenda: to know who is doing what within the EMBL with images + to be enlightened by imaging related researches going on outside the EMBL.

More details here: CMCI seminar details

The 3rd CMCI Image Analysis Mini Symposium

room: 202

Organizers

• Kota Miura
• Andrea Picco

1. Volker Hilsenstein
   • Title: (TBA, interfacing Cellprofiler to the Microscopes)
2. Christian Tischer
   • Title: Fully Automated FRAP of ER Exit Sites
3. Julius Hossain
   • Title: Towards a canonical four dimensional computational model of the dividing human cells
4. Yin Cai
   • Title: Automatic analysis of subcellular protein distributions and temporal dynamics during mitosis

1. Oleg Simakov
   • Title: Cell type profiling and morphometrics in Platynereis
2. Luis Pedro Coelho
   • Title: Location Proteomics Beyond the Pattern Recognition Approach
3. Sevi Durdu
   • Title: Tracking movement with peak detection
4. Justus Fuesers
   • Title: 2D image analysis from nuclear markers via machine learning-based segmentation to single cell tracking

1. Frank Stein
   • Title: FluoQ – a new ImageJ macro for rapid analysis of multiparameter fluorescence imaging data
2. Joseph Barry
   • Title: Measuring line curvature of intercellular membrane using EBImage

Mr. Wu, Bahnhofstr. 4

Two seminars on this day. Be careful for different rooms.

Majority Spanning Trees and Cotrees and Their Applications

Speaker's Affiliation: Department of Computer Science and Engineering, Bangladesh University of Engineering and Technology

Abstract: A new class of spanning trees, called Majority Spanning trees, and Majority Cotrees have been defined and their existence in directed graphs, with non-negative weights on edges, have been established. The applications of Majority Spanning Trees to Minimum Connection Time Problem and Optimal Ranking of a Round Robin Tournament have been shown.

Host: Julius Hossain

From template matching to traction force microscopy

Check his ImageJ Plugin page here!.

Motion filters and its application on target tracking

Julius is a new comer to EMBL, and is a computer scientists. We will have seminar about his previous works.

An Introduction to Clustering

An informal lecture, providing an introduction to learn various algorithms for clustering (with active interactions with the lecturer!)

Lecture Slides

An Introduction to Classification and Machine Learning

An informal lecture, providing an introduction to learn various algorithms for Classification and Machine Learning (with active interactions with the lecturer!)

Lecture Slides

Image analysis and modelling of organogenesis

Investigating tissue dynamics using random forests

Single Particle Tracking with CellProfiler

Visualization and Analysis of 3D tracking results

Abstract: capability of tracking 3D time series data is increasing, but it typically lacks methods to verify the results. Visualization of resulted tracks is a key. I will present some of the trials using 3Dviewer in ImageJ.

Designing Cost Functions for Particle Tracking Algorithm

Abstract: Linking between segmented objects could be done in many ways. I will present some of the example cost functions for particle linking, and also present example tracking results in Drosophila cells & Chromosomes.

Using Tracking to Deduce Endocytic Structures

imaging of co-recruited assemblies in vivo: analysis of the exocyst

Towards automated morphometrics and cellular expression profiling of marine invertebrates

Quantification of actin dynamics and tissue shape by live imaging in vivo

Complete 3D kinetochore tracking in mouse oocyte meiosis

“ImageJ and Fiji: current status and future”

Fiji is a distribution of ImageJ bundled with many high-end image processing and analysis algorithms. Johannes is at the hub of its developer community.

Since Johannes is a key figure of this open-source development project, we invited him to give his view on the current status of the ImageJ project and its future.

Quantitative measurement and modeling of cell size dependent spindle elongation in the C.Elegans Embryo

Cell Architecture Laboratory, Center for Frontier Research, National Institute of Genetics, Mishima, Japan

Abstract: The cell is a highly organized architecture that the positions, sizes, and shapes of intracellular organelles and other components are important for cell functions. Cell size is a critical parameter to control the size of intracellular structures. However, how cell size regulates the size of the intracellular structures is poorly understood. The mitotic spindle, a molecular machine that assembles and segregates chromosomes during cell division, is an important example whose size depends on cell size. We investigated the mechanism underlying the cell size-dependency of spindle elongation using Caenorhabditis elegans embryo as a model system. Quantitative measurements of spindle elongation in cells with various sizes revealed that the length and speed of spindle elongation depended on the cell size. Gene knockdown studies indicated that there are (at least) two qualitatively distinct mechanisms contributing to the cell size-dependent elongation of the spindle. Based on these observations and previous studies, we built several hypotheses that might account for the cell size-dependent elongation. We computed the consequences of these candidate hypotheses using computer simulation, and compared them with the behavior in vivo. A combination of two hypotheses reproduced the in vivo behavior, which led us to propose the first mechanical model for cell size-dependent spindle elongation [1]. The proposed model on spindle elongation was combined with previously proposed models on the migrations of the nucleus [2] and spindle [3], and will be integrated with future studies on other structures, to construct and improve a 4-dimensional cell model for better understanding of the mechanics inside the cell.

[References] 1. Y. Hara & A. Kimura (2009) Cell-size-dependent spindle elongation in the Caenorhabditis elegans early embryo. Curr. Biol., 19: 1549-1554.
2. A. Kimura & S. Onami (2005) Computer simulations and image processing reveal length-dependent pulling force as the primary mechanism for C. elegans male pronuclear migration. Dev. Cell, 8: 765-775.
3. A. Kimura & S. Onami (2007) Local cortical pulling-force repression switches centrosomal centration and posterior displacement in C. elegans. J. Cell Biol., 179: 1347-1354.

Keywords: Caenorhabditis elegans, Mitotic spindle, Cell size, Computer simulation

CAS-MPG Partner Institute for Computational Biology Shanghai Institutes for Biological Sciences

Visual Analysis Tools for Multivariate Image Data

Abstract: Traditional immunofluorescence microscopy techniques recently have been extended to colocalize, i.e. to simultaneously label and image, a large number of proteins. The Toponome Imaging system (MELC/TIS) by Walter Schubert makes is possible to colocalize up to 100 and more proteins in a single fixed probe, aiming at gaining new insights into complex protein-protein functional networks (Schubert et al., Nature Biotechnology, Vol 24, 2006) . The challenge for analyzing the resulting multivariate image data sets lies in making both, the contained spatial information as well as the high-dimensional protein abundance data, readable to biological and medical experts in an interlinked and yet comprehensive way. For this purpose we demonstrate the efficiency of our visualization software tool Lasagne, which provides an interactive, real-time navigation through one or multiple data sets. It allows for a fast overview of the data, an in-depth annotation of histological features as well as a comparison of data sets. Data sets shown include MELC/TIS images of human tissue sections affected by the Psoriasis skin disease, and we also demonstrate the application of the Lasagne tool to other imaging techniques like spatially resolved FT-IR microspectroscopy.

2nd round CMCI sumposium after June 30th (Tue). The aim of this non-formal symposium is to share knowledge and techniques for measuring biological system using images, through talks given by EMBL researchers. Most of all, the biggest opportunity is that you could get to know who is doing what type of analysis. Similar symposium held three years ago was a big success that flourished interactions among those who attended, to solve one's own individual problem.

Single Particle Classification in IMAGIC5

Looking at the fractal nature of chromatin using live cell imaging

Segmenting and Modelling cells using Level Set methods

Automatic identification and clustering of chromosome phenotypes in large scale screens by time-lapse microscopy

Microscopy Autopilot for automatic secondary screens and data workflow

Markerless alignment of Cryo-EM tilt series using graphics card computation.

HCI, IWR, University of Heidelberg

3D Image Segmentation for Neural Circuit Reconstruction

Abstract: Serial Block Face Scanning Electron Microscopy (SBFSEM) has facilitated the 3D imaging of nervous systems at an isotropic resolution of 25 nm per voxel. Using SBFSEM, all neurites within a sample are imaged simultaneously and samples as large as an entire neocortical column can be processed. In order to automatically reconstruct the wiring diagram of a nervous system from an SBFSEM volume image, accurate 3D image segmentation is required. Established algorithms fail to provide the required accuracy. A new method developed at the Heidelberg Collaboratory for Image Processing goes beyond these algorithms by incorporating the non-local structure found in the volume image into the segmentation procedure. Moreover, segmentation criteria are not hand-crafted into the algorithm but are learned from a small subset of the data which was carefully traced by neuroscientists. Segmentation is finally cast into a global optimization problem which combines non-local image features with descriptors of the local image geometry. This method doubles the performance of a previous approach which did not use global optimization. The accuracy is not yet sufficient to allow for an automated analysis of synaptic connectivity. However, the 3D reconstructions provide insight into the geometry of nervous systems and serve as a starting point for semi-automatic procedures. References

[1] K. L. Briggman and W. Denk, “Towards neural circuit reconstruction with volume electron microscopy techniques,” Current Opinion in Neurobiology, vol. 16, no. 5, pp. 562–570, November 2006.

[2] W. Denk and H. Horstmann, “Serial block-face scanning electron microscopy to reconstruct three-dimensional tissue nanostructure,” PLoS Biology, vol. 2, pp. 1900–1909, November 2004.

[3] B. Andres, U. Koethe, M. Helmstaedter, W. Denk, and F. A. Hamprecht, “Segmentation of SBFSEM volume data of neural tissue by hierarchical classification,” in Pattern Recognition, ser. LNCS, G. Rigoll, Ed., vol. 5096. Springer, 2008, pp. 142–152.

see –> Link for what he is working on.

In most cases, imaging software alone is not a complete solution for your research. One needs to input your own idea to analyze. For all those who are interested in, please join one day symposium on image processing and analysis which will be held on June 30th (Tue). The aim of this non-formal symposium is to share knowledge and techniques for measuring biological system using images, through talks given by EMBL researchers. Most of all, the biggest opportunity is that you could get to know who is doing what type of analysis. Similar symposium held three years ago was a big success that flourished interactions among those who attended, to solve one's own individual problem.

Automated analysis and reconstruction of the lateral line primordium in zebrafish

3D Segmentation of SPIM/DSLM Images and Multiple-View Fusion in Object Parameter Space

From Light Microscopy to Supramolecular Organization: bridging the gap.

Ways to automate the analysis of in vitro motility assays

Detection and quantitative analysis of membranes and microtubules in fission yeast

Quantitative analysis of actin-driven chromosome transport in starfish oocytes

Automated High-Throughput Image Analysis with CellProfiler

Characterization of gene function by quantitative cellular descriptors and RNA interference

Segmentation of Saccharomyces cerevisiae images for automated microscopy

Institute of Neuroinformatics, ETH Zurich

Neuroanatomy of Drosophila brain: from confocal to serial section electron microscopy

see –> Link for what he is working on.

… associated workshop on Feb 4th: Working on FIJI, an ImageJ package (see Fiji website)

Department of Electrical & Computer Engineering, FAMU-FSU College of Engineering, Florida State University

Pattern Analysis and Visualization in Computer-Aided Diagnosis:Cross-Fertilization between Biomedical Imaging and Engineering

Abstract: Technical innovations in medical cross-sectional imaging have opened up new vistas for the exploration of the human body, enabling both high spatial and temporal resolution. However, these techniques have led to vast amounts of image data whose precise and reliable visual analysis by medical doctors and bioscientists requires a considerable amount of human intervention and expertise, thus resulting in a cost factor of substantial economic relevance. Hence, the computer-assisted analysis of medical image data has moved into the focus of interest as an issue of high priority research efforts. The talk covers novel methods for pattern analysis, visualization and computer-aided diagnosis in the field of biomedical imaging, specifically MRI, such as functional MRI for human brain mapping, dynamic cerebral contrast-enhanced perfusion MRI and new approaches to breast cancer diagnosis in MRI mammography. An outlook to topical projects in systems biology confirms the broad applicability of the presented methods.

Anke Meyer-Baese is author of “Pattern Recognition for Medical Imaging” (2003).

Professor of Biological Sciences, Biomedical , Engineering, and Machine Learning, Director, Ray and Stephanie Lane , Center for Computational Biology, Carnegie Mellon University

Automated Determination and Modeling of Subcellular Location for Systems Biology
see –> Link

Spatial Regulation of Microtubule Dynamics in Fission Yeast

Christian Tischer 1, Damian Brunner 2, and Marileen Dogterom 1

1. FOM Institute for Atomic and Molecular Physics (AMOLF), Kruislaan 407, 1098 SJ Amsterdam, The Netherlands
2. European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany

Microtubules are protein polymers that form an integral part of functional cytoskeletal networks inside eukaryotic cells. Specific microtubule networks are central to the organization of the intracellular space and they are involved in the control of cell morphology. To understand how microtubules fulfill these functions it is important to understand how the lengths of microtubules are adapted to cell size and shape. In fact, individual microtubules typically have no fixed length but constantly switch between a growing and a shrinking state in a process termed dynamic instability. One of the keys to better understand microtubule function is to investigate how the rates that govern microtubule dynamics are regulated inside cells.
In interphase fission yeast (S. Pombe) cells, microtubule catastrophes occur preferentially at the distal ends of elongating cells, but the mechanism by which this spatial selectivity is obtained is not yet understood. We developed automated image analysis procedures to measure microtubule catastrophe rates with unprecedented statistics and at high spatial resolution. We find that: (i) pushing forces generated by growing microtubules induce catastrophes specifically at the cell poles; and (ii) long microtubules undergo catastrophes more often than short ones. Moreover, we show that the microtubule destabilizing motor proteins Klp5/Klp6 enhances the catastrophe rate in a spatially selective way.

EMBL Heidleberg

Image processing using Matlab: Applications in particle and cell detection

EMBL Heidelberg

Measurement and Evaluation of Cell Migration: Part I

Dept. of Imaging Science, National Institute of Basic Biology, Okazaki

Symmetry break in mammalian development: Left-right determination

references:
Randomization of left-right asymmetry due to loss of nodal cilia generating leftward flow of extraembryonic fluid in mice lacking KIF3B motor protein.
Nonaka et al.
Cell. 1998;95:829–837. Link

Determination of left–right patterning of the mouse embryo by artificial nodal flow
Nonaka et al.
Nature 418, 96-99 (4 July 2002) Link

De Novo Formation of Left–Right Asymmetry by Posterior Tilt of Nodal Cilia
Nonaka et al.
PLoS Biol. 2005 August; 3(8): e268. Link

Department of Chemistry, New York University

Colorful Chemical Genetics

Abstract: With the successful result of Human Genome Project, we are facing the problem of handling numerous target genes whose functions remain to be studied. In chemical genetics, instead of using gene knock-out or overexpression as in conventional genetics, a small molecule library is used to disclose a novel phenotype, eventually for the study of gene function. The most serious bottleneck of modern chemical genetics is target identification. To surrogate the currently popular affinity matrix technique, our group has developed fluorescence libraries for a visualization of the biological events. High throughput strategy using colorful chemical genetics will open the efficient road to chemical genomics and proteomics.

See Young-Tae Chang lab URL –> Link

Department of Biomedical Optics, Max-Planck-Institute for Medical Research
Imaging odor responses in zebrafish forebrain by using two-photon microscopy

Marco Marcello recommended him for giving a talk at the CMCI seminar. The way he analyzes image data is very interesting. See Yaksi & Friedrich (2006) Nature Method 3: 377 (–> Link)

Prof. Ralf Schnabel (Technical University of Braunschweig)
SIMIBiocell a software to evaluate 4D-microscopic records: documentation of development, cell behavior, gene expression and bioinformatical analyses (–> Link)

Antje Fischer @ Arendt lab has interest in this software for tracking of cell lineages.4D sequences are manually tracked and their lineage are documented simultaneously to the pre-defined “template”lineage tree.

Software presented at the Computational Cell Biology Meeting, 6-9 Mar 2007

Regulation of intercellular junctions by nanopatterned adhesive interfaces

An extended CMCI seminar by five members of Centre of Mathematical Morphology (CMM) in the Paris Schools of Mines and two talks by EMBL staffs(see below). The seminar will be shown in EBI as well, by live video conference.

CMCI + Mitocheck, EMBL
Image Analysis and data mining in a genome wide RNAi screen by time lapse imaging in order to identify mitotic genes
Abstract

Centre of Mathematical Morphology, Ecole des Mines de Paris
Presentation of the Centre of Mathematical Morphology
Abstract

Centre of Mathematical Morphology, Ecole des Mines de Paris
Presentation of the Centre of Computational Biology

Centre of Mathematical Morphology, Ecole des Mines de Paris
Kernel methods for bioinformatics and vision
Abstract

Strunctural & Computational Biology Unit, EMBL
Image processing in electron microscopy

Centre of Mathematical Morphology, Ecole des Mines de Paris
Morphological-based robust segmentation of cell assays in HCS
Abstract

Centre of Mathematical Morphology, Ecole des Mines de Paris
A package for statistical analysis and modelling of cell array data.
Abstract

Centre of Mathematical Morphology, Ecole des Mines de Paris
Ontology-based lymphocyte population description using mathematical morphology on colour blood images
Abstract

MPI Cell Biology and Biophysics, Dresden

What is the basis of erythrocyte morphology? From 3D image to membrane mechanics

DFKZ, Heidleberg

Analysis of FRAP experiments in the context of chromatin interacting proteins

Imaging and analyzing microtubule dynamic instability in 3D

• 3D spherical mapping centering at the centrosme to initialize the position of microtubules
  • phi vs theta density map at certain radius→ background correction, waterhed, then detect centers of the hot spot
• filament tracing in 3D, especially the tip detection is difficult but the key point:
  • end point determination by standarfd deviation of the 2D plane normal to the filament long axis.
• Output coodrinates were fitted with 3rd-order polynominal. Analyzed for dynamic instability, mechanical properties
• written in Matlab

Cells under confined geometry

• substrate patterning to control the cell shape –> averaging of the signal distribution is possible
• method developed for long term observation under high serum condition
• Analysis:
  • Golgi positioning, distance from the nucleus during steady state.
  • Goligi positioning during migraiton: Front or Back? Nucleus, Golgi tracking
  • Correlation between Protrusion and Retraction: cell edge tracking
• image analysis done using ImageJ.

Tomography of cells - method and software

• IMOD, the software specially fit for microtubule imaging.
• General introcuction to tomography

Image analysis of tubulin oligomers

• Ontogeny of single microtubule filament: create model and verify using static images
  • static image of tubulin solution contains tubulin oligomers with different size.
  • size distribution enables evaluation of models.
  • size distribution measured using ImageJ native function 'particle counting'

3D image-based modeling and analysis of cellular structure

• uses AMIRA and Visualizaiton Tool Kit
  
• topic 1: Computer Aided Surgery Planning (CASP)
  
• topic 2: 3D genome project: registration of intraceuular structure is a challenge.
  
  • would it be possible to “Normalize” certain struncture in cell biology?
    
• topic 3: Cell Mechanics: Fibroblast Stretching
  
  • use FEM for modeling stretch-induced cell shape changes.
    

Conference Report: ImageJ meeting @ Luxemburg

• conference official web site
  
• conference program
  

1. Two Useful PlugIns introduced.
   
   1. Image5D & Sync_windows Plugin by Joachim Walter.
      
   2. Excellent for processing and checking 3D-time lapse with multiple channels.
      
2. MRI Visual Scripting Plugin by Volker Baecker
   
   1. Menu commands can be composed as scripts with flow control statements.
      
   2. This sounds like a macro, but can be more easily done by graphical user interface + drag & drop.
      

Morphometry and Algorithms: Categorization of spindle shapes by fuzzy logic

1. Task of the reaserach is to develop methods for a drug screening.
   1. Find out the population ratio of cells with anomalous spindle shapes.
2. Introductory explanation for the Fuzzy logic was given.
   1. Fuzzy logic uses linguistic variables for both input values and output values to conclude a decision which seemingly is fuzzy for drawing a conclusion with classic binary logic. The spindle shape & patterns are various and complex - fuzzy.
      
   2. For this reason, fuzzy logic was used. Spindle shape and patterns where successfully categorized using the morphometric parameters such as area, convex-hull, orientation, orientation matching, distance between spindle pair.

Introduction

- Role and funciton of CMCI
- Image Processing / Analysis is becoming an inevitable tool for biology.

Re-defining Organelle

- Organelle –> Protein dynamics (Convensional: static)
- Protein Dynamics –> Organelle (novel approach: dynamic)
- Probability distribution function rather than segmentation.

Intracellular Protein Movement: Automatic Tracking

- Tracking of Microtubule associated protein EB1, EB3
- Thresholding to segment particles.
- Measure the position of particles.
- Link particles positions in the time series: minimizing the function “Phai” to serch for the candidate.
- generate an evaluation matrix: similar to the graph theory based approach by Danuser group
- mistakes: only 3 %, evaluated by Lucia
- Combination of IgorPro and ImageJ

Image processing of fluorescence microscopy data on a large scale with Python: FLIM and SPIM data

- Merits of Python:

• easy scripting, but also a true programming language
  
• extendible with C/C++
  
• strong user community
  
• well documented
  
• good support for numerical computations
  

- Screening using FLIM:

• large data sets (~30GB)
  
• screen around 500 clones with FLIM
  
• data analysis with Python takes a few hours on Power Mac
  

- Deconvolution of large 3D SPIM data:

• custom deconvolution softeware written in Python
  
• splitting large image data (5Gb~) into parts
  
• calculation using EMBL cluster
  

Cytoskeletal Dynamics: Fitting and modeling cellular contractility
- Mechanics of contraction after laser nanosurgery
- Contraction kinetics derived by kymograph and detecting the tip position (2D→ 1D)
- edge detection → Vertical derivative + Gaussian fitting along space axis of the kymograph to track the tip.
- contraction kinetics fitted with double-exponential equation.
- Molecular candidates of intracellular stress sensing
- Modelling: various type of elastic contraction and resulting simulated kymographs.
- Exploring parameter space with different spring constant combinations.
- MatLab, IgorPro, ImageJ

Mechanics and dynamics of microtubules studied with video-microscopy single-particle tracking: theoretical and technical aspects

Measurement of fluctuation of beads attached to single microtubule filament
- 3D movement tracked. Z-axis –> defocusing method.
- IgorPro was used for tracking. For 2D, recently published ImageJ plug-in is better (Link).
- Data Processing in MatLab
- Estimation of the mechanical properties of microtubule, sliding distance between subunits.
- Power spectrum of fluctuation without Foulier Transform

Analyzing Aster Length in Xenopus Egg Extracts: Algorithms for tracking fibres

- Morphometry of aster shapes.
- Francois Nedelec's MatLab program –> radial intensity distribution
- Optimization for measureing asymmetrically shaped asters.
- Further development for tracking fibres.

FRAP curves: models and analysis
- FRAP analysis program written in IgorPro (Link).
- Single exponential, Double exponential, and two diffusion dominant models are reday for curve fitting.

Anisotropic Diffusion filtering applied to live-cell imaging
- theoretical background
- Isotropic diffusion ↔ Anisotrapic diffusion (bounded by Edge stopping function).
- Edge-stopping funciton, using gradient of the image.
- Comparison of different iterations appied to microtubule images.
- Anisotropic diffusion filtering is available in ImageJ (Link).

Extracting Shape Parameters: Automatic quantification of angiogenesis
- Application to angiographies of the CAM of chicken embryos
- Geodesic distance based approach .. find the local maximum for the distance from radial center.

• looping problem
  

- Automatic measurement of following parameters:

• No. of bifurcations
  
• Number of Crossings
  
• Branch Length / Vessel Length