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26 projects in result set. Displaying 20 per page. Projects sorted by alphabetical order.
<1> <2>
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: 93.89 Registered: 2015-09-15 17:52 |
Are subject-specific musculoskeletal models robust to parameter identification?
- This study analyzed the sensitivity of the predictions of an MRI-based musculoskeletal model (i.e., joint angles, joint moments, muscle and joint contact forces) during walking to the unavoidable uncertainties in parameter identification, i.e., body landmark positions, maximum muscle tension and musculotendon geometry. To this aim, we created an MRI-based musculoskeletal model of the lower limbs, defined as a 7-segment, 10-degree-of-freedom articulated linkage, actuated by 84 musculotendon units. We then performed a Monte-Carlo probabilistic analysis perturbing model parameters according to their uncertainty, and solving a typical inverse dynamics and static optimization problem using 500 models that included the different sets of perturbed variable values. Model creation and gait simulations were performed by using freely available software that we developed to standardize the process of model creation, integrate with OpenSim and create probabilistic simulations of movement. | |
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Activity Percentile: 93.13 Registered: 2014-11-10 15:19 |
MIcro Simulation Tool - MIST
- The MIcro Simulation Tool is free software that allows the user to :
* Define state transition models with multiple processes
* Generate populations to match given statistics using Evolutionary Computation
* Run Simulations in High Performance Computing environment - including the cloud
* Analyze and Report the results
Below are some videos that describe MIST capabilities:
This video shows the basic ideas behind MIST
<iframe width="640" height="360" src="https://www.youtube.com/embed/AD896WakR94" frameborder="0" allowfullscreen></iframe>
This video shows some population generation capabilities using Evolutionary Computation:
<iframe width="640" height="360" src="https://www.youtube.com/embed/PPpmUq8ueiY" frameborder="0" allowfullscreen></iframe>
This video will show how MIST runs over the cloud:
<iframe width="640" height="360" src="https://www.youtube.com/embed/wpfw8POx-wI" frameborder="0" allowfullscreen></iframe>
This video will show how MIST modeled COVID19 in <a href="https://devpost.com/software/improved-disease-modeling-tools-for-populations">Pandemic Response Hackathon</a>
<iframe width="640" height="360" src="https://www.youtube.com/embed/0ElKy0Ysz3I" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
The Reference Model is one examples of use of MIST. It can be found in the following link:
https://simtk.org/projects/therefmodel
MIST version 0.92.5.0 is released to the public. It has limited capabilities. For later versions with enhanced capabilities, please contact the developer.
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Registered: 2014-08-21 20:53 |
MSMBuilder
- MSMBuilder is an open source software package for automating the construction and analysis of Markov state models (MSMs). It is primarily written in the python programming language with C extensions for the most time consuming routines.
MSMs are a powerful means of modeling the structure and dynamics of molecular systems, like proteins. An MSM is essentially a map of the conformational space a molecule explores. Such models consist of a set of states and a matrix of transition probabilities (or, equivalently, transition rates) between each pair of states. Intuitively, the states in an MSM can be thought of as corresponding to local minima in the free energy landscape that ultimately determines a molecule’s structure and dynamics.
MSMBuilder includes tools for
- Constructing an MSM from a set of computer simulations (typically molecular dynamics simulations in standard formats like xtc, dcd, and pdb)
- Validating statistical properties of MSMs
- Mimicking various experimental protocols to allow a quantitative comparison with experiments
- Driving efficient simulations via adaptive sampling (which decides where new simulations should be run to minimize statistical uncertainty in a model)
<p style="font-size:20px">For more information, including the latest releases, see our website at</p><p style="font-size:20px; text-align:center; font-weight:600;"><a href="http://msmbuilder.org">MSMBuilder.org</a></p> | |
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Registered: 2008-11-26 04:53 |
ACL Reconstruction Decision Support Through Personalized Simulation of the Lachm
- The objective of the proposed approach is to develop a clinical decision support system (DSS) that will help clinicians optimally plan the ACL reconstruction procedure in a patient specific manner.
Methods: A full body model is developed in this study with 23 degrees of freedom and 93 muscles. The knee ligaments are modeled as non-linear spring-damper systems and a tibiofemoral contact model was utilized. The parameters of the ligaments were calibrated based on an optimization criterion. Forward dynamics were utilized during simulation for predicting the model’s response to a given set of external forces, posture configuration and physiological parameters.
Results: The proposed model is quantified using MRI scans and measurements of the well-known Lachman test, on several patients with a torn ACL. The clinical potential of the proposed framework is demonstrated in the context of flexion-extension, gait and jump actions. The clinician is able to modify and fine tune several parameters such as number of bundles, insertion position on the tibia or femur and the resting length that correspond to the choices of the surgical procedure and study their effect on the biomechanical behavior of the knee.
Conclusion: Computational knee models can be used to predict the effect of surgical decisions and to give insight on how different parameters can affect the stability of the knee. Special focus has to be given in proper calibration and experimental validation.
<iframe width="560" height="315" src="https://www.youtube.com/embed/zgcq0c5_w3c" frameborder="0" allow="autoplay; encrypted-media" allowfullscreen></iframe> | |
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Activity Percentile: 46.95 Registered: 2015-08-31 08:55 |
Musculoskeletal model sensitivity to soft tissue artefacts
- Musculoskeletal models estimates can be heavily affected by the soft tissue artefact (STA) when input positional data are obtained using stereophotogrammetry. In this study, we assessed the sensitivity to the STA of three open-source musculoskeletal models and relevant tools, implemented in OpenSim. To this purpose, a baseline dataset of marker trajectories was created using point kinematics for each model from experimental data of one healthy volunteer’s gait. Five hundred STA realizations were then statistically generated using a marker-dependent model of the pelvis and lower limb artefact and added to the baseline data. The STA's impact on the musculoskeletal model estimates of an inverse dynamics pipeline (joint angles, joint moments, and muscle and joint contact forces) was finally quantified using a Monte Carlo analysis. | |
Registered: 2016-09-19 13:22 |
ForceBalance : Systematic Force Field Optimization
- ForceBalance is free software for force field optimization.
It facilitates the development of more accurate force fields using a systematic and reproducible procedure.
ForceBalance is highly versatile and can optimize nearly any set of parameters using experimental measurements and/or ab initio calculations as reference data.
<b>SOURCE CODE:</b> For the newest features, visit the GitHub source code repository at https://github.com/leeping/forcebalance.
The SVN repository on the left frame is an outdated archive.
<b>RELEASES:</b> Stable versions of the code updated once every few months. Click "Releases" on the left frame for the most recent release and notes.
<b>CONTACT:</b> Please contact me (Lee-Ping, right frame) if you have questions or comments! | |
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Registered: 2011-12-20 17:04 |
Multicore parallel computing with OpenSim Moco
- In this project, we investigated the computational speed‐up obtained via multicore parallel computing relative to solving problems serially (i.e., using a single core) in optimal control simulations of human movement in OpenSim Moco. Simulations were solved using up to 18 cores with a variety of temporal mesh interval densities and using two different initial guess strategies. Considerable speed‐up can be achieved for some optimal control simulation problems in OpenSim Moco by leveraging the multicore processors often available in modern computers.
This work is described in the paper "Computational performance of musculoskeletal simulation in OpenSim Moco using parallel computing" which is available on the Publications page. Models and complete working examples are provided on the Downloads page. This project was supported by a Rackham Graduate Student Research Grant. | |
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Registered: 2023-08-21 23:33 |
Neuromuscular Models for the Predictive Treatment of Parkinson's Disease
- NoTremor aims to provide patient specific computational models of the coupled brain and neuromuscular systems that will be subsequently used to improve the quality of analysis, prediction and progression of Parkinson’s disease. In particular, it aspires to establish the neglected link between brain modelling and neuromuscular systems that will result in a holistic representation of the physiology for PD patients. | |
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Activity Percentile: 17.56 Registered: 2014-06-18 13:56 |
Neuromusculoskeletal Modeling (NMSM) Pipeline
- <div style="display:inline-block"><a href="https://nmsm.rice.edu"><img src="https://nmsm.rice.edu/img/nmsm-pipeline-social-card.jpg" style="float:left;max-width:calc(100% - 40px);"></a></div>
Full project information is available at: https://nmsm.rice.edu. Please direct any inquiries about the NMSM Pipeline to us by posting your questions on this SimTK project forum or emailing nmsm@rice.edu.
Neuromusculoskeletal Modeling (NMSM) Pipeline is a set of tools for personalizing models and designing treatments for movement impairments and other pathologies.
The NMSM Pipeline consists of two toolsets:
Model Personalization - Personalize joint, muscle-tendon, neural control, and ground contact model properties.
Treatment Optimization - Design treatments using personalized models and an optimal control methodology.
At this time, Treatment Optimization requires the use of <a href="https://www.gpops2.com/">GPOPS-II optimal control solver</a>.
The NMSM Pipeline is written in MATLAB to lower the barrier for entry and to facilitate accessibility to the core codebase. We encourage users to modify the code to meet their needs.
The core codebase and examples are available to download for use in research. At this time, we ask that you wait to publish any work that uses the NMSM Pipeline until the journal article reference for the software is available. Please get in touch with us if you have any questions.
If you need help or want to start a discussion, please use the SimTK forum for this project.
Note: This project is a living entity. Updates will be made available as the Pipeline, examples, and tutorials are developed further and improved. | |
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Registered: 2022-07-07 14:55 |
A Python implementation of the multistate Bennett acceptance ratio (MBAR)
- pymbar has migrated to GitHub:
https://github.com/choderalab/pymbar | |
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Registered: 2007-11-12 19:45 |
Finite Element Mesh Overclosure Reduction and Slicing (FEMORS)
- The code was developed with the project to make freely available 3D geometries of the lower limbs of the Visible Human Female and Visible Human Male. The FEMORS code was used to remove all overclosures between adjacent geometries. The VH 3D geometries are available at: https://simtk.org/projects/3d-vh-geometry
The code was implemented in MATLAB utilizing the Machine Learning Toolbox and is available free and open-source, but we ask that you cite the following two works:
Andreassen, T. E., Hume, D. R., Hamilton, L. D., Higinbotham, S. E. & Shelburne, K. B. "An Automated Process for 2D and 3D Finite Element Overclosure and Gap Adjustment using Radial Basis Function Networks". 1–13 (2022) https://doi.org/10.48550/arXiv.2209.06948
TE Andreassen, DR Hume, LD Hamilton, K Walker, SE Higinbotham, KB Shelburne, "Three-dimensional lower extremity musculoskeletal geometry of the Visible Human Female and Male,” Sci Data 10, 34 (2023). https://doi.org/10.1038/s41597-022-01905-2.
Adding changes to the code is encouraged and can be added to the repository by contacting the author. The author will check new or revised content for accuracy and completeness and add it to the repository.
Future/ongoing work aims to recreate the code using code that does not need the Machine Learning Toolbox, as well as implementing the code into a Python Toolbox for widespread use. | |
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Registered: 2023-03-27 19:58 |
Tibial forces in independently ambulatory children with spina bifida
- Experimental motion capture and bone strength data and simulation results from 16 independently ambulatory children with spina bifida and 16 age- and sex-matched children with typical development. Additional motion capture and EMG data and simulation results for 6 independently ambulatory children with spina bifida and 1 child with typical development. Custom scripts were used to calculate joint kinematics, moments, and forces. Post-simulation analyses were conducted to compare these waveforms between the group with spina bifida and the group with typical development.
The manuscript using these data and simulations can be found here:
Lee MR, Hicks JL, Wren TAL, and Delp SL (2022). Independently ambulatory children with spina bifida experience near-typical knee and ankle joint moments and forces during walking. Gait and Posture, 99:1-8. https://doi.org/10.1016/j.gaitpost.2022.10.010 | |
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Registered: 2022-06-01 20:00 |
Computational Analysis of Kinase Selectivity using Structural Knowledge
- Here, we present a knowledge-based approach to profile kinase selectivity based on the similarity between drug binding microenvironments. To allow large-scale kinase site similarity profiling, we have created a kinome structure database consisting of 5000 inhibitor-binding pockets from 187 unique human kinase crystal structures. | |
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Registered: 2017-04-18 20:03 |
Application for the simulation of the prosthetic gait
- This application has a dataset belonging to macha prosthetic patterns , in which the angle of the socket and prosthetic foot is changed.
It focuses on patients with transtibial amputation and uses opensim in MATLAB libraries to link and generate a model for opensim , based on data captured from a measuring TECHNAID brand. | |
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Registered: 2016-08-24 14:21 |
Identifying druggable targets by protein microenvironments matching
- DrugFEATURE is a computational method that evaluates target druggability by assessing the protein microenvironments in potential small molecule binding sites. | |
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Activity Percentile: 0.00 Registered: 2013-09-28 17:15 |
Systematic Target Function Annotation of Human Transcription Factors
- Transcription factors (TFs), the key players in transcriptional regulation, have attracted great experimental attention, yet the functions of most human TFs remain poorly understood. Recent capabilities in genome-wide protein binding profiling have stimulated systematic studies of the hierarchical organization of human gene regulatory network and DNA-binding specificity of TFs, shedding light on combinatorial gene regulation. We show here that these data also enable a systematic annotation of the biological functions and functional diversity of TFs. We compiled a human gene regulatory network for 384 TFs covering the 146,096 TF-target gene relationships, extracted from over 850 ChIP-seq experiments as well as the literature. By integrating this network of TF-TF and TF-target gene relationships with 3,715 functional concepts from six sources of gene function annotations, we obtained over 9,000 confident functional annotations for 279 TFs. We observe extensive connectivity between transcription factors and Mendelian diseases, GWAS phenotypes, and pharmacogenetic pathways. Further, we show that transcription factors link apparently unrelated functions, even when the two functions do not share common genes. Finally, we analyze the pleiotropic functions of TFs and suggest that increased number of upstream regulators contributes to the functional pleiotropy of TFs. Our computational approach is complementary to focused experimental studies on TF functions, and the resulting knowledge can guide experimental design for discovering the unknown roles of TFs in human disease and drug response. | |
Activity Percentile: 0.00 Registered: 2015-11-17 06:49 |
Ensemble Validation Tools
- NOTE: This SimTK repository is deprecated: Please visit instead:
https://github.com/shirtsgroup/checkensemble
This software allows users to perform statistical test to determine if a given molecular simulation is consistent with the thermodynamic ensemble it is performed in. | |
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Activity Percentile: 0.00 Registered: 2011-08-24 11:01 |
MutInf & K-L Div/J-S Div: information theory analysis of molecular dynamics sims
- MutInf is an analysis package written in Python. inline C, and R that analyses data from Molecular Dynamics Simulations to identify statistically significant correlated motions and calculate residue-by-residue conformational entropies. Our work has shown that the pattern of mutual information between residues can be used to predict potential allosteric sites, identify couplings between allosteric sites, and identify residues that might be important in mediating these couplings.
Recently, we've also included a module to compare conformational ensembles from MD sims or sets of MD sims using the Kullback-Leibler Divergence / Jensen-Shannon Divergence expansion. This is useful for comparing simulations of wildtype/mutant proteins, apo/holo, simulations started from different conformations, etc. Please see McClendon et. al., JCTC, 2012. for more information. | |
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Activity Percentile: 0.00 Registered: 2010-11-09 22:28 |
SMART: Single Molecule Analysis Research Tool
- We provide a standardized approach for analyzing single molecule data in the software package SMART: Single Molecule Analysis Research Tool. SMART provides a format for organizing and easily accessing single molecule data, a general hidden Markov modeling algorithm for fitting an array of possible models specified by the user, a standardized data structure and graphical user interfaces to streamline the analysis and visualization of data. This approach guides experimental design, facilitating acquisition of the maximal information from single molecule experiments. SMART also provides a standardized format to allow dissemination of single molecule data and transparency in the analysis of reported data. | |
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Activity Percentile: 0.00 Registered: 2011-12-19 00:53 |
26 projects in result set. Displaying 20 per page. Projects sorted by alphabetical order.
<1> <2>