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This model demonstrates behaviour of the general artificial immune network (GAIN), that was firstly introduced by F. González et al. in 2005.
GAIN is composed of the antigens (red objects, agent Turtle), b-lymphocytes (blue object, agent Turtle) and connections between antigens and b-lymphocytes and between b-lymphocytes (gray link with blue arrow , agent Link).
Step 1.: before running the model, we have to specify count of agents in our simulation. slider nrAntigens and nrBLymphocytes are used for this purpose.
Then we need to set up affinity value for b-lymphocytes in case of recognizing antigens by b-lymphocytes (slider affinityThreshold-Ag) and affinity value for b-lymphocytes in case of mutually recognizing b-lymphocytes (slider affinityThreshold-Ab).
Then we specify stimulation level threshold (sliderstimulationLevelThreshold).
If you want you can change color of the background in the NetLogo model or size of the agents. These properties do not influence stimulation and suppression of the cells.
Step 2.: Then we inicialize model with the aid of SETUP button. Some antigens and b-lymphocytes are created. We have two possibilities for run the model
a) we can use STEP button for run the model step by step (tick by tick): this way is useful for the detailed observation of the simulation
b) we can use GO button: model runs until STOP MODEL button is activated
Step 3.: you can see průběh modelu in the two graphs:
a) first one shows changes in the population of b-lymphocytes
b) second one shows already died b-lymphocytes
Step 4.: In the output-window you can see steps in the running model.
BUTTONS
setup: inicialization of the model (creating antigens and b-lymphocytes)
step: stepping the model
go: start the simulation
stop: stop the model
change the position of the agent:during the stepping the model you can use this button for change a position of the agent
SLIDERS
sizeOfBLymphocytes: size of shape of a b-lymphocyte
sizeOfAntigens: size of shape of an antigen
nrBLymphocytes: count of b-lymphocytes
nrAntigens: count of antigens
affinityThreshold-Ag: affinity threshold value for b-lymphocytes that recognize antigens (it is the sensitivity of b-lymphocyte; what minimal count of values of the comparing lists of agents have to be the same; Hamming distance is used.)
affinityThreshold-Ab: affinity threshold value for b-lymphocytes that recognize other b-lymphocytes (it is the sensitivity of b-lymphocyte; what minimal count of values of the comparing lists of agents have to be the same; Hamming distance is used.)
stimulationLevelThreshold: this slider determine minimal stimulation level threshold that is necessary for stimulation of the b-lymphocyte (proliferation and mutation)
CHOSER
background: changing the color of the background in the NetLogo model
If you use STEP button, you can use it together with the button CHANGE THE POSITION OF THE AGENT. You are able to drag and drop your agent (antigen or b-lymphocyte) on your chosed position in the model. It is useful, if you can not see relations between agents very well.
Lenght of links between agents can be calculated according to the affinity values between them.
NetLogo Models Library contains section NETWORKS that contains some network models, but no one is focused on modelling artificial immune networks. The most related model with the artificial immune networks is the Virus on a network.
Following sources were mainly used for the development of the GAIN model in NetLogo:
1. De Castro, L. N., Timmis, J.: Artificial Immune Systems: A New Computational |Intelligence Approach. Springer, 2002, ISBN 1-85233-594-7.
2. De Castro, L. N.: Immune, Swarm, and evolutionary algorithms. Part I.: Basic |models. ICONIP, 2002. Vol. 3, pp. 1464 – 1468.
3. Dasgupta, D., Nino, L. F.: Immunological Computation: Theory and Applications. CRS |Press, 2009. ISBN 978-1-4200-6545-9.
4. De Castro, L. N.: Fundamentals of natural computing: basic concepts, algorithms, |and applications. 2006. ISBN 1-58488-643-9. Chapman and Hall/CRC.
Web adress of the NetLogo-GAIN: http://www.lide.uhk.cz/fshusam2/lekarnicky/zt3/NetLogo-GAIN-Informatics09.html
Author of the NetLogo-GAIN: Martina Husáková (email: martina.husakova.2@uhk.cz)
Publicated: on the international conference Informatics 2009 in Slovakia - Košice.