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35 projects in result set. Displaying 20 per page. Projects sorted by alphabetical order.
<1> <2>
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 |
Statistical analysis of conformational ensembles
- This project provides computational tools and methods to analyze conformational ensembles of biomolecules, as well as their assemblies, such as those obtained from molecular simulations.
(A) PROTEINS: The molecular understanding of the functional regulation of proteins requires assessment of various states, including active and inactive states, as well as their interdependencies. For several proteins, their various states can be distinguished from each other on the basis of their minimum energy 3D structures. For many other proteins, like GPCRs, PDZ domains, nuclear transcription factors, heat shock proteins, T-cell receptors and viral attachment proteins, their states can be distinguished categorically from each other only when their finite-temperature conformational ensembles are considered alongside their minimum-energy structures. We are developing tools/methods for:
(A1) Direct comparison of conformational ensembles - The traditional approach to compare two or more conformational ensembles is to compare their respective summary statistics. This approach is, however, prone to artifactual bias, as data is compared after dimensionality reduction. The proper way to compare ensembles is to compare them directly with each other and prior to any dimensionality reduction. g_ensemble_comp is a tool we have developed that does just that and reports the difference between ensembles in terms of a true metric defined by the zeroth law of thermodynamics.
(A2) Prediction of allosteric signaling networks - method under development.
(B) LIPID MEMBRANES: The surface area of a lipid bilayer is related fundamentally to many other observables, such as thermal phase transitions and domain formation in mixed lipid bilayers. We have developed g_tessellate_area to compute the 3D surface area of a bilayer using Delunay tessellation. | |
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Activity Percentile: 92.99 Registered: 2015-09-15 17:52 |
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 |
Practical Annotation and Exchange of Virtual Anatomy
- Representation of anatomy in a virtual form is at the heart of clinical decision making, biomedical research, and medical training. Virtual anatomy is not limited to description of geometry but also requires appropriate and efficient labeling of regions - to define spatial relationships and interactions between anatomical objects; effective strategies for pointwise operations - to define local properties, biological or otherwise; and support for diverse data formats and standards - to facilitate exchange between clinicians, scientists, engineers, and the general public. Development of aeva, a free and open source software package (library, user interfaces, extensions) capable of automated and interactive operations for virtual anatomy annotation and exchange, is in response to these currently unmet requirements. This site serves for aeva outreach, including dissemination the software and use cases. The use cases drive design and testing of aeva features and demonstrate various workflows that rely on virtual anatomy.
aeva downloads:
Downloads (https://simtk.org/frs/?group_id=1767)
Kitware data repository (https://data.kitware.com/#folder/5e7a4690af2e2eed356a17f2)
aeva documentation:
Guides and tutorials (https://aeva.readthedocs.io)
aeva videos:
Short instructions (https://www.youtube.com/channel/UCubfUe40LXvBs86UyKci0Fw)
aeva source code:
Kitware source code repository (https://gitlab.kitware.com/aeva)
aeva forum:
Forums (https://simtk.org/plugins/phpBB/indexPhpbb.php?group_id=1767 ) | |
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Registered: 2019-08-28 01:27 |
BlurLab -- 3D Microscopy Simulation Package
- BlurLab is an easy to use platform for generating simulated fluorescence microscopy data for use in mechanistic modeling visualization, image comparison, and hypothesis testing. The software accepts the 3D positions, intensities and labels of fluorescing objects that are produced by an underlying mechanistic model and transforms them into high quality simulated images. The program includes full 3D convolution with realistic (or even measured) point spread functions; inclusion of thermal, shot and custom noise spectra; simulations of mean and fully stochastic photobleacing; the ability to view scenes in wide-field and TIRF, and perform Z-slicing; and the ability to simulate FRAP experiments.
The software provides a platform for adjusting and saving these simulated images, as well as a number of helpful, semi-automated features to make image simulation easy and less error prone. | |
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Activity Percentile: 79.44 Registered: 2011-08-05 01:17 |
Predicting Cell Deformation from Body Level Mechanical Loads
- This project is a NIBIB/NIH funded study (1R01EB009643-01) to establish models and computational platforms to predict cellular deformations from joint level mechanical loading.
Collaborators:
Ahmet Erdemir (PI), Amit Vasanji, Jason Halloran (Cleveland Clinic)
Cees Oomens, Frank Baaijens (Eindhoven University of Technology)
Jeff Weiss (University of Utah)
Farshid Guilak (Duke University)
Summary (from grant proposal):
Cells of the musculoskeletal system are known to have a biological response to deformation. Deformations, when abnormal in magnitude, duration, and/or frequency content, can lead to cell damage and possible disruption in homeostasis of the extracellular matrix. These mechanisms can be studied in an isolated fashion but connecting mechanical cellular response to organ level mechanics and human movement requires a multiscale approach. At the organ level, physicians perform surgical procedures, investigators try to understand risk of injury, and clinicians prescribe preventive and therapeutic interventions. Many of these operations are aimed at management and prevention of cell damage, and to associate joint level mechanical markers of failure to cell level failure mechanisms. Through human movement, one explores neuromuscular control mechanisms and the influence of physical activity on musculoskeletal tissue properties. At a lower level, mechanical sensation of cell deformations regulate movement control. Physical rehabilitation and exercise regimens are prescribed to promote tissue healing and/or strengthening through cellular regeneration. The knowledge of the mechanical pathway, through which the body level loads are distributed between organs, then within the tissues and further along the extracellular matrix and the cells, is critical for the success of various interventions. However, this information is not established. The goal of this research proposal is to portray that prediction of cell deformations from loads acting on the human body, therefore a clear depiction of the mechanical pathway, is possible, if a multiscale simulation approach is used. Multiresolution models of the knee joint, representative of joint, tissue and cell structure and mechanics, will be developed for this purpose. The knee endures high rates of traumatic injury to its soft tissue structures and it is predominantly affected by osteoarthritis, chronically induced by abnormalities in mechanical loading or how it is transferred to the cartilage. Through multiscale mechanical coupling of these models, a map of cellular deformation in cartilage, ligaments and menisci under a variety of tibiofemoral joint loads will be obtained. Comprehensive mechanical testing at joint, tissue and cell levels will be conducted for parameter estimation and validation, including in vitro loading of the knee joint representative of lifelike loading scenarios. In addition, imaging modalities will capture joint and tissue anatomy, and spatial and deformation related information from cell and extracellular matrix. Advanced computational approaches will be used to obtain model properties and to facilitate multiscale simulations. The approach will combine the expertise of many investigators experienced in biomechanical modeling and experimentation at various biological scales, some with clinical expertise. In future, the research team will utilize this platform to establish the relationship between the structural and loading state of the knee and chondrocyte stresses to explore potential mechanisms of cartilage degeneration. Through documented dissemination of data and models, simulations of other pathologies and translation of the methodology to other organs can be carried out by any interested investigator. | |
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Registered: 2009-07-23 17:33 |
DeepCell: Deep convolutional neural networks for image segmentation
- The assignment of a cellular identity to individual pixels in microscopy images is a key technical challenge for many live-cell experiments. Traditional approaches to this image segmentation problem have relied on standard computer vision techniques, such as thresholding, morphological operations, and the watershed transform. While these approaches have enabled the analysis of numerous experiments, they are limited in their robustness and in applicability. Here, we show that deep convolutional neural networks, a supervised machine learning method, can robustly segment the cytoplasms of individual bacterial and mammalian cells. This approach automates the analysis of thousands of bacterial cells and leads to more accurate quantification of localization based fluorescent reporters in mammalian cells. In addition, this approach can also simultaneously segment and identify different mammalian cell types in co-cultures. Deep convolutional neural networks have had a transformative impact on the problem of image classification, and we anticipate that they will have a similar impact for live-cell imaging experiments.
Visit our webpage at http://covertlab.github.io/DeepCell | |
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Activity Percentile: 71.50 Registered: 2015-11-16 19:58 |
Data for Exacycle GPCR paper on cloud-based simulations
- This project provides links to the GPCR trajectory data used for the analysis in the paper on cloud-based simulations on Google Exacycle. The data is available for download and can be used freely by anyone. | |
Activity Percentile: 50.00 Registered: 2013-12-13 19:27 |
Live Cell NF-κB
- This project provides data and visualization tools to explore single-cell NF-κB dynamics. To view the interactive figure, please see the Downloads section. | |
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Activity Percentile: 12.62 Registered: 2013-03-05 01:40 |
Agent-based model of skeletal muscle disuse-induced atrophy
- This project is a tissue level prediction of muscle atrophy. The model aims to incorporate cellular interactions to establish the extent of muscle atrophy observed during disuse. Current predictions are focused on muscle fiber CSA, but methods are being developed to analyze ECM content and turnover as well | |
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Activity Percentile: 10.75 Registered: 2015-01-19 17:07 |
Neurogene: Elucidating apoptotic pathways in brain tumor models
- Genomics has brought many important discoveries and changes into science and medicine. The central dogma of molecular biology where "DNA makes RNA and RNA makes protein" is well established (yet controversial). Watson and Crick had originally proposed a double stranded model of DNA. This served as a useful foundation for further understanding and research. Throughout the years more investigations demonstrated that human evolution was far more complex than originally believed. There was originally a great deal of migration around the world causing some hereditary lineages to become isolated and others to become more robust.
The life cycle of a cell usually begins with division and continues with replication. However, errors in mitosis can cause a cell to undergo apoptosis or form into a tumor. Differentiating between the two final pathways may be critical in helping to guide cells towards a less destructive pathway for the host organism. The critical component has to do with the environment the cell is in. The cell receives information from the outside environment and adapts according to received stimuli.
This project has been conceived to leverage a team based approach for elucidating the underlying apoptotic pathways responsible for tumor lysis and cell death. Combining the current understanding of molecular dynamics, genomics, and contrast imaging agents to discover novel therapeutic targets and further the current understanding of tumor biology within the genomic era. | |
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Registered: 2010-03-17 09:26 |
CompuCell3D
- For more information please visit: http://www.compucell3d.org/
Modeling the behavior of multi-cell biological systems using multi-scale approach is one of the goals behind CompuCel3D project.
CompuCell3D was originally written to model morphogenesis, the process in embryonic development where cells cluster into patterns which eventually differentiate into organs, muscle or bone. Through integration of multiple mathematical models into a software implementation with easy to use XML based syntax scientists were able to build models within few hours as opposed to weeks when writing source code from scratch. compuCell3D is based on Glazier-graner-Hogeweg model (GGH) also known as the Cellular Potts Model (CPM).The model is capable of capturing key cellular behaviors: cell clustering as well as growth, division, death, intracellular adhesion, and volume and surface area constraints;
In addition researchers may include partial differential equation models for external chemical fields which can model reaction-diffusion, and cell type automata to provide a method for categorizing cells by behavior into types and algorithms for changing cell type.
These models can communicate to establish for example cellular reactions to external chemical fields such as secretion or resorption, and cellular responses such as chemotaxis and haptotaxis. Using scripting language (Python) users may build sophisticated intra-cellular models e.g. reaction-kinetics models, gene pathways etc that determine macroscopic properties of cells. Thus using CompuCell3D one can build truly multi-scale, multi-cell models.
The Graphical User Interface CompuCellPlayer, built upon Qt, interactively visualizes these simulations in three dimensions and also provides the ability to switch to 2D cross sections in each dimension, and also the ability to alternate between chemical fields being visualized. Through this player you can easily pause a simulation to view results and restart again, and also use camera techniques such as zooming, rotating, translating and projecting to more easily view results. The Player uses Qt Threads to enable parallel execution with the CompuCell3D back end. Through the player you can save screenshots of a simulation and for long simulations the Player can be run in silent mode to improve performance, generating images every certain number of steps.
We provide all these features in a single package - CompuCell3D. Both source code and binaries are available for Windows, Linux and Mac OS X. For complete download selection please visit
http://www.compucell3d.org
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Registered: 2006-02-05 19:55 |
NetworkPainter: Biological pathway animation
- NetworkPainter is a web-based program for drawing and painting signaling network diagrams with high-dimensional cytometry data. Two versions of NetworkPainter are available. The <a href="http://covert.stanford.edu/networkpainter">NetworkPainter stand-alone version</a> is capable of visualizing any uploaded cytometry data. NetworkPainter is also available through the <a href="http://www.cytobank.org/networkpainter.html">Cytobank</a> flow cytometry repository. This version is capable of analyzing flow and mass cytometry data stored in Cytobank. | |
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Registered: 2014-01-10 00:11 |
Anatomicaly-based 3D models of the middle ear and the inner ear
- The OtoBiomechanics Group at Stanford is developing three-dimensional and multiscale bio-computational models of the middle ear and the inner ear and their applications to understanding disease processes and interventions.
This project is a collection of code that simulates the biomechanics of the cochlea and the middle ear. At the core is FAST4. This is a program for calculating axisymmetric shells of revolution. FAST4 uses asymptotic methods for calculations, which are orders of magnitude faster than other methods including the finite element approach. The interface to FAST4 is built using MATLAB or Mathematica. | |
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Activity Percentile: 0.00 Registered: 2006-06-05 05:53 |
Membrane Segmentation Toolkit
- The Membrane Segmentation Toolkit implements the approach to identifying plasma membrane voxels in light microscopy images of cells described in Kasson et al., Bioinformatics. 2005 Oct 1;21(19):3778-86. | |
Activity Percentile: 0.00 Registered: 2007-04-22 01:23 |
C++ and Python code, distributed computing and OpenMM interfaces for simulations
- please cite: "Interplay of Protein and DNA Structure Revealed in Simulations of the lac Operon" (PLOS One 2013)
for any code related to protein-DNA modeling and
"Free Energy Monte Carlo Simulations on a Distributed Network" (Lecture Notes in Computer Science Journal for PARA 2010)
http://link.springer.com/chapter/10.1007%2F978-3-642-28145-7_1
for parallel client-server code, users of additional code should cite this web site. Code is provided as-is with no warranty and examples are provided to illustrate the usage of these modeling techniques with some sample systems. Code is the intellectual property of Luke Czapla, developer and biophysicist. Examples are provided in C/C++ and Python. | |
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Activity Percentile: 0.00 Registered: 2014-02-01 22:32 |
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 |
Osmotic pressure, bacterial growth, and bacterial division.
- This project aims to test the hypothesis that bacteria exploit osmotic pressure as a physical driving force for growth and division. | |
Activity Percentile: 0.00 Registered: 2013-03-04 20:25 |
scexpress: A visual aid to examine expression patterns within single cells
- We have designed SC Express, a bioinformatics tool that produces a three-dimensional shape that is reflective of the expression patterns of a single cell. The software package accepts tab delimited text files containing the relevant gene expression data and provides a graphical user interface that enables facile comparison of any two individual cell types on the same screen. | |
Activity Percentile: 0.00 Registered: 2011-03-05 14:54 |
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 |
35 projects in result set. Displaying 20 per page. Projects sorted by alphabetical order.
<1> <2>