CompuCell Software Current capabilities and Research Plan Rajiv Chaturvedi Jesús A. Izaguirre With Patrick M. Virtue.

Slides:



Advertisements
Similar presentations
Parameterizing a Geometry using the COMSOL Moving Mesh Feature
Advertisements

Active Contours, Level Sets, and Image Segmentation
1 Coven a Framework for High Performance Problem Solving Environments Nathan A. DeBardeleben Walter B. Ligon III Sourabh Pandit Dan C. Stanzione Jr. Parallel.
MotoHawk Training Model-Based Design of Embedded Systems.
MATLAB Presented By: Nathalie Tacconi Presented By: Nathalie Tacconi Originally Prepared By: Sheridan Saint-Michel Originally Prepared By: Sheridan Saint-Michel.
Uncertainty Representation. Gaussian Distribution variance Standard deviation.
Student Mr Daniel Birkett ( ) Course MEng Electronic & Electrical
ProActive Task Manager Component for SEGL Parameter Sweeping Natalia Currle-Linde and Wasseim Alzouabi High Performance Computing Center Stuttgart (HLRS),
Scientific Programming MAIN INPUTINITCOMPUTEOUTPUT SOLVER DERIV FUNC2 TABUL FUNC1 STATIC BLASLAPACKMEMLIB.
Software Testing and Quality Assurance
Evaluation of Fast Electrostatics Algorithms Alice N. Ko and Jesús A. Izaguirre with Thierry Matthey Department of Computer Science and Engineering University.
CSE351/ IT351 Modeling and Simulation
Improving UML Class Diagrams using Design Patterns Semantics Shahar Maoz Work in Progress.
CAD/CAM Design Process and the role of CAD. Design Process Engineering and manufacturing together form largest single economic activity of western civilization.
Modeling Chemotaxis, Cell Adhesion and Cell Sorting. Examples with Dictyostelium Eirikur Pálsson Dept of Biology, Simon Fraser University.
Section 8.3 – Systems of Linear Equations - Determinants Using Determinants to Solve Systems of Equations A determinant is a value that is obtained from.
Knowledge Systems Lab JN 8/24/2015 A Method for Temporal Hand Gesture Recognition Joshua R. New Knowledge Systems Laboratory Jacksonville State University.
Loads Balanced with CQoS Nicole Lemaster, Damian Rouson, Jaideep Ray Sandia National Laboratories Sponsor: DOE CCA Meeting – January 22, 2009.
Intro to CompuCell3D Chris Mueller September 20, 2004.
UNDERSTANDING DYNAMIC BEHAVIOR OF EMBRYONIC STEM CELL MITOSIS Shubham Debnath 1, Bir Bhanu 2 Embryonic stem cells are derived from the inner cell mass.
LESSON 8 Booklet Sections: 12 & 13 Systems Analysis.
1 Validation & Verification Chapter VALIDATION & VERIFICATION Very Difficult Very Important Conceptually distinct, but performed simultaneously.
Deformable Models Segmentation methods until now (no knowledge of shape: Thresholding Edge based Region based Deformable models Knowledge of the shape.
An Introduction to Software Architecture
An Introduction to Design Patterns. Introduction Promote reuse. Use the experiences of software developers. A shared library/lingo used by developers.
Computer Concepts 2014 Chapter 12 Computer Programming.
Phase diagram calculation based on cluster expansion and Monte Carlo methods Wei LI 05/07/2007.
Software Development Cycle What is Software? Instructions (computer programs) that when executed provide desired function and performance Data structures.
CompuCell3D: A Morphogenesis simulation package
Lecture 7: Requirements Engineering
Chapter 12 Computer Programming. Chapter Contents Chapter 12: Computer Programming 2  Section A: Programming Basics  Section B: Procedural Programming.
Sketch Outline Ising, bio-LGCA and bio-Potts models Potts model general description computational description Examples of ‘energies’ (specifying interactions)
Modeling Morphogenesis in Multi-Cellular Systems (Complex Systems Project) Heather Koyuk Spring 2005 Other Team Members CS Student: Nick Armstrong Chemistry.
_______________________________________________________________CMAQ Libraries and Utilities ___________________________________________________Community.
OBJECT-ORIENTED PROGRAMMING (OOP) WITH C++ Instructor: Dr. Hany H. Ammar Dept. of Electrical and Computer Engineering, WVU.
1 P. David, V. Idasiak, F. Kratz P. David, V. Idasiak, F. Kratz Laboratoire Vision et Robotique, UPRES EA 2078 ENSI de Bourges - Université d'Orléans 10.
Post-Processing Output with MATLAB Claudia Fricke Institute of Petroleum Engineering, Heriot Watt University.
Solution of a Partial Differential Equations using the Method of Lines
Framework for MDO Studies Amitay Isaacs Center for Aerospace System Design and Engineering IIT Bombay.
AS-RIGID-AS-POSSIBLE SHAPE MANIPULATION
Finite Element Analysis
1 Circuitscape Design Review Presentation Team Circuitscape Mike Schulte Sean Collins Katie Rankin Carl Reniker.
Implementing Hypre- AMG in NIMROD via PETSc S. Vadlamani- Tech X S. Kruger- Tech X T. Manteuffel- CU APPM S. McCormick- CU APPM Funding: DE-FG02-07ER84730.
Domain Decomposition in High-Level Parallelizaton of PDE codes Xing Cai University of Oslo.
GCSE ICT Systems Analysis. Systems analysis Systems analysis is the application of analytical processes to the planning, design and implementation of.
SOFTWARE DESIGN AND ARCHITECTURE LECTURE 31. Review Creational Design Patterns – Singleton Pattern – Builder Pattern.
Software Engineering1  Verification: The software should conform to its specification  Validation: The software should do what the user really requires.
00/XXXX 1 Data Processing in PRISM Introduction. COCO (CDMS Overloaded for CF Objects) What is it. Why is COCO written in Python. Implementation Data Operations.
using Radial Basis Function Interpolation
Model validity, testing and analysis. Conceptual and Philosophical Foundations Model Validity and Types of Models –Statistical Forecasting models (black.
1 Circuitscape Capstone Presentation Team Circuitscape Katie Rankin Mike Schulte Carl Reniker Sean Collins.
Collaboration with Craig Henriquez’ laboratory at Duke University Multi-scale Electro- physiological Modeling.
Active Walker Model for Bacterial Colonies: Pattern Formation and Growth Competition Shane Stafford Yan Li.
Nonlinear balanced model residualization via neural networks Juergen Hahn.
Banaras Hindu University. A Course on Software Reuse by Design Patterns and Frameworks.
Computer-Aided Design
Xing Cai University of Oslo
Status of QLASA Tool Adapter
current PicUp capabilities and expected performance from SPIS
Introduction to Design Patterns
Software for scientific calculations
PreOpenSeesPost: a Generic Interface for OpenSees
FRED A software tool for modern optical engineering
Computer Programming.
A Computational Model of Chemotaxis-Based Cell Aggregation
TOPIC: Computer-Aided Design
MECH 3550 : Simulation & Visualization
Ph.D. Thesis Numerical Solution of PDEs and Their Object-oriented Parallel Implementations Xing Cai October 26, 1998.
Overview Activities from additional UP disciplines are needed to bring a system into being Implementation Testing Deployment Configuration and change management.
Hydrology Modeling in Alaska: Modeling Overview
Presentation transcript:

CompuCell Software Current capabilities and Research Plan Rajiv Chaturvedi Jesús A. Izaguirre With Patrick M. Virtue

Objective u Introduction to integrated Potts model simulation and visualization package called CompuCell u Show simulation results (application to macrophage and bacteria movement) u Present a Research and Development plan to n Model chicken limb growth n Model Integration (Potts and Reaction Diffusion)

Talk Outline u Preliminary results: n Current model and software capabilities n Macrophage simulation results u Research and Development plan n Modeling l Cell condensation in 2D l Chicken limb bud in 2D l R-D integration l (Flock modeling) n Software l Integration of other models (eg., Reaction Diffusion) l GUI designed for generality l 3-d simulation an dvisualization

Movie from experiments

Problem schematic Macrophage and bacterium wbc bacterium Periodic boundary conditions on square lattice Gradient fields in medium Linear field from left to right Radial field originating from bacteria Update field after each move

Results: Model Description u Hamiltonians: n Volume n Surface n Interaction n Chemotaxis u Multiple gradients of chemical field n Linear n Radial distribution of concentration from a source u Field implementation n Current limitation: Field as action at a distance rather than diffusing through lattice

Results: Initial and boundary conditions u SubDomains in software Cells in the model: n Experimented with 2 and 3 cells in the lattice u Boundaries: n The pixels of the changing bacteria boundary act as source n Periodic boundary conditions on lattice edges

Results: Verification and validation u Verification: n Potts model for multiple fluctuating cells without chemotaxis Hamiltonian n Potts model for moving cells with linear gradient u Validation n Qualitative studies (visual inspection) for patterns formed and those observed

(Show animated gif)

Results: Software u Software: n Interactive (integrated with visualization) n Stand-alone u Visualization: n Uses VTK (visualization tool kit) libraries n Movie creation capabilities n Image manipulation: rotate, zoom, section n Visualization done by Patrick Virtue

Results: GUI u Allows user to define initial conditions n Cells of arbitrary shape on a lattice n Visualization properties for cells u Future integration with CompuCell discussed below

Results: Gui u GUI:

Results: Visualization u Visualization 3D hydra burst:

Results: Software extensibility u Object Oriented design: caters for reuse and extensibility by n Hierarchy of classes: General to specific n Abstraction n Encapsulation

Computational engines running multiscale simulations (ellipses) PottsReaction diffusion Data Communication Experimen tal data Computational engine running Analysis Visualization Engine High Level Architecture for Integrated PSE GUI

Results: Software extensibility u Addition of new hamiltonians (at programming level): n Derive new hamiltonian from abstract Hamiltonian class n Encapsulate its data, mimic methods of other Hamiltonians n Total Hamiltonian (a subclass of Hamiltonian) takes care of Energy calculations n In modeling code, create objects of various types of Hamiltonians, add them to TotalHamiltonian object u Addition of new fields: similar u Addition of new boundary conditions

Results: Software u Input: n Command line prompts n File input (and from GUI) n Initial conditions l Lattice l Cells u Positions and sizes n Parameters l Constraints params… u Output: n Runtime visualization n Movies n Post processing mode

Results: cell movement in gradient (Show animated gif)

Talk Outline u Overview: Integrated Problem Solving Environment u Preliminary results: bacteriophage problem n Current model and software capabilities n Bacteriophage simulation results u Research and Development plan n Modeling l Steps to Chicken limb bud l R-D integration n Software l Integration of other models (eg., Reaction Diffusion) l GUI designed for generality l Visualization

Research Plan: Cell Sorting u Problem 0: (Cell sorting in the presence of a gradient)

Research Plan: Condensation u Problem 1: (Cell condensation in the presence of reaction-diffusion)

Research Plan: Limb bud growth u Problem 2: Full of 3D cells No activity in Progress zone Time Progress Zone

Research Plan: Limb bud growth u Problem 1 and 2: K steps of Reaction Diffusion in a lattice Potts model movement, cells as moving sources

R&D plan: Limb bud growth u Model extension needed: l Diffusive gradients l Reaction diffusion equations to solve l Extra cellular matrix characterization (field) l Progress zone characterization (in Potts model) l Set of reasonable initial/boundary conditions, and parameters for Potts model validation l 3 D potts l 3 D RD

R&D plan: Limb bud growth u Software Extension needed/desired: l Front end: u Integration and extension of GUI u Automated tuning of parameters (software detects param ranges where desired behavior is obtained) l Computational backend: u Integration with reaction-diffusion code u Handling multiple grids (hierarchy of grids, interpolation) u Clustering algorithms to detect pattern formation u More efficient solvers (for 3D)

Issue of accuracy u A working definition of “good” simulation for various simulations needs to be defined. n Verification: Solving the model right l Verification against known analytical solutions u (analytical results for statistical variables in stochastic models) l Quantifying accuracy of results against grid size n Validation: Solving the right model: basis of comparing results to experiments

Integrated Problem Solving Environment u Grand aim: The end user must be able to focus on Biology/ Physics problems rather than software/ programming. u Runtime and post processing visualization u Configuration files to specify initial conditions and simulation parameters u Recommender system (to assist user) u GUI to allow for user inputs u Ability to allow user to choose models (in the long run) through a GUI