Searching across hundreds of databases
Integrated Models is a virtual database currently indexing computational models from: CellML, ModelDB, Open Source Brain, SimTK.
(last updated: Nov 23, 2022)
Data or Model Models| Database | Model Name | Simulator Software | Model Type | Neurons | Neurotransmitters | Receptors | ||||
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CellML | Generic human stomach scaffold | CellML | ||||||||
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ModelDB | Gamma oscillations in hippocampal interneuron networks (Bartos et al 2002) | NEURON | Realistic Network | GabaA | I Na,t, I K | Activity Patterns, Oscillations, Synchronization, Synaptic Integration | To examine whether an interneuron network with fast inhibitory synapses can act as a gamma frequency oscillator, we developed an interneuron network model based on experimentally determined properties. In comparison to previous interneuron network models, our model was able to generate oscillatory activity with higher coherence over a broad range of frequencies (20-110 Hz). In this model, high coherence and flexibility in frequency control emerge from the combination of synaptic properties, network structure, and electrical coupling. | Jonas, Peter [Peter.Jonas at ist.ac.at] | ||
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ModelDB | Facilitation by residual calcium (Stockbridge, Hines 1982) | NEURON | Neuromuscular Junction | Facilitation | The residual calcium hypothesis is compatible with facilitation of transmitter release from the neuromuscular junction. | Hines, Michael [Michael.Hines at Yale.edu] | ||||
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ModelDB | Correcting space clamp in dendrites (Schaefer et al. 2003 and 2007) | NEURON | Neuron or other electrically excitable cell | Neocortex M1 L5B pyramidal pyramidal tract GLU cell | I K, I K,leak, I M, I Potassium | Parameter Fitting, Influence of Dendritic Geometry, Detailed Neuronal Models | In voltage-clamp experiments, incomplete space clamp distorts the recorded currents, rendering accurate analysis impossible. Here, we present a simple numerical algorithm that corrects such distortions. The method enabled accurate retrieval of the local densities, kinetics, and density gradients of somatic and dendritic channels. The correction method was applied to two-electrode voltage-clamp recordings of K currents from the apical dendrite of layer 5 neocortical pyramidal neurons. The generality and robustness of the algorithm make it a useful tool for voltage-clamp analysis of voltage-gated currents in structures of any morphology that is amenable to the voltage-clamp technique. | Schaefer, Andreas T [andreas.schaefer at crick.ac.uk] | ||
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ModelDB | Sleep-wake transitions in corticothalamic system (Bazhenov et al 2002) | C or C++ program | Realistic Network | Thalamus geniculate nucleus/lateral principal GLU cell, Thalamus reticular nucleus GABA cell, Neocortex L5/6 pyramidal GLU cell | GabaA, GabaB, AMPA, NMDA | I Na,t, I L high threshold, I T low threshold, I K,leak, I M, I K,Ca | Depression, Oscillations, Synchronization, Spatio-temporal Activity Patterns, Short-term Synaptic Plasticity, Sleep | The authors investigate the transition between sleep and awake states with intracellular recordings in cats and computational models. The model describes many essential features of slow wave sleep and activated states as well as the transition between them. | Bazhenov, Maxim [Bazhenov at Salk.edu] | |
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ModelDB | Active dendrites and spike propagation in a hippocampal interneuron (Saraga et al 2003) | NEURON | Neuron or other electrically excitable cell | Hippocampus CA1 interneuron oriens alveus GABA cell | AMPA | I Na,t, I A, I K, I h | Action Potential Initiation, Dendritic Action Potentials, Active Dendrites, Influence of Dendritic Geometry, Detailed Neuronal Models, Action Potentials | We create multi-compartment models of an Oriens-Lacunosum/Moleculare (O-LM) hippocampal interneuron using passive properties, channel kinetics, densities and distributions specific to this cell type, and explore its signaling characteristics. We find that spike initiation depends on both location and amount of input, as well as the intrinsic properties of the interneuron. Distal synaptic input always produces strong back-propagating spikes whereas proximal input could produce both forward and back-propagating spikes depending on the input strength. Please see paper for more details. | Saraga, Fernanda [Fernanda.Saraga at utoronto.ca] | |
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ModelDB | CA1 pyramidal neuron: effects of Ih on distal inputs (Migliore et al 2004) | NEURON | Dendrite | Hippocampus CA1 pyramidal GLU cell | AMPA | I Na,t, I A, I K, I h | Action Potential Initiation, Dendritic Action Potentials, Synchronization, Active Dendrites, Detailed Neuronal Models, Action Potentials | NEURON mod files from the paper: M. Migliore, L. Messineo, M. Ferrante Dendritic Ih selectively blocks temporal summation of unsynchronized distal inputs in CA1 pyramidal neurons, J.Comput. Neurosci. 16:5-13 (2004). The model demonstrates how the dendritic Ih in pyramidal neurons could selectively suppress AP generation for a volley of excitatory afferents when they are asynchronously and distally activated. | Migliore, Michele [Michele.Migliore at Yale.edu] | |
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ModelDB | Irregular oscillations produced by cyclic recurrent inhibition (Friesen, Friesen 1994) | NEURON | Connectionist Network | Activity Patterns, Bursting, Temporal Pattern Generation, Oscillations, Simplified Models | Model of recurrent cyclic inhibition as described on p.119 of Friesen and Friesen (1994), which was slightly modified from Szekely's model (1965) of a network for producing alternating limb movements. | Carnevale, Ted [Ted.Carnevale at Yale.edu] | ||||
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ModelDB | Local variable time step method (Lytton, Hines 2005) | NEURON | Methods | The local variable time-step method utilizes separate variable step integrators for individual neurons in the network. It is most suitable for medium size networks in which average synaptic input intervals to a single cell are much greater than a fixed step dt. | Hines, Michael [Michael.Hines at Yale.edu] | |||||
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SimTK | Side Chain Placement | neuromuscular model | Sice chain placement software | |||||||
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SimTK | Divide and Conquer Coarse-Grain Molecular Modeling | neuromuscular model | The divide and conquer algorithm [1-3] would make it easier to implement frequent topology changes (by adding or constraining degrees of freedom) in coarse grain molecular models. This approach may be specially useful in situations where it is desirable to adaptively manipulate/change the coarse grain model locally, during the course of simulation. Simulation Example: https://simtk.org/docman/view.php/327/1350/pend.gif Current interface with Molmodel: https://simtk.org/docman/view.php/327/1380/molmodelDCA01.pdf [1] R. Featherstone, 1999a. A Divide-and-Conquer Articulated-Body Algorithm for Parallel O(log(n)) Calculation of Rigid-Body Dynamics. Part 1: Basic Algorithm. Int. J. Robotics Research, vol. 18, no. 9, pp. 867-875, 1999. [2] R. Featherstone, 1999b. A Divide-and-Conquer Articulated-Body Algorithm for Parallel O(log(n)) Calculation of Rigid-Body Dynamics. Part 2: Trees, Loops and Accuracy. Int. J. Robotics Research, vol. 18, no. 9, pp. 876-892, 1999. [3] Rudranarayan M. Mukherjee and Kurt S. Anderson, A Logarithmic Complexity Divide-and-Conquer Algorithm for Multi-flexible Articulated Body Dynamics, Journal of Computational and Nonlinear Dynamics, January 2007, Volume 2, Issue 1, pp. 10-21 | |||||||
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SimTK | The DKR LTM HIP Prosthesis | neuromuscular model | The true key problem of implant fixation in THR is stress distribution, i.e. load transmission between bone and implant. The closer the load transfer is to the original physiological situation, the easier the adaptation of the periprosthetic bone to the new biomechanical conditions after implantation of the stem the safer is its long lasting fixation. Based on reason and experience it would seem apparent that we must accommodate the natural and unchanging laws of normal bone behavior by implant designing and fixation technique that simulate as closely as possible the normal joint mechanics and physiology that control and sustain normal hip function. With loss of the normal stress dispersing joint biomechanics in prosthetic replacement, however, the nature of the joint and the manner of stress distribution becomes purely mechanical and the subsequent physiological and structural integrity of the periprosthetic bone, and thus the stability of the implant, is entirely dependent on the mode of loading at the bone-prosthetic juncture. As a consequence of conjoining a nonviable, mechanical prosthetic device with a viable, physiologically active bone structure, the etiology of implant failure is both mechanical and physiological. Mechanical, due to the common failure to provide a mechanically sound design related connection at the nonviable bone-prosthetic juncture to counter the severe displacement stresses generated by prosthetic replacement of the femoral head and neck | |||||||
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SimTK | Molecular Mechanics Clustering Tools | neuromuscular model | This project pools tools for clustering molecular mechanics and molecular dynamics data, with an emphasis on using these clusters in building discrete-state master equation models (e.g., Markov state models). There are many such tools available (developed in several research groups) which are to be combined here. | |||||||
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SimTK | Obstacle Set Muscle Path Modules | neuromuscular model | This project is a collection of SimTK-compatible C/C++ modules for representing the paths of muscles wrapping around underlying obstacles. The modules derive from algorithms that represent each muscle path as an elastic band wrapping around simple geometric shapes such as a sphere, cylinder, double-cylinder, or sphere-capped cylinder. The modules permit calculation of such quantities as a muscle\\'s length, line of action, and moment arm within a kinematic skeletal model. | |||||||
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SimTK | Mechanical Analysis of Osteotomy | neuromuscular model | This project allow users to test mechanical conditions on geometric model of human musculosceletal system. It provides analysis of lower limb biomechanics before and after osteotomy. | |||||||
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SimTK | RNA dataset and multi-scale knowledge-based potential | neuromuscular model | This project is made of three parts. It first contains a collection of RNA Replica-Exchange Molecular Dynamics generated decoys to test RNA force-fields and simulation methodology. The second part is made by a collection of MD program input files to perform minimization and/or molecular dynamics simulation with the knowledge-based force field we developed. Available as Gromacs4 files for the moment, both all-atom and coarse-grained simulation are possible. The last part is a database from which the filtered non-redundant dataset extracted for building the knowledge-based potential can be browsed and queried. Decoy structures, KB potential and MD simulation setup are avaiable in the download section. | |||||||
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SimTK | Solvated alanine dipeptide - Thermodynamics and kinetics datasets | neuromuscular model | This project is a collection of datasets of the alanine dipeptide (more specifically, terminally-blocked alanine peptide) in explicit solvent. These datasets cover both thermodynamic simulations (parallel tempering) and kinetic simulations (Hamiltonian dynamics trajectories) useful for testing algorithms analyzing the thermodynamics and kinetics of biomolecular systems. This model system has already been used in several research papers. | |||||||
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SimTK | Reserved for Simbios Center use | neuromuscular model | This project is reserved for use by the Simbios center for centralized commentary on its various software offerings, consisting of SimTK (a toolkit for developers of biosimulation applications) and Simbios Applications (a collection of such applications produced by or in collaboration with Simbios). | |||||||
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SimTK | Baseball Batting | neuromuscular model | To enable players of all ages to increase the likelihood of successful outcomes, of making solid contact, while attempting to hit a pitched Baseball by ensuring they are Biomechanically in the best position to do so. | |||||||
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SimTK | Mechanical effort predicts postural responses | neuromuscular model | This project provides more detailed information on the research article entitled "Mechanical effort predicts the selection of ankle over hip strategies in non-stepping postural responses" published in journal of neurophysiology. More specifically, the motion capture data of perturbed standing and software to predict the measured postural response is shared. This information is on the one hand usefull to reproduce the experimental and simulation results. On the other hand, the software can be used as a basis for more detailed predictive simulations of postural control. |
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