Java Adaptive Mathematical Modeling Engine (JAMME) - PowerPoint PPT Presentation

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Java Adaptive Mathematical Modeling Engine (JAMME)

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Java Adaptive Mathematical Modeling Engine (JAMME) Leeland Artra, Cell Systems Initiative (CSI) Zheng Li, Department of Bioengineering University of Washington, Seattle – PowerPoint PPT presentation

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Title: Java Adaptive Mathematical Modeling Engine (JAMME)


1
Java Adaptive Mathematical Modeling Engine(JAMME)
  • Leeland Artra, Cell Systems Initiative (CSI)
  • Zheng Li, Department of Bioengineering
  • University of Washington, Seattle

2
Introduction of JAMME
  • Proposed collaborative project between NSR
    (National Simulation Resource for Circulatory
    Mass Transport and Exchange NIH/NCRR) and CSI to
    provide a complete software database
    environment for real time biological modeling.
  • Integration of NSRs JSIM model simulation
    environment with CSIs Moulage System framework,
    Metagraph data representation model, and a new
    object database management system.

3
Background (available software at NSR and CSI)
  • JSIM is an integrative model simulation
    environment being developed at NSR.
  • Moulage is a real time data sharing analysis
    system framework.
  • Metagraph is a code name for a data and process
    representation language used to describe
    structures and methods that capture a
    computerized abstraction of the scientific
    process.
  • The new object database management system being
    developed at CSI. Its primary goal is to provide
    a dynamic data engine that can handle complex
    hyper-graph / XML / Metagraph queries directly.

4
JSIM Design Goals
  • Easy-to-use end-user interface. Low barriers to
    entry of math modelling for biologically-inclined
    users.
  • Facilitate collaborative model development
    (integration)
  • Integration at mathematical level.
  • Integration at component level.
    (Plug-and-play).
  • Connectivity to heterogeneous data sources.
  • Facilitate collaborative software development.
  • Facilitate distributed-computing.
  • Flexibility and Extensibility at all levels
  • math model classes and representations
  • hierarchical component libraries
  • numeric libraries

5
JSIM Architecture
6
Items Needed By JSIM
  • Persistence Engine
  • Intelligent Distributed Analysis Engine
  • Visual Programming Ability
  • Ability to Import Various Modeling Data
  • Ability to Directly Interface With Experiment Data

7
Moulage Design Goals
  • Create a development framework that automatically
    can provide
  • Transparent access
  • Ability to accept multiple data sources
  • Easy sharing of data
  • Data in form usable by object-oriented databases
  • Multiple tools for analysis
  • Dynamic version distribution

8
Moulage Base Components
  • Inspector analysis, application
  • DataObject data
  • IOController IO operations
  • DataObjectManager database
  • Translator file to/from object

Translator
textual data
DataObjectManager
binary data
0111010101
0101011...
DataObject
remote data
4
3
2
1
Analysis / Application (Inspector)
9
JAMME Approach
  • 100 Core Java
  • Any needed classes built directly from on the 1.2
    core
  • Carefully engineered to work within the Java
    Virtual Machine constraints
  • Allow operation as
  • Stand alone application
  • Command line utility (batch processing)
  • Applet (Web and Email integration)

10
Integration Overview
  • Start with JSIM

JSIM
11
Integration Overview - Moulage
  • Enhance by adapting to Moulage

Analysis
JSIM
MML Data
IO
12
Integration Overview - Metagraph
  • Enhance by creating Metagraph Data Structures

Analysis
JSIM
MML Data
IO
13
Integration Overview - ODB
  • Enhance by adding new object database

Analysis
JSIM
IO
IO
14
Integration Overview - ODBMS
  • Enhance by allowing distributed database
    processing of analysis

Analysis
JSIM
IO
IO
ODBMS
Analysis
Analysis
Analysis
15
Integration Overview - Result
  • Resulting in a set of reusable components

JAMME
Analysis
T-Cell Modeling
IO
IO
ODBMS
Analysis
Analysis
Analysis
Query Engine X
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