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182 projects in result set. Displaying 20 per page. Projects sorted by alphabetical order.
<1> <2> <3> <4> <5> <6> <7> <8> <9> <10>
Open Knee(s): Virtual Biomechanical Representations of the Knee Joint
- Open Knee(s) was aimed to provide free access to three-dimensional finite element representations of the knee joint (<A HREF="https://doi.org/10.1007/s10439-022-03074-0">https://doi.org/10.1007/s10439-022-03074-0</A>). The development platform remains open to enable any interested party to use, test, and edit the model; in a nut shell get involved with the project.
This study was primarily funded by the National Institute of General Medical Sciences, National Institutes of Health (R01GM104139) and in part by National Institute of Biomedical Imaging and Bioengineering (R01EB024573 and R01EB025212). Previous activities leading towards this project had been partially funded by the National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health (R01EB009643).
Open Knee(s) by Open Knee(s) Development Team is licensed under a <A HREF="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International License</A>.
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Registered: 2010-02-18 20:41 |
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 |
OpenArm: Volumetric & Time Series Models of Muscle Deformation
- We invite anyone in the research community to use the OpenArm and OpenArm Multisensor data sets to validate existing muscle deformation models or to devise new ones.
Full details can be found in the following papers:
Laura A. Hallock, Bhavna Sud, Chris Mitchell, Eric Hu, Fayyaz Ahamed, Akash Velu, Amanda Schwartz, and Ruzena Bajcsy. "Toward Real-Time Muscle Force Inference and Device Control via Optical-Flow-Tracked Muscle Deformation." In IEEE Transactions on Neural Systems and Rehabilitation Engineering (TNSRE). IEEE, 2021. (Under review.)
Laura Hallock, Akash Velu, Amanda Schwartz, and Ruzena Bajcsy. "Muscle deformation correlates with output force during isometric contraction." In IEEE RAS/EMBS International Conference on Biomedical Robotics & Biomechatronics (BioRob). IEEE, 2020. (Available at https://people.eecs.berkeley.edu/~lhallock/publication/hallock2020biorob.)
Yonatan Nozik*, Laura A. Hallock*, Daniel Ho, Sai Mandava, Chris Mitchell, Thomas Hui Li, and Ruzena Bajcsy, "OpenArm 2.0: Automated Segmentation of 3D Tissue Structures for Multi-Subject Study of Muscle Deformation Dynamics," in International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE, 2019. *Equal contribution. (Available at https://people.eecs.berkeley.edu/~lhallock/publication/nozikhallock2019embc.)
Laura Hallock, Akira Kato, and Ruzena Bajcsy. "Empirical quantification and modeling of muscle deformation: Toward ultrasound-driven assistive device control." In IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2018. (Available at https://people.eecs.berkeley.edu/~lhallock/publication/hallock2018icra.)
This project is currently in development in the Human-Assistive Robotic Technologies (HART) Lab at the University of California, Berkeley (http://hart.berkeley.edu). | |
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Registered: 2018-11-28 20:40 |
Muscle-actuated Simulation of Human Running
- The purpose of this study was to determine how muscles contribute to propulsion (i.e., the fore-aft acceleration) and support (i.e., the vertical acceleration) of the body mass center during running at 3.96 m/s (6:46 min/mile), including the effects of the torso and arms. To achieve this, we developed a three-dimensional muscle-actuated simulation of running that included 92 musculotendon actuators representing 76 muscles of the lower extremities and torso. By using a three-dimensional model with lower extremity muscles, a torso, and arms, we were able to quantify the contribution of muscles and arm dynamics to mass center accelerations in three dimensions, which provided insights into the actions of muscles during running. The simulation is freely available (simtk.org) allowing other researchers to reproduce our results and perform additional analyses. | |
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Registered: 2010-06-04 01:25 |
SimVascular: Examples and Clinical Cases
- We invite you to download and try these examples and clinical case projects, which are all compatible with the open source SimVascular cardiovascular modeling software package. Each case includes image data of a healthy or diseased individual, a 3D anatomic model created from the image data, and simulation job files which specify initial conditions, boundary conditions and various parameters required to run the simulation. Many of the cases are already organized as SV projects, which means you can easily load them into SimVascular and view or try out various project components. Following the guides in the SimVascular documentation website, you can also create new models and run simulations with different conditions, based on these example cases.
You are free to download the examples and cases provided that you properly reference the source. The cases are part of the academic output of the researcher cited and should be referred to as such. Permission is granted to use these cases for research purposes, but for commercial use please contact the director of the Cardiovascular Biomechanics Computation Lab, Alison Marsden (amarsden@stanford.edu).
The examples and clinical cases included are:
Example: Demo Project
Example: Cylinder Project (no image, for simulation)
Clinical Case: Coronary Normal
Clinical Case: Aortofemoral Normal 1
Clinical Case: Aortofemoral Normal 2
Clinical Case: Healthy Pulmonary
SimVascular is available for download at our project website at:
https://simtk.org/projects/simvascular
Comprehensive documentation is available on the SimVascular website at:
http://www.simvascular.org
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Activity Percentile: 95.04 Registered: 2014-03-14 20:12 |
Grand Challenge Competition to Predict In Vivo Knee Loads
- Knowledge of muscle and joint contact forces during gait is necessary to characterize muscle coordination and function as well as joint and soft-tissue loading. Musculoskeletal modeling and simulation is required to estimate muscle and joint contact forces, since direct measurement is not feasible under normal conditions. This project provides the biomechanics community with a unique and comprehensive data set to validate muscle and contact force estimates in the knee. This data set includes motion capture, ground reaction, EMG, tibial contact force, and strength data collected from a subject implanted with an instrumented knee prosthesis. | |
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Activity Percentile: 94.66 Registered: 2009-07-14 23:24 |
Simulations of Crouch Gait
- This research examined the <b>dynamics of crouch gait among children with cerebral palsy </b>. Specifically, our work examined individual muscles contribute to joint and mass center movement in children with cerebral palsy who walk with a crouch gait. In 2010, we created simulations of single-limb stance for 10 subjects with a mild crouch gait. In 2012-2013, we expanded this study to evaluate muscle contributions to gait during mild, moderate, and severe crouch gait. We also used these simulations to evaluate how muscle weakness may contribute to crouch gait and to examine knee contact force during crouch gait. In 2017, these simulations were also used to evaluate how passive or powered ankle foot orthoses may assist during crouch gait. Together this research has helped us understand the mechanisms that contribute to crouch gait and guide treatment planning to improve gait for children with cerebral palsy.
Please visit the <a href="https://nmbl.stanford.edu"> Neuromuscular Biomechanics Lab </a> and the <a href="depts.washington.edu/uwsteele/"> Ability & Innovation Lab </a> to learn more about our on-going research in this area.
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Activity Percentile: 93.89 Registered: 2010-05-18 22:21 |
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: 92.37 Registered: 2014-11-10 15:19 |
Data-driven prediction of gait with ankle exoskeletons
- The datasets included on this page contain walking data from twelve unimpaired adults walking on a treadmill while wearing bilateral passive ankle exoskeletons. Datasets are four minutes long, and contain kinematic and ground reaction force data, and electromyography from seven leg muscles bilaterally.
The associated Python code can be used to generate data-driven predictive models of response to the ankle exoskeletons. The associated MATLAB code can be used to perform statistical analyses of the data. | |
Registered: 2020-05-29 23:55 |
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 |
Collagen Database
- This project contains the supplementary materials for the cited publication on molecular dynamics simulations of collagen type I. | |
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Registered: 2008-07-03 01:33 |
Predicting allosteric communication in myosin via a conserved residue pathway
- This project contains the AlloPathFinder application that allows users to compute likely allosteric pathways in proteins. The underlying assumption is that residues participating in allosteric communication should be fairly conserved and that communication happens through residues that are close in space.
The initial application for the code provided was to study the allosteric communication in myosin. Myosin is a well-studied molecular motor protein that walks along actin filaments to achieve cellular tasks such as movement of cargo proteins.
It couples ATP hydrolysis to highly-coordinated conformational changes that result in a power-stroke motion, or ''walking'' of myosin. Communication between a set of residues must link the three functional regions of myosin and transduce energy: the catalytic ATP binding region, the lever arm, and the actin-binding domain. We are investigating which residues are likely to participate in allosteric communication pathways. | |
Registered: 2007-01-09 18:30 |
Model of the Scapulothoracic Joint
- In this study, we developed a rigid-body model of a scapulothoracic joint to describe the kinematics of the scapula relative to the thorax. This model describes scapula kinematics with four degrees of freedom: 1) elevation and 2) abduction of the scapula on an ellipsoidal thoracic surface, 3) upward rotation of the scapula normal to the thoracic surface, and 4) internal rotation of the scapula to lift the medial border of the scapula off the surface of the thorax. The surface dimensions and joint axes can be customized to match an individual’s anthropometry. We compared the model to “gold standard” bone-pin kinematics collected during three shoulder tasks and found modeled scapula kinematics to be accurate to within 2 mm root-mean-squared error for individual bone-pin markers across all markers and movement tasks. As an additional test, we added random and systematic noise to the bone-pin marker data and found that the model reduced kinematic variability due to noise by 65% compared to Euler angles computed without the model. Our scapulothoracic joint model can be used for inverse and forward dynamics analyses and to compute joint reaction loads. The computational performance of the scapulothoracic joint model is well suited for real-time applications, is freely available as an OpenSim 3.2 plugin, and is customizable and usable with other OpenSim models. | |
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Activity Percentile: 88.17 Registered: 2015-01-14 23:10 |
Musculoskeletal Model of the Lumbar Spine
- The work here features a number of different OpenSim models of the lumbar spine developed to study lumbar kinematics and dynamics.
Briefly, the models consist of the following bodies:
# rigid pelvis and sacrum
# five lumbar vertebrae (separated by joints with three rotational degrees of freedom)
# torso (thoracic spine + ribcage)
The motion of the individual joints are defined using constraint functions specifying the motion of the lumbar vertebra as functions of the net lumbar motion (flexion-extension, lateral bending and axial rotation). Future models will incorporate joints with stiffness properties to more accurately mimic the action of the intervertebral joints.
The most complex of these models also feature the 238 muscle fascicles associated with the 8 main muscle groups of the lumbar spine necessary to study the contribution of the lumbar spinal musculature to spinal motion. Simpler models incorporating two and seven of the main muscle groups of the lumbar spine are provided as well for completeness.
Read more about the model in the paper, freely downloadable at http://link.springer.com/article/10.1007%2Fs10237-011-0290-6.
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September 2011 Addendum
Click on the "Downloads" link to the left for downloads related to more recent work.
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September 2012 Addendum
The Constrained Lumbar Spine Model does not require any of the files uploaded after the creation of the Constrained Lumbar Spine Model project. The .vtp files (and descriptions) are included here for the benefit of those of you who wish to create your own model that has origins shifted to the center of the bones since this typically saves a number of transformations. Many apologies for any confusion(!).
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March 2014 Addendum
(1)
This model was build with OpenSim 2+. Version 3+ will not allow you to use periods (.) in your variable names. Unfortunately, a bunch of the variables used (muscles mainly) have periods in the names so it will throw an error if you try and run it in OpenSim version 3+. To fix this, either use version 2+, OR, rename the variables appropriately.
(2)
We have all graduated and are no longer actively working on this project (we haven't been working on it since the end of 2011 actually). At this point, you probably know more than us about OpenSim so we apologize in advance if our support is subpar.
(3)
The complex mode is not meant to be run straight out of the box. It has almost 250 muscles after all and unless you have a super computer, running CMC, or FD on it is going to bring up the rainbow ball of death on your computer.
Rather, it's meant to be a reference for those of you who intend to build up your own model. My advice would be to start with the simple 4 fascicle model, get it to work, then incrementally build up from there using the parameters provided in our model as a starting point. Copy-Paste is your friend here. :)
(4)
If this is your very first OpenSim project, I strongly _strongly_ *strongly* suggest that you go through the examples provided with the OpenSim version you just downloaded and understand how they work. This will save you months of pain down the road. | |
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Activity Percentile: 87.02 Registered: 2010-11-04 02:25 |
Force Field X
- Force Field X is a group of open source (GPL v. 3), platform independent (Java Runtime Environment) modules for molecular biophysics. Key methods include:
Polarizable AMOEBA force fields
Particle-mesh Ewald electrostatics
Generalized Kirkwood continuum electrostatics
X-ray and neutron crystallography refinement
Real space refinement for CryoEM
Methods for structure based drug design
for more information, see http://ffx.kenai.com | |
Activity Percentile: 86.26 Registered: 2012-02-04 21:49 |
Specimen-Specific Models of the Healthy Knee
- As part of research funded by the National Institutes of Health, National Institute of Biomedical Imaging and Bioengineering (NIBIB), investigators at the University of Denver Center for Orthopaedic Biomechanics have made available a repository of experimental, image, and computational modeling data from mechanical testing of natural human knee biomechanics. It is uncommon for such a comprehensive dataset to be obtained. Therefore, we have made this repository available to assist the greater research community interested in the complexities and pathologies of knee health and mechanical function. Data are provided for 7 human knees (5 cadaveric subjects) and fall under two categories:
Image Data and Experimental & Computational Modeling Data.
Additional details about the data can be found at:
http://ritchieschool.du.edu/research/centers-institutes/orthopaedic-biomechanics/downloads/natural-knee-data/
This repository of natural knee data has been made available thanks to funding from the National Institutes of Health through National Institute of Biomedical Imaging and Bioengineering R01-EB015497. | |
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Registered: 2008-06-12 23:15 |
Reference Models for Multi-Layer Tissue Structures
- This project aims to establish the founding knowledge, data and models for the mechanics of multi-layer tissue structures of the limbs, particularly of the lower and upper legs and arms. The activity is targeted to promote scientific research in layered tissue structures and allow reliable virtual surgery simulations for clinical training and certification.
This research and development project titled “Reference Models for Multi-Layer Tissue Structures" was conducted by the Cleveland Clinic Foundation and was made possible by a contract vehicle which was awarded and administered by the U.S. Army Medical Research & Materiel Command under award number: W81XWH-15-1-0232. The views, opinions and/or findings contained in this website are those of the authors and do not necessarily reflect the views of the Department of Defense and should not be construed as an official DoD/Army position, policy or decision unless so designated by other documentation. No official endorsement should be made. | |
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Registered: 2015-08-24 12:54 |
Simulation of Constrained Musculoskeletal Systems in Task Space
- Objective: This work proposes an operational task space formalization of constrained musculoskeletal systems, motivated by its promising results in the field of robotics.
Methods: The change of representation requires different algorithms for solving the inverse and forward dynamics simulation in the task space domain. We propose an extension to the Direct Marker Control and an adaptation of the Computed Muscle Control algorithms for solving the inverse kinematics and muscle redundancy problems respectively.
Results: Experimental evaluation demonstrates that this framework is not only successful in dealing with the inverse dynamics problem, but also provides an intuitive way of studying and designing simulations, facilitating assessment prior to any experimental data collection.
Significance: The incorporation of constraints in the derivation unveils an important extension of this framework towards addressing systems that use absolute coordinates and topologies that contain closed kinematic chains. Task space projection reveals a more intuitive encoding of the motion planning problem, allows for better correspondence between observed and estimated variables, provides the means to effectively study the role of kinematic redundancy and, most importantly, offers an abstract point of view and control, which can be advantageous towards further integration with high level models of the precommand level.
Conclusion: Task-based approaches could be adopted in the design of simulation related to the study of constrained musculoskeletal systems.
The source code of the project can be found at: https://github.com/mitkof6/opensim-task-space.git
The new API of task space and constraint projection for OpenSim V4.0 is available at: https://github.com/mitkof6/task-space
<iframe width="560" height="315" src="https://www.youtube.com/embed/jfE14iWRZDs" frameborder="0" allow="autoplay; encrypted-media" allowfullscreen></iframe> | |
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Registered: 2017-08-28 12:06 |
Muscle contributions to mass center accelerations over a range of running speeds
- These simulations were created using OpenSim and the workflow included Scale, Inverse Kinematics (IK), Reduced Residual Algorithm (RRA), Computed Muscle Control (CMC), and Induced Acceleration Analysis (IAA). The following resources provide instructions for using these tools and information on how to generate and evaluate musculoskeletal simulations:
• OpenSim User's Guide | http://stanford.io/17cia3U
• OpenSim Support Webpage | http://stanford.io/17ciwrn
• Webinar on Simulations of Running | http://bit.ly/oDIUOa
<object width="500" height="375"><param name="allowfullscreen" value="true" /><param name="allowscriptaccess" value="always" /><param name="movie" value="//vimeo.com/moogaloop.swf?clip_id=45852110&force_embed=1&server=vimeo.com&show_title=1&show_byline=1&show_portrait=1&color=00adef&fullscreen=1&autoplay=0&loop=0" /><embed src="//vimeo.com/moogaloop.swf?clip_id=45852110&force_embed=1&server=vimeo.com&show_title=1&show_byline=1&show_portrait=1&color=00adef&fullscreen=1&autoplay=0&loop=0" type="application/x-shockwave-flash" allowfullscreen="true" allowscriptaccess="always" width="500" height="375"></embed></object> <p><a href="http://vimeo.com/45852110">Muscle contributions to fore-aft and vertical body mass center accelerations over a range of running speeds</a> from <a href="http://vimeo.com/samner">Sam Hamner</a> on <a href="http://vimeo.com">Vimeo</a>.</p>
The goal of this study was to determine how muscles and arm swing affect dynamics of the body at different running speeds. Specifically, we determined how muscles contribute to mass center accelerations during the stance phase of running, and how the arms act to counterbalance the motion of the legs. We achieved this goal by creating and analyzing muscle-driven, forward dynamic simulations of ten subjects running across a range of speeds: 2 m/s, 3 m/s, 4 m/s, and 5 m/s. An induced acceleration analysis determined the contribution of each muscle to mass center accelerations. Our simulations also included arm motion, allowing us to investigate the contributions of arm swing to running dynamics. These simulations use experimental data as inputs, so we also collected data to characterize joint angles, joint moments, and ground reaction forces at different running speeds. | |
Activity Percentile: 80.53 Registered: 2011-01-28 22:11 |
Topological Methods for Exploring Low-density States in Folding Pathways
- In this paper, we develop a computational approach to explore the relatively low populated transition or intermediate states in biomolecular folding pathways based on a topological data analysis tool, Mapper. We applied Mapper to simulation data from large-scale distributed computing to provide structural evidence on multiple intermediate states of the unfolding and refolding of an RNA hairpin with a GCAA tetraloop. This project contains Mapper, the RNA conformations (in contact map format), and instructions to reproduce results from this paper.
<b> Motivation: </b> Characterization of transient intermediate or transition states is crucial for the description of biomolecular folding pathways, which is however difficult in both experiments and computer simulations. Such transient states are typically of low population in simulation samples. Even for simple systems such as RNA hairpins, recently there are mounting debates over the existence of multiple intermediate states.
<b> More about Mapper and the computational approach </b> The method is inspired by the classical Morse theory in mathematics which characterizes the topology of high dimensional shapes via some functional level sets. In this paper we exploit a conditional density filter which enables us to focus on the structures on pathways, followed by clustering analysis on its level sets, which helps separate low populated intermediates from high populated uninteresting structures.
The method is effective in dealing with high degree of heterogeneity in distribution, capturing structural features in multiple pathways, and being less sensitive to the distance metric than nonlinear dimensionality reduction or geometric embedding methods. The methodology described in this paper admits various implementations or extensions to incorporate more information and adapt to different settings, which thus provides a systematic tool to explore the low density intermediate states in complex biomolecular folding systems. | |
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Activity Percentile: 79.77 Registered: 2008-12-10 00:53 |
182 projects in result set. Displaying 20 per page. Projects sorted by alphabetical order.
<1> <2> <3> <4> <5> <6> <7> <8> <9> <10>