—Multiscale models that link sub-cellular, cellular and multicellular components offer powerful i... more —Multiscale models that link sub-cellular, cellular and multicellular components offer powerful insights in disease development. Such models need a realistic set of parameters to represent the physical and chemical mechanisms at the sub-cellular and cellular levels to produce high fidelity multicellular outcomes. However, determining correct values for some of the parameters is often difficult and expensive using high-throughput microfluidic approaches. This work presents an alternative approach that estimates cellular parameters from spatiotemporal data produced from bioengineered multicellular in vitro experiments. Specifically, we apply a search technique to an integrated cellular and multicellular model of retinal pigment epithelial (RPE) cells to estimate the binding rate and auto-regulation rate of vascular endothelial growth factor (VEGF). Understanding VEGF regulation is critical in treating age-related macular degeneration and many other diseases. The method successfully identifies realistic values for autoregulatory cellular parameters that reproduce the spatiotemporal in vitro experimental data.
Abstract. Simulated annealing and genetic algorithms represent pow-erful optimization methods wit... more Abstract. Simulated annealing and genetic algorithms represent pow-erful optimization methods with complementary strengths and weak-nesses. Hence, there is an interest in identifying hybrid methods (which combine features of both SA and GA) that exhibit performance superior ...
ABSTRACT The transition in breast cancer from ductal carcinoma in situ to invasive ductal carcino... more ABSTRACT The transition in breast cancer from ductal carcinoma in situ to invasive ductal carcinoma marks a significant drop in patient survival and is one of the leading causes of death in women. This work presents a new 3D model of the breast duct in which the previous 2D duct section model is extended in the lateral dimension to capture the complete duct morphology. The resulting increase in fidelity due to lateral extension is necessary for the discovery of effective interventions since interactions among the duct wall, interstitial fluid and the surrounding stroma are significantly changed. Specifically, the new model can capture the relief of pressure along the duct and the complex morphology of tumor invasion by the breaching of the basement membrane and epithelial tight junction wall. The model represents multiple biochemical and biomechanical interactions among the epithelia, tumor cells, diffusible signals, and stromal components such as fibroblasts, myofibroblasts and extracellular matrix in the ductal microenvironments. Understanding how the interplay among these components drives the dynamics of metastasis and invasion may lead to new therapeutic approaches to breast cancer. We introduced a 3D multicellular agent-based model of DCIS growth and invasion that includes ductal, stromal and tumor cell types acting along with microenvironmental components such as matrix metalloproteinases (MMP), Lysyl oxidase(LOX), nutrients, TGFβ and extracellular matrix (ECM) protein assemblies. We are investigating a wide range of parameters and assumptions in our model that can lead to changes in the model outcomes. The model explicitly determines mechanical tensional and compressive forces within the developing tissue.
In earlier research the Center for Self-Organizing and Intelligent Systems (CSOIS) at Utah State ... more In earlier research the Center for Self-Organizing and Intelligent Systems (CSOIS) at Utah State University (USU) was funded by the US Army Tank-Automotive and Armaments Command's (TACOM) Intelligent Mobility Program to develop and demonstrate enhanced mobility concepts for unmanned ground vehicles (UGVs). As part of our research, we presented the use of a grammar-based approach to enabling intelligent behaviors in autonomous robotic vehicles. With the growth of the number of available resources on the robot, the variety of the generated behaviors and the need for parallel execution of multiple behaviors to achieve reaction also grew. As continuation of our past efforts, in this paper, we discuss the parallel execution of behaviors and the management of utilized resources. In our approach, available resources are wrapped with a layer (termed services) that synchronizes and serializes access to the underlying resources. The controlling agents (called behavior generating agents) generate behaviors to be executed via these services. The agents are prioritized and then, based on their priority and the availability of requested services, the Control Supervisor decides on a winner for the grant of access to services. Though the architecture is applicable to a variety of autonomous vehicles, we discuss its application on T4, a mid-sized autonomous vehicle developed for security applications.
Cell types are defined at the molecular level during embryogenesis by a process called pattern fo... more Cell types are defined at the molecular level during embryogenesis by a process called pattern formation and created by the selective utilization of combinations of sequence specific transcription factors. Developmental programs define the sets of genes that are available to each particular cell type, and real-time biochemical signaling interactions define the extent to which these sets are used at any given time and place. Gene expression is regulated through the integrated action of many cis-regulatory elements, including core promoters, enhancers, silencers, and insulators. The chromatin state in developing body parts provides a code to cellular populations that direct their cell fates. Chromatin profiling has been a method of choice for mapping regulatory sequences in cells that go through developmental transitions. We used antibodies against histone H3 lysine 4 trimethylations (H3K4me3) a modification associated with promoters and open/active chromatin, histone H3 lysine 27 trimethylations (H3K27me3) associated with Polycomb-repressed regions and RNA polymerase II (Pol2) associated with transcriptional initiation to identify the chromatin state signature of the mouse forelimb during mid-gestation, at embryonic day 12 (E12). The families of genes marked included those related to transcriptional regulation and embryogenesis. One third of the marked genes were transcriptionally active while only a small fraction were bivalent marked. Sequence specific transcription factors that were activated were involved in cell specification including bone and muscle formation. Our results demonstrate that embryonic limb cells do not exhibit the plasticity of the ES cells but are rather programmed for a finer tuning for cell lineage specification.
Biological system behaviors are often the outcome of complex interactions among a large number of... more Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming. We have developed Biocellion, a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biologic...
2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2007
Area coverage operations such as plowing a field or mowing a lawn can be performed faster if mult... more Area coverage operations such as plowing a field or mowing a lawn can be performed faster if multiple vehicles are involved. To use a team of automated vehicles safely and effectively they must be coordinated to avoid collisions and deadlock situations. Unexpected events may occur during the operation which may affect vehicles' velocities, so the coordination method must be robust with respect to these events. In this paper, a path coordination method is introduced which delays decisions about mission coordination as long as possible during mission execution so such unexpected situations are efficiently handled. The method's computation speed and solution quality are evaluated through simulation, and compared with two other methods based on common path coordination techniques.
We used a computational approach to examine three questions at the intersection of developmental ... more We used a computational approach to examine three questions at the intersection of developmental biology and evolution: 1) What is the space available for evolutionary exploration for genetic regulatory networks (GRNs) able to solve developmental patterning problems? 2) If different GRNs exist that can solve a particular pattern, are there differences between them that might lead to the selection of one over another? 3) What are the possibilities for co-opting GRN subcircuits or even entire GRNs evolved to solve one pattern for use in the solution of another pattern? We used a Monte Carlo strategy to search for simulated GRNs composed of nodes (proteins) and edges (regulatory interactions between proteins) capable of solving one of three striped cellular patterning problems. These GRNs were subjected to a knockout procedure akin to gene knock-outs in genetic research. Knockout was continued until all individual network components of the reduced GRN were shown to be essential for function. This GRN was termed irreducible. We found many different unique irreducible GRNs that were able to solve each patterning problem. Since any functional GRN must include an irreducible GRN as a core or subgraph, the space for evolutionary exploration of pattern-forming GRNs is large. Irreducible GRNs that solve a particular pattern differed widely in their robustness - the ability to solve a target pattern under different initial conditions. These differences may offer a target for selection to winnow out less robust GRNs from the set of GRNs found in nature. Finally, subgraph isomorphism analysis revealed great potential for co-option during evolution. Some irreducible GRNs appear in their entirety within larger GRNs that solve different patterning problems. At much higher frequency, subcycles are shared widely among irreducible GRNs, including those that solve different patterns. Irreducible GRNs may form the core elements of GRNs found in biological systems and provide insight int- o their evolution
... This research has resulted in the so-called T-series of omni-directional (ODV) robots ( Moore... more ... This research has resulted in the so-called T-series of omni-directional (ODV) robots ( Moore & Flann, 2000). The distinguishing feature of these robots is that both the speed and direction of each smart wheel can be independently controlled through dedicated processors. ...
—Multiscale models that link sub-cellular, cellular and multicellular components offer powerful i... more —Multiscale models that link sub-cellular, cellular and multicellular components offer powerful insights in disease development. Such models need a realistic set of parameters to represent the physical and chemical mechanisms at the sub-cellular and cellular levels to produce high fidelity multicellular outcomes. However, determining correct values for some of the parameters is often difficult and expensive using high-throughput microfluidic approaches. This work presents an alternative approach that estimates cellular parameters from spatiotemporal data produced from bioengineered multicellular in vitro experiments. Specifically, we apply a search technique to an integrated cellular and multicellular model of retinal pigment epithelial (RPE) cells to estimate the binding rate and auto-regulation rate of vascular endothelial growth factor (VEGF). Understanding VEGF regulation is critical in treating age-related macular degeneration and many other diseases. The method successfully identifies realistic values for autoregulatory cellular parameters that reproduce the spatiotemporal in vitro experimental data.
Abstract. Simulated annealing and genetic algorithms represent pow-erful optimization methods wit... more Abstract. Simulated annealing and genetic algorithms represent pow-erful optimization methods with complementary strengths and weak-nesses. Hence, there is an interest in identifying hybrid methods (which combine features of both SA and GA) that exhibit performance superior ...
ABSTRACT The transition in breast cancer from ductal carcinoma in situ to invasive ductal carcino... more ABSTRACT The transition in breast cancer from ductal carcinoma in situ to invasive ductal carcinoma marks a significant drop in patient survival and is one of the leading causes of death in women. This work presents a new 3D model of the breast duct in which the previous 2D duct section model is extended in the lateral dimension to capture the complete duct morphology. The resulting increase in fidelity due to lateral extension is necessary for the discovery of effective interventions since interactions among the duct wall, interstitial fluid and the surrounding stroma are significantly changed. Specifically, the new model can capture the relief of pressure along the duct and the complex morphology of tumor invasion by the breaching of the basement membrane and epithelial tight junction wall. The model represents multiple biochemical and biomechanical interactions among the epithelia, tumor cells, diffusible signals, and stromal components such as fibroblasts, myofibroblasts and extracellular matrix in the ductal microenvironments. Understanding how the interplay among these components drives the dynamics of metastasis and invasion may lead to new therapeutic approaches to breast cancer. We introduced a 3D multicellular agent-based model of DCIS growth and invasion that includes ductal, stromal and tumor cell types acting along with microenvironmental components such as matrix metalloproteinases (MMP), Lysyl oxidase(LOX), nutrients, TGFβ and extracellular matrix (ECM) protein assemblies. We are investigating a wide range of parameters and assumptions in our model that can lead to changes in the model outcomes. The model explicitly determines mechanical tensional and compressive forces within the developing tissue.
In earlier research the Center for Self-Organizing and Intelligent Systems (CSOIS) at Utah State ... more In earlier research the Center for Self-Organizing and Intelligent Systems (CSOIS) at Utah State University (USU) was funded by the US Army Tank-Automotive and Armaments Command's (TACOM) Intelligent Mobility Program to develop and demonstrate enhanced mobility concepts for unmanned ground vehicles (UGVs). As part of our research, we presented the use of a grammar-based approach to enabling intelligent behaviors in autonomous robotic vehicles. With the growth of the number of available resources on the robot, the variety of the generated behaviors and the need for parallel execution of multiple behaviors to achieve reaction also grew. As continuation of our past efforts, in this paper, we discuss the parallel execution of behaviors and the management of utilized resources. In our approach, available resources are wrapped with a layer (termed services) that synchronizes and serializes access to the underlying resources. The controlling agents (called behavior generating agents) generate behaviors to be executed via these services. The agents are prioritized and then, based on their priority and the availability of requested services, the Control Supervisor decides on a winner for the grant of access to services. Though the architecture is applicable to a variety of autonomous vehicles, we discuss its application on T4, a mid-sized autonomous vehicle developed for security applications.
Cell types are defined at the molecular level during embryogenesis by a process called pattern fo... more Cell types are defined at the molecular level during embryogenesis by a process called pattern formation and created by the selective utilization of combinations of sequence specific transcription factors. Developmental programs define the sets of genes that are available to each particular cell type, and real-time biochemical signaling interactions define the extent to which these sets are used at any given time and place. Gene expression is regulated through the integrated action of many cis-regulatory elements, including core promoters, enhancers, silencers, and insulators. The chromatin state in developing body parts provides a code to cellular populations that direct their cell fates. Chromatin profiling has been a method of choice for mapping regulatory sequences in cells that go through developmental transitions. We used antibodies against histone H3 lysine 4 trimethylations (H3K4me3) a modification associated with promoters and open/active chromatin, histone H3 lysine 27 trimethylations (H3K27me3) associated with Polycomb-repressed regions and RNA polymerase II (Pol2) associated with transcriptional initiation to identify the chromatin state signature of the mouse forelimb during mid-gestation, at embryonic day 12 (E12). The families of genes marked included those related to transcriptional regulation and embryogenesis. One third of the marked genes were transcriptionally active while only a small fraction were bivalent marked. Sequence specific transcription factors that were activated were involved in cell specification including bone and muscle formation. Our results demonstrate that embryonic limb cells do not exhibit the plasticity of the ES cells but are rather programmed for a finer tuning for cell lineage specification.
Biological system behaviors are often the outcome of complex interactions among a large number of... more Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming. We have developed Biocellion, a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biologic...
2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2007
Area coverage operations such as plowing a field or mowing a lawn can be performed faster if mult... more Area coverage operations such as plowing a field or mowing a lawn can be performed faster if multiple vehicles are involved. To use a team of automated vehicles safely and effectively they must be coordinated to avoid collisions and deadlock situations. Unexpected events may occur during the operation which may affect vehicles' velocities, so the coordination method must be robust with respect to these events. In this paper, a path coordination method is introduced which delays decisions about mission coordination as long as possible during mission execution so such unexpected situations are efficiently handled. The method's computation speed and solution quality are evaluated through simulation, and compared with two other methods based on common path coordination techniques.
We used a computational approach to examine three questions at the intersection of developmental ... more We used a computational approach to examine three questions at the intersection of developmental biology and evolution: 1) What is the space available for evolutionary exploration for genetic regulatory networks (GRNs) able to solve developmental patterning problems? 2) If different GRNs exist that can solve a particular pattern, are there differences between them that might lead to the selection of one over another? 3) What are the possibilities for co-opting GRN subcircuits or even entire GRNs evolved to solve one pattern for use in the solution of another pattern? We used a Monte Carlo strategy to search for simulated GRNs composed of nodes (proteins) and edges (regulatory interactions between proteins) capable of solving one of three striped cellular patterning problems. These GRNs were subjected to a knockout procedure akin to gene knock-outs in genetic research. Knockout was continued until all individual network components of the reduced GRN were shown to be essential for function. This GRN was termed irreducible. We found many different unique irreducible GRNs that were able to solve each patterning problem. Since any functional GRN must include an irreducible GRN as a core or subgraph, the space for evolutionary exploration of pattern-forming GRNs is large. Irreducible GRNs that solve a particular pattern differed widely in their robustness - the ability to solve a target pattern under different initial conditions. These differences may offer a target for selection to winnow out less robust GRNs from the set of GRNs found in nature. Finally, subgraph isomorphism analysis revealed great potential for co-option during evolution. Some irreducible GRNs appear in their entirety within larger GRNs that solve different patterning problems. At much higher frequency, subcycles are shared widely among irreducible GRNs, including those that solve different patterns. Irreducible GRNs may form the core elements of GRNs found in biological systems and provide insight int- o their evolution
... This research has resulted in the so-called T-series of omni-directional (ODV) robots ( Moore... more ... This research has resulted in the so-called T-series of omni-directional (ODV) robots ( Moore & Flann, 2000). The distinguishing feature of these robots is that both the speed and direction of each smart wheel can be independently controlled through dedicated processors. ...
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