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X-Machines for Agent-Based Modeling: FLAME Perspectives
cells navigate the length and complexity of the female reproductive
tract, to reach and fertilize the oocyte, are extremely fascinating and
difficult to study. Numerous complex processes can potentially influence
the movement of spermatozoa within the tract, resulting in a regulated
supply of spermatozoa to the oocytes at the site of fertilization. Despite
significant differences between species, breeds and individuals, these processes converge, ensuring that an optimal number of high quality spermatozoa reach the oocytes, resulting in successful fertilization without a
significant risk of polyspermy. Computational modeling provides a useful method to combine knowledge about the individual processes to help
understand the relative significance of each factor. In this study, the first
agent-based computational model of sperm behavior within an oviductal
environment was created. Firstly, a generic conceptual model of sperm
behavior within the 3D oviduct was presented. Sperms are modeled as
individual cells with a set of behavioral rules defining how they interact
with their local environment and regulate their internal state. Secondly,
a set of 3D models of the mammalian oviduct were constructed. Histology images of the mouse oviduct were obtained and the path that the
oviductal tube follows through the tissue was identified using CUDAbased image analysis (using GPUs). This was used to determine crosssectional topology, and measurements from the cross sections were used
to generate a set of accurately scaled 3D models of the oviduct. The
process of constructing and validating the agent-based computational
model of sperm movement and transport within the oviductal environment was described. The model is grounded in reality, with accurate
space and time scales used throughout, and parameters and mechanisms
from literature where available. Sensitivity analysis was performed on
all parameters, and those most sensitive to variation were identified.
The model was validated against literature, to validate it. However the
model had a few limitations based on the assumptions drawn which were
also presented. The model was used to investigate the significance of the
oviductal environment on the regulation of sperm distribution and their
progression to the site of fertilization. How changes to the the oviduct
environment can alter the sperm distribution was also studied. Finally,
the potential use for the model and how more complex mechanisms could
be integrated in the future were discussed [34].
Blood flow. This work investigated how a specific biological system - heart
cells and tissue - can be studied using computation as a metaphor, and
addressed the question of whether biological behavior can be labelled as
a computation. Clearly, an answer to this question is an ambitious goal
and is yet far off; however, the intent was to take a small step towards it.
As a test-bed, this work aimed to describe and implement a novel computational perspective for modeling cardiac electrophysiology. It aimed
specifically to develop a hybrid, hierarchical, agent-based model of the
X-Machines for Agent-Based Modeling: FLAME Perspectives
cells navigate the length and complexity of the female reproductive
tract, to reach and fertilize the oocyte, are extremely fascinating and
difficult to study. Numerous complex processes can potentially influence
the movement of spermatozoa within the tract, resulting in a regulated
supply of spermatozoa to the oocytes at the site of fertilization. Despite
significant differences between species, breeds and individuals, these processes converge, ensuring that an optimal number of high quality spermatozoa reach the oocytes, resulting in successful fertilization without a
significant risk of polyspermy. Computational modeling provides a useful method to combine knowledge about the individual processes to help
understand the relative significance of each factor. In this study, the first
agent-based computational model of sperm behavior within an oviductal
environment was created. Firstly, a generic conceptual model of sperm
behavior within the 3D oviduct was presented. Sperms are modeled as
individual cells with a set of behavioral rules defining how they interact
with their local environment and regulate their internal state. Secondly,
a set of 3D models of the mammalian oviduct were constructed. Histology images of the mouse oviduct were obtained and the path that the
oviductal tube follows through the tissue was identified using CUDAbased image analysis (using GPUs). This was used to determine crosssectional topology, and measurements from the cross sections were used
to generate a set of accurately scaled 3D models of the oviduct. The
process of constructing and validating the agent-based computational
model of sperm movement and transport within the oviductal environment was described. The model is grounded in reality, with accurate
space and time scales used throughout, and parameters and mechanisms
from literature where available. Sensitivity analysis was performed on
all parameters, and those most sensitive to variation were identified.
The model was validated against literature, to validate it. However the
model had a few limitations based on the assumptions drawn which were
also presented. The model was used to investigate the significance of the
oviductal environment on the regulation of sperm distribution and their
progression to the site of fertilization. How changes to the the oviduct
environment can alter the sperm distribution was also studied. Finally,
the potential use for the model and how more complex mechanisms could
be integrated in the future were discussed [34].
Blood flow. This work investigated how a specific biological system - heart
cells and tissue - can be studied using computation as a metaphor, and
addressed the question of whether biological behavior can be labelled as
a computation. Clearly, an answer to this question is an ambitious goal
and is yet far off; however, the intent was to take a small step towards it.
As a test-bed, this work aimed to describe and implement a novel computational perspective for modeling cardiac electrophysiology. It aimed
specifically to develop a hybrid, hierarchical, agent-based model of the