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9 projects in result set.
Whole-Cell Computational Model of Mycoplasma genitalium
- The goal of this project was to develop the first detailed, "whole-cell" computational model of the entire life cycle of living organism, <i>Mycoplasma genitalium</i>. The model describes the dynamics of every molecule over the entire life cycle and accounts for the specific function of every annotated gene product.
We anticipate that whole-cell models will be critical for synthetic biology and personalized medicine. Please see the project website <a href="http://wholecell.org">wholecell.org</a> and the Downloads page to explore the whole-cell knowledge base and simulations and obtain the model code. | |
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Registered: 2012-01-24 03:21 |
Integrated Flux Balance Analysis Model of Escherichia coli
- This project includes several MATLAB scripts that simulate E. coli central metabolism and the effects of single gene deletions on metabolism using 3 approaches -- iFBA, rFBA, and ODE. The project also includes several MATLAB scripts that simulate biochemical networks using 1) integrated flux balance analysis (iFBA) -- a combined FBA, boolean regulatory, and ODE approach; 2) regulatory flux balance analysis (rFBA); and 3) ordinary differential equations (ODE). Additionally, the project includes several MATLAB and php scripts for visualizing metabolic simulations. | |
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Registered: 2008-06-11 23:27 |
Modularizing biological models: physiomimetic mechanism modules (PMMs)
- This study describes a method to modularize biological models, such that they can be reused, repurposed, integrated, and shared without significant refactoring. The unit of modularization is a biological mechanism; the modularized mechanism is called a physiomimetic mechanism module (PMM). The study provides both a scientific, generalized modularization method as well as a demonstrated method specific to Java and other object-oriented programming languages. | |
Activity Percentile: 0.00 Registered: 2015-05-07 20:35 |
Dynamic Redox Regulation of IL-4 Signaling
- Incomplete reduction of oxygen during respiration results in the formation of highly reactive molecules known as reactive oxygen species (ROS) that react indiscriminately with cellular components and adversely affect cellular function. For a long time ROS were thought solely to be undesirable byproducts of respiration. Indeed, high levels of ROS are associated with a number of diseases. Despite these facts, antioxidants, agents that neutralize ROS, have not shown any clinical benefits when used as oral supplements. This paradox is partially explained by discoveries over the last two decades demonstrating that ROS are not always detrimental and may be essential for controlling physiological processes like cell signaling. However, the mechanisms by which ROS react with biomolecules are not well understood. In this work we combined biological experiments with novel computational methods to identify the most important mechanisms of ROS-mediated regulation in the IL-4 signaling pathway of the immune system. We developed a detailed computer model of the IL-4 pathway and its regulation by ROS dependent and independent methods. Our work enhances the understanding of principles underlying regulation of cell signaling by ROS and has potential implications in advancing therapeutic methods targeting ROS and their adverse effects. | |
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Activity Percentile: 0.00 Registered: 2015-10-16 21:42 |
Agent-based (AB) pharmacokinetic, AB pathology, and AB PK/PD tutorial models
- The tutorials in this publication outline the development and simulation results of three agent-based (AB) models: a pharmacokinetic (PK), pathology, and pharmacokinetic/pharmacodynamic (PKPD) models. 1) The AB PK model uses a two-compartment system, including five agents that transfer, store, and record simulation information. 2) The AB pathology model includes a Morbidity agent and Symptom information. 3) The AB PK/PD model integrates the two earlier models and allows the user to delivery an intervention Dose that diminishes Symptom until Dose is cleared. | |
Activity Percentile: 0.00 Registered: 2015-08-10 18:01 |
Flexible (flexFBA) and time-linked (tFBA) Flux Balance Analysis methods
- (provided for computational biologists to reproduce publication results, and a small utility written for example use with the Cobra toolbox) The associated publication describes two complimentary methods that remove the inherent long-time assumptions of the biomass reaction used in FBA. Implementing a flexible objective flexFBA, enables a metabolic network to produce biological process reactants independently from one another. This flexibility is in contrast to the rigid proportion held by the traditional biomass reaction of FBA. Also, time-linked simulation (tFBA) can represent transitions between metabolic steady states by returning cell process byproducts at subsequent time-steps. | |
Activity Percentile: 0.00 Registered: 2013-08-19 17:12 |
In Silico Liver (ISL) - Multi-level, multi-attribute model mechanisms
- The ISL project consists of a body of Java code used and reused for exploring hypothetical liver mechanisms. The codebase is designed to allow for multiple distinct use cases and experimental designs, some of which we've published already. The scale/resolution of focus changes depending on the use case/experiment being considered. Typically, the hypothetical mechanism is finer grained than the falsifcation/validation data available. Much of the published work focuses on intracellular mechanisms, which requires the cellular and tissue contexts to be defined according to the literature. | |
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Registered: 2014-03-17 18:37 |
T cell calcium dynamics regulated by age-induced oxidation
- T cells reach a state of replicative senescence characterized by a decreased ability to proliferate and respond to foreign antigens. Calcium release associated with TCR engagement is widely used as a surrogate measure of T cell response. Using an ex vivo culture model that partially replicates features of organismal aging, we observe that while the amplitude of Ca2+ signaling does not change with time in culture, older T cells exhibit faster Ca2+ rise and a faster decay. Gene expression analysis of Ca2+ channels and pumps expressed in T cells by RT-qPCR identified overexpression of the plasma membrane CRAC channel subunit ORAI1 and PMCA in older T cells. To test whether overexpression of the plasma membrane Ca2+ channel is sufficient to explain the kinetic information, we adapted a previously published computational model by Maurya and Subramaniam to include additional details on the store-operated calcium entry (SOCE) process to recapitulate Ca2+ dynamics after T cell receptor stimulation. Simulations demonstrated that upregulation of ORAI1 and PMCA channels is not sufficient to explain the observed alterations in Ca2+ signaling. Instead, modeling analysis identified kinetic parameters associated with the IP3R and STIM1 channels as potential causes for alterations in Ca2+ dynamics associated with the long term ex vivo culturing protocol. Due to these proteins having known cysteine residues susceptible to oxidation, we subsequently investigated and observed transcriptional remodeling of metabolic enzymes, a shift to more oxidized redox couples, and post-translational thiol oxidation of STIM1. The model-directed findings from this study highlight changes in the cellular redox environment that may ultimately lead to altered T cell calcium dynamics during immunosenescence or organismal aging. | |
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Registered: 2016-07-01 17:00 |
Bionet biological cell network pathway simulation
- The methodology in bionet is distinguished from previous qualitative modeling approaches in several ways. The goal was to develop a model that would allow experimental biologists to use the kind of qualitative data found in typical journal articles to describe the interaction of genes, proteins, and other cellular components to create computer models of large numbers of interacting parts. This arose from a practical need in our research to keep track of myriad components in pathway models that were built from data extracted from dozens of journal articles. Biologists already do this kind of mental modeling every time they make a new hypothesis; a tool was needed to aid in this reasoning. Secondly, with new sources of data becoming available, it was important to design a methodology that could be expanded in the future to integrate new data sources to refine models.
Finally, biological processes span many scales. A kind of heuristic modeling is common in the literature, where molecular interactions are analyzed and used to create new hypotheses about cellular events, tissue processes or disease progression. For example, specific gene mutations accelerate tumor growth in specific tissues. This is a semi-quantitative relationship between two very different scales. Fuzzy network modeling can be used as a tool for aiding human reasoning when many interacting variables participate in complex interaction networks on several scales. Though the interactions can sometimes only be described approximately, the logic of the interactions is rigorous.
Pathway models can be constructed manually by biologists and manipulated to study the dynamics of alternative pathways. However, the power of this method is that it provides a framework for using various soft computing technologies to integrate diverse data sources to improve and refine models. Rule-based or fuzzy logic models are appropriate for manipulation by genetic or other evolutionary algorithms, which may be useful for drug target discovery. This process will be discussed in future papers that expand the basic model presented here. Details about methods for integration of high-throughput data with expert knowledge will also be reserved for future publications. Because the soft computing paradigm has been widely adopted for many engineering tasks, it is hoped that the framework presented here can be adopted and rapidly expanded by many researchers with expertise in these methods. Input files and code for all examples presented are available at the Bionet website.
Continued development of Bionet is funded in part by the Stowers Institute for Medical Research (http://www.stowers-institute.org). | |
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Activity Percentile: 0.00 Registered: 2009-08-12 20:28 |