Project Tree
Now limiting view to projects in the following categories:
All Topics :: Biological Applications :: Tissue [Remove This Filter]
All Topics > Biological Applications > Cell |
Browse By: |
15 projects in result set.
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 ) | |
|
Registered: 2019-08-28 01:27 |
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. | |
|
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 | |
|
Activity Percentile: 80.30 Registered: 2015-11-16 19:58 |
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. | |
|
Activity Percentile: 77.27 Registered: 2011-08-05 01:17 |
Simple Immune System Response Agent Based Model
- This is a simple Agent Based Model of the immune response to a hypothetical wound. The model accompanies a Science News for Students article as a supplement to allow readers the opportunity to directly experiment with biological simulation. Adjust the strength of the immune response, the number of bacteria in the wound, the bacterial colony growth rate, and other parameters to view the time course of healing. | |
|
Activity Percentile: 0.00 Registered: 2015-07-29 00:16 |
FEBio: Finite Elements for Biomechanics
- FEBio is a nonlinear finite element solver that is specifically designed for biomechanical applications. It offers modeling scenarios, constitutive models, and boundary conditions that are relevant to many research areas in biomechanics and biophysics. All features can be used together seamlessly, giving the user a powerful tool for solving 3D problems in computational biomechanics. The software is open-source, and pre-compiled executables for Windows, Mac OS X and Linux platforms are available.
Current modeling capabilities include:
* Large deformation quasi-static and dynamic structural mechanics analysis.
* Modeling of complex structures that contain a combination of deformable and rigid parts.
* Multiphasic modeling, where the solvent can contain any number of solutes that may undergo chemical reactions.
* Fluid mechanics analysis, both steady-state and transient
* Fluid-solid interaction (FSI), which combines the powerful solid and fluid solvers.
FEBio also supports a plugin framework that can be used to easily develop new features for FEBio, including new constitutive models, boundary conditions, and even entire new physics solvers.
For more information check out the FEBio website at http://www.febio.org | |
|
Registered: 2007-09-14 16:08 |
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 |
Optimal Control Workshop
- This project provides files distributed at the NSF-funded Optimal Control Workshop held on July 9, 2015 at the University of Edinburgh as part of the XV International Symposium on Computer Simulation in Biomechanics. The workshop material was organized into three sections: 1) Motivational material, 2) Technical material, and 3) Tutorial material. Slides from each section, along with all tutorial material (requires a license of GPOPS-II optimal control software), are included. | |
|
Activity Percentile: 0.00 Registered: 2015-08-01 16:35 |
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 |
Agent-Based Model of Skeletal Muscle Injury, Inflammation, and Regeneration
- This model simulates the sterile inflammation process that follows a muscle injury (contusion, laceration, etc). The simulation tracks key inflammatory cells (neutrophils and macrophages), as well as their secretions and interactions with native muscle cells (muscle fibers, satellite cells, fibroblasts). | |
|
Activity Percentile: 0.00 Registered: 2015-06-25 19:33 |
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 | |
|
Activity Percentile: 0.00 Registered: 2015-01-19 17:07 |
Toward virtual biomedical experiments
- Envision a biomedical R&D landscape in which researchers plan detailed wet-lab experiments and execute them in a virtual laboratory—all before putting on their lab coat. They choose virtual reagents, lab equipment, and specimens; they implement virtual protocols and take virtual measurements using virtual instrumentation. They use the results of virtual experiments to design new or refocused wet-lab experiments, which they then conduct in a physical laboratory.
This is the virtual biomedical experiment (VBE) vision. A virtual biomedical experiment is a simulation of a wet-lab or clinical experiment. When developing a VBE, the modeler aspires to mimic particular relevant aspects of the referent experiment—from hypothesis formation to data analysis, and key concepts in between—not just features of the underlying biological processes. | |
Activity Percentile: 0.00 Registered: 2016-04-27 19:44 |
Acetaminophen Induced Liver Injury
- The AILI project is a type of In-Silico Liver (ISL) project, which consists of a body of Java code used and reused for exploring hypothetical liver mechanisms. For AILI, the liver mechanisms are those that cause cellular damage, specifically necrosis, because of exposure to acetaminophen. Moreover, the model, a mouse analog, is used for virtual experimentation to explore and explain AILI phenomena, analogous to wet-lab experimentation. A recent addition to this project is studying the disconnect between in vitro and in vivo wet-lab experiments by comparing and contrasting virtual Mouse and Culture Analogs. | |
|
Activity Percentile: 0.00 Registered: 2015-05-07 23:25 |
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. | |
|
Registered: 2010-03-17 09:26 |
Cell Movement Simulation
- simulation of cell movements | |
Activity Percentile: 0.00 Registered: 2013-11-13 18:02 |