1. Multi-Agent Based Modeling and Simulation of Stem Cell Behaviour
BIOMABS – Biomedical Multi-Agent Based Simulation
April, 2007

2. Outline Motivation The Research Hypothesis The Objectives
The Problem Description
The Research Hypothesis
The Objectives
The Expected Contributions
The Methodology
On Going Work
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3. Motivation How do stem cells behave in the human body?
How to predict about how and why stem cells behave either individually or collectively?
formal models
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4. Motivation Medicine point of view Software engineering
The model serves as a reference, a guide for interpreting experimental results
The models serves as a powerful means of suggesting new hypotheses
The simulation lets us test experimentally unfeasible scenarios and can potentially reduce experimental costs
Software engineering
How can we model such a large and complex system?
How to minimize the complexity of the design and implementation of simulation ?
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5. Motivation
Agent-Oriented Software Engineering (AOSE) and Multi-Agent-Based Simulation (MABS) provides the best of both worlds:
clean design in the modeling phase
efficient numerical routines in the simulation phase.
Current Drawback
Model’s semantics
Model and program reuse is limited
Such dynamic structures can be intuitively represented and efficiently implemented in agent-oriented simulators.
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6. The Problem Description: Definition of Stem Cells
Stem cells are:
a potentially heterogeneous population of functionally undifferentiated cells,
composed of multi-cellular organisms.
capable of:
homing to an appropriate growth heterogeneous environment;
proliferation;
production of a large number of differentiated progeny;
self-renewing or self-maintaining their population;
regenerating the functional tissue after injury with
flexibility and reversibility in the use of these options.
- Stem Cell Definitions from Wikipedia. accessed in March 2007.
- M. Loeffler and I. Roeder. Cells Tissues Organs, 171(1):8-26, 2002.
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7. The Problem Description: Simulating Stem Cells - Motivation
Self-organizing system: The way to understand how stem cells organize themselves
Emergent global behavior
The agent-based simulation
suggests how tiny changes in individual stem cell behavior might lead to disease at the global
allows temporal analysis
reduce costs and risks
avoid ethical issues
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8. The Problem Description: The niche – Stem Cells Environment
a specialized cellular environment
provides stem cells with the support needed for self-renewal
contains the cells and proteins that constitute the extra cellular environment
The niche has regulatory mechanisms:
It saves stem cells from depletion
It protects the host from over-exuberant stem-cell proliferation
David T. Scadden. The stem-cell niche as an entity of action.
Nature 441, (29 June 2006) | doi: /nature04957; Published online 28 June 2006.
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9. Niche Example: The Epithelial Stem Cell Niche in Skin
Illustration of the epidermal stem cells. Stem cells are located in the bulge region of the hair follicle
beneath the sebaceous gland. Upon activation, stem cells undergo division; the daughter cells retained in
the bulge remain as stem cells while other daughter cells migrate down to become hair-matrix
progenitors responsible for hair regeneration. In neonatal mice or in damaged skin, stem cells can also
migrate upward and convert to epidermal progenitors that replenish lost or damaged epidermis. The
bulge area is an environment that restricts cell growth and differentiation by expressing Wnt inhibitors,
including DKK,Wif, and sFRP as well as BMPs. During the early anagen phase, Wnts from dermal
papilla (DP) and Noggin, which is derived from both DP and bulge (J. Zhang & L. Li, unpublished data),
coordinate to overcome the restriction signals imposed by both BMPs and Wnt inhibitors; this leads to
stem cell activation and subsequent hair regeneration. The FGF and Notch pathways are also involved in
DP function for hair-matrix cell proliferation and lineage fate determination, but their in.uence on
stem cells is not clear.
Annu. Rev. Cell Dev. Biol : Downloaded from arjournals.annualreviews.org
by CAPES on 04/11/07. For personal use only.
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10. Stem Cells
To ensure self-renewal, stem cells undergo two types of cell division:
Symmetric division
Asymmetric division
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11. The Problem Description: Stem cell division and differentiation
Self-renew
Niche
A - stem cell;
B - progenitor cell;
C - differentiated cell;
1 - symmetric stem cell division;
2 - asymmetric stem cell division;
3 - progenitor division;
4 - terminal differentiation
Limited Self-renew
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12. The Research Hypothesis
The multi-agent system approach is appropriated for the modeling and simulation of stem cell behavior
The multi-agent system approach is more suitable for the modeling of stem cell behavior then
Mathematical models (ODE)
Cellular automata
Petri nets
Other agent-based related works that uses formal methods
And MAS allows
functional view on stem cell population as self-organising systems, necessary to
describe plasticity* and flexibility observed in experimental work
*plasticity phenomena: capacity to change tissue-specific differentiation program
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13. The Research Hypothesis+ +
Main Organization
Multi-Agent System
Environment
agent
Main Irganization
object
Sub-Organization
Agent Role
Object Role
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14. Objectives
To build an agent-based stem cells model in which current and new theories of stem cell behaviour can be modelled.
To investigate appropriated frameworks to run the stem cells simulation.
To investigate how to better present the simulation results and process to the users/physicians
To compare the agent-based results with the Petri nets approache (at the first moment)
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15. The Expected Contributions
Medicine point of view
A tool that allows the understanding of how the behaviour of a system of stem cells is related to the local cell-cell and cell-environment interactions.
A first step in order to
challenge current modes of conceptualising stem cell behaviour.
predict properties of systems of stem cells that can be tested experimental that will provide insights into what behaviour is happening at the cellular level
Agent-Oriented Software Engineering point of view
To provide:
Methods and techniques for modeling stem cell behavior
a framework for the stem cells simulation
To illustrate the advantages of using agent-oriented software engineering instead of other technique
Better understanding of the process of self-organisation multi-agent systems
HCI – Human-Computer Interaction point of view
To identify appropriated ways to present the results
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16. The Methodology Work Team Mini-workshops PUC-Rio, LES
Prof. Carlos Lucena
Maíra Gatti
José Eurico
Renato Raposo
UFRJ, LANDIC – Cellular Differentiation and Neurogenesis Lab
Prof. Stevens Rehen
4 Students
1 PhD. student, 3 Ms. student, 1 undergraduate student
Mini-workshops
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17. The Methodology Iteratively LES Team + LANDIC Team Domain Analysis
Modeling
Simulation
Results Analysis
LES Team
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18. The Methodology First Phase Second Phase Third Phase Domain Analysis
Cell Life-cycle
Stem cell process
Self-renew
Differentiation
Modeling
MAS-ML
Petri nets
Simulation
Jade
Java
Agent-based Simulation FW evaluation
Second Phase
Domain Analysis
Refine the Stem Cell
process
Differentiation
problem
Modeling
MAS-ML
Petri nets
Simulation ??
Java
Third Phase
Comparisons
Advantages
Disadvantages
Papers
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19. On Going Work  First Phase Second Phase Third Phase Domain Analysis
Cell Life-cycle
Stem cell process
Self-renew
Differentiation
Modeling
MAS-ML
Petri nets
Simulation
Jade
Java
Agent-based Simulation FW evaluation
July 03
July 31
June 05
Second Phase
Domain Analysis
Refine the Stem Cell
process
Differentiation
problem
Modeling
MAS-ML
Petri nets
Simulation ??
Java
Third Phase
Comparisons
Advantages
Disadvantages
Papers 
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20. The Cell Lyfecicle
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21. MAS-ML Modeling Structural Elements Static Diagram Dynamic Diagram
Environment
Main Organization: Niche
Organizations: Cell, StemCell, ProgenitorCell, DifferentiatedCell, Centrosome
Agents: Chromatin, Chromosome, Microtubules
Objects: CellMembrane, NuclearMembrane, Nuclei, Chromatids, Centriole, Substances, Protein, Organelles, CellsStructures, Centromere, Kinetochore, MolecularMotorProtein
Static Diagram
Organization Diagram
Role Diagram
Agent Diagram*
Class Diagram
Dependence Diagram** (Tropos)
Dynamic Diagram
Sequence Diagram
Agent interactions
Goals, plans and actions
Activity Diagram
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22. Organization Diagram Environment Cell StemCell DifferentiatedCell
<<main-organization>>
Niche
<<organization>>
StemCell
Cell
Centrosome
ProgenitorCell
<<organization>>
Cell
<<organization>>
<<organization>>
ProgenitorCell
Centrosome
Object role
Agent role
Object / Environment
Agent
Organization
Legend:
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23. Organization Diagram Environment Chromosome Chromatin Chromatin
<<agent>>
Chromosome
Chromatin
Chromatin
<<organization>>
<<agent>>
Chromosome
Cell
Microtubule
NuclearMembrane
CellMembrane
NuclearMembrane
<<agent>>
CellMembrane
Microtubule
Object role
Agent role
Object / Environment
Agent
Organization
Legend:
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24. <main-organization>
Niche
<main-organization>
<<goal>> boolean : regulateStemCellDifferentiation = true  regulatingCellsNumber
<<belief>> Ontology : ontology
<<belief>> String :type
<<belief>> int : id
<<belief>> Collection : cells = null
<<belief>> int: bestCellsNumber = 0
<<belief>> int: time
{} preventFromDepletion {}
{} preventFromOverExuberantStemCellProliferation {}
{} acceptCell {}
regulatingCellsNumber { preventFromDepletion, preventFromOverExuberantStemCellProliferation }  regulateStemCellDifferentiation
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25. <organization>
Cell
<organization>
<<goal>> boolean : metabolize = true {
<<sub-goal>> boolean : accomplishInterphaseG1 = true  runningInterphaseG1
<<sub-goal>> boolean : accomplishInterphaseS = true  runningInterphaseS
<<sub-goal>> boolean : accomplishInterphaseG2 = true  runningInterphaseG2
<<sub-goal>> boolean : accomplishProphase = true  runningProphase
<<sub-goal>> boolean : accomplishPrometaphase = true  runningPrometaphase
<<sub-goal>> boolean : accomplishMetaphase = true  runningMetaphase
<<sub-goal>> boolean : accomplishAnaphase = true  runningAnaphase
<<sub-goal>> boolean : accomplishTelophase = true  runningTelophase }
<<belief>> Status : status
<<belief>> int : maturityPromoterFactor #MPF
<<belief>> int : selfRenewPotentialy
<<belief>> int : differentiationPotentialy
<<belief>> Collection<Substance> : substances
{} synthesizeSubstances {}
{} increaseCellMetabolicRate {}
{} startChromatidReplication {}
{} finishChromatidReplication {}
{} replicateCentrosome {}
{} condenseChromatin {}
{} createRepulsiveForces {}
{} disassembleNuclearMembrane {}
{} increaseMPF {}
{} executeControlCheckpoint {}
runningInterphaseG1 {synthesizeSubstances, increaseCellMetabolicRate } accomplishInterphaseG1
runningInterphaseS {startChromatidReplication, replicateCentrosome }  accomplishInterphaseS
runningInterphaseG2 {finishChromatidReplication }  accomplishInterphaseG2
runningProphase { condenseChromatin, createRepulsiveForces, disolveNuclearMembrane, increaseMPF, executeControlCheckpoint }  accomplishProphase
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26. Class Diagram Environment Chromatid CellStructure Substance Centromere
Organelle
Protein
Kinetochore
MolecularMotorProtein
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27. Role Diagram Environment Cell Chromosome Centrosome Chromatin 1
CellMembrane *
Substance
Cell
Chromosome 2
Chromatid
Nuclei
Centrosome
NuclearMembrane
Chromatin 2
Centriole *
MolecularMotorProtein
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28. References
M. d’Inverno, and J. Prophet. Modelling, simulation and visualisation of adult stem cells. In P. Gonzalez, E. Merelli, and A. Omicini, editors, Fourth International Workshop on Network Tools and Applications, NETTAB, pages 105–116, 2004.
M. d’Inverno and R. Saunders. Agent-based modelling of stem cell organisation in a niche. In Engineering Self-Organising Systems, volume 3464 of LNAI. Springer, 2005.
M. d’Inverno, N. D. Theise, and J. Prophet. Mathematical modelling of stem cells: a complexity primer for the stem cell biologist. In Christopher Potten, Jim Watson, Robert Clarke, and Andrew Renehan, editors, Tissue Stem Cells: Biology and Applications. Marcel Dekker, 2005.
Instituto Virtual de Células-Tronco.
Project: Modelling and Simulating the Behaviour of Adult Stem Cells using Agent-Based Systems -
David T. Scadden. The stem-cell niche as an entity of action. Nature 441, (29 June 2006) | doi: /nature04957; Published online 28 June 2006.
Preece, J.;Rogers, Y.; Sharp, H. Design de Interação: Além da interação homem-computador, Porto Alegre, Brasil: Bookman, 2005.
Gatti, M.; Lucena, C. An Agent-Based Approach for Building Biological Systems: Improving The Software Engineering for Complex and Adaptative Multi-Agent Systems. To be published in Monografias de Ciências da Computação, PUC-Rio, Rio de Janeiro, 2007.
Stem Cell Definitions from Wikipedia. accessed in March 2007.
M. Loeffler and I. Roeder. Cells Tissues Organs, 171(1):8-26, 2002.
© LES/PUC-Rio

29. Multi-Agent Based Modeling and Simulation of Stem Cell Behaviour
BIOMABS – Biomedical Multi-Agent Based Simulation
April, 2007