Online Tutorials
Online tutorials for software developed by MMBioS partners are listed here. More information on these packages plus others can be found on the Software page.
For tutorial presentations given by MMBioS investigators, see the Tutorial Presentations page.
Online tutorials are available for:
- BioNetGen
- CellOrganizer
- GTKDynamo
- MCell
- ProDy
Software
The following software tools and services, developed by MMBioS partners, are freely available to the biomedical community. We ask that any publications resulting from their use include an acknowledgement.
AlignTK
AlignTK is an image alignment toolkit. It is designed for batch-oriented alignment of a large number of 2-D images in either 2 or 3-dimensions. Although it has been applied most extensively to electron-microscopy (EM) images of neural tissue, the package can be used with arbitrary grayscale images. Multiple image formats are supported.
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ANM
ANM (Anisotropic network model) t is a simple tool for predicting the collective motions of molecular systems introduced using Elastic Network Models (ENM) and normal mode analysis. The biomolecular system is represented as a network, or graph, the nodes of which are the residues and the springs are their interactions. The model helps elucidate the intrinsic dynamics of proteins and their complexes and make inferences on functional mechanisms.
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BioNetGen
BioNetGen is software for the specification and simulation of rule-based models of biochemical systems, including signal transduction, metabolic, and genetic regulatory networks.
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CellBlender
CellBlender is a Blender addon for creation, simulation, visualization, and analysis of realistic 3D Cell Models. CellBlender leverages the full-featured 3D content creation capabilities of Blender to support a rich environment for the creation of simulation-ready, biophysically realistic models of the microscopic structure and biochemical function of cells.
CellBlender is fully functional with MCell and partially functional with SBML (http://sbml.org). We invite the computational cell biology community to contribute to the project, adding features and support for their favorite simulation environments.
More: | >>Home page | >>Downloads | >>Forum |
CellOrganizer
The CellOrganizer project provides tools for
- learning generative models of cell organization directly from images
- storing and retrieving those models in XML files
- synthesizing cell images (or other representations) from one or more models
Model learning captures variation among cells in a collection of images. Images used for model learning and instances synthesized from models can be two- or three-dimensional static images or movies.
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GAMELAN
GamelanPy is a Python implementation of the GAMELAN (GrAphical Models of Energy LANdscapes) algorithm. This algorithm is for learning a sparse Gaussian Mixture Model for structural fluctuations of a protein, but can also be used for other data where the original data can be assumed to follow a mixture of Gaussian distributions. GamelanPy supports options for sub-sampling methods for scalability and nonparanormal distributions for richer family of distributions than Gaussians. This package contains a pure python library and scripts for the command-line usages.
More information on GAMELAN can be found in this paper: Generative Models of Conformational Dynamics
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iGNM
Gaussian network model (GNM) is a simple yet powerful model for investigating the dynamics of proteins and their complexes. GNM analysis became a broadly used method for assessing the conformational dynamics of biomolecular structures with the development of a user-friendly interface and database, iGNM, in 2005. We present here an updated version, iGNM 2.0 http://gnmdb.csb.pitt.edu/, which covers more than 95% of the structures currently available in the Protein Data Bank (PDB). Advanced search and visualization capabilities, both 2D and 3D, permit users to retrieve information on inter-residue and inter-domain cross-correlations, cooperative modes of motion, the location of hinge sites and energy localization spots. The ability of iGNM 2.0 to provide structural dynamics data on the large majority of PDB structures and, in particular, on their biological assemblies makes it a useful resource for establishing the bridge between structure, dynamics and function.
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GTKDynamo
GTKDynamo is free/open source software which, together with pDynamo, transforms PyMOL into a powerful interface for molecular modeling. The interface has been designed to facilitate determining reaction pathways in biological systems, specially using hybrid QC/MM (or QM/MM) methods. Pymol has been chosen as a graphical interface to pDynamo because it has a python API with wide documentation available.
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MCell
MCell is a Monte Carlo reaction-diffusion simulator for modeling computational microphysiology in arbitrarily complex 3D spatial geometries.
As a modeling tool, MCell creates realistic simulations of cellular signaling in the complex 3-D subcellular microenvironment in and around living cells -- what we call cellular microphysiology. At such small subcellular scales the familiar macroscopic concept of concentration is not useful and stochastic behavior dominates. MCell uses highly optimized Monte Carlo algorithms to track the stochastic behavior of discrete molecules in space and time as they diffuse and interact with other discrete effector molecules (e.g. ion channels, enzymes, transporters) heterogeneously distributed within the 3-D geometry of the subcellular environment.
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>> Forum |
ProDy
ProDy is a free and open-source Python package for protein structural dynamics and sequence evolution analysis. It is designed as a flexible and responsive API suitable for interactive usage and application development. NMWiz, a VMD plugin GUI, also accompanies ProDy for streamlining protein dynamics analysis calculations and enabling comparative visual analysis of experimental and theoretical data.
With ProDy, you can perform principal component analysis of heterogeneous X-ray structures, NMR models, and MD snapshots. Protein dynamics can be modeled using normal mode analysis of anisotropic network model with optional distance and property dependent force constants. Powerful and customizable atom selections allow for contact identification and matching, superposing, and comparing multiple structures/chains. Newest additions to ProDy include fast and flexible features for analysis of sequence evolution and its comparison to protein functional dynamics.
More: | >> Home page | >> Tutorials | >> Downloads |
Rhapsody
Rhapsody is a web tool for pathogenicity prediction of human missense variants based on sequence, structure and dynamics of proteins.
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SWiFT-IR
SWiFT-IR uses Signal Whitening Fourier Transform Image Registration technique to achieve high precision image matching which is very robust to typical image distortions and defects. This high quality image matching in turn allows a hierarchical model based approach for the deformable registration of very deep image serial-section electron microscopy datasets. SWiFT-IR is also useful with other forms of grayscale and color imagery.
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WE
The "weighted-ensemblizer" is an automated tool for setting up WESTPA-based weighted-ensemble (WE) simulations for existing MCell models. Because MCell models can be complex and expensive to simulate, WE can provide enhanced sampling for targeted observables of interest, such as the concentration of a certain species in a specified location, by using a strategy of replicating and pruning trajectories. The alpha-version webserver was developed by Rory Donovan, a student in the Zuckerman research group supported by the MMBioS resource.
For more information, see: Donovan RM, Tapia JJ, Sullivan DP, Faeder JR, Murphy RF, Dittrich M, Zuckerman DM. (2016) Unbiased Rare Event Sampling in Spatial Stochastic Systems Biology Models Using a Weighted Ensemble of Trajectories. PLoS Comput Biol 12(2): e1004611. doi: 10.1371/journal.pcbi.1004611WESTPA
WESTPA (the Weighted Ensemble Simulation Toolkit with Parallelization and Analysis) is an open-source software package that provides a high-performance framework for carrying out extended-timescale simulations of rare events with rigorous kinetics using the weighted ensemble algorithm of Huber and Kim (1996). The software also includes options for further enhancing the sampling efficiency through reassignment of weights according to either equilibrium or nonequilibrium steady state, and a plugin for using a weighted ensemble-based string method. The software is designed to interface with any stochastic simulation engine, including but not limited to molecular dynamics (e.g. AMBER, GROMACS, and NAMD), Monte Carlo codes, BioNetGen, and MCell.
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Research Highlights
The Bahar (TR&D1) and Sorkin (DBP3) labs published an article in the Journal of Biological Chemistry, selected as one of JBC's "Editors' Picks. Our results demonstrate a direct coupling between conformational dynamics of DAT, functional activity of the transporter and its oligomerization leading to endocytosis. The high specificity of such coupling for DAT makes the TM4-9 hub a new target for pharmacological modulation of DAT activity and subcellular localization. (Read more)
Differences in the intrinsic spatial dynamics of the chromatin contribute to cell differentiation
Comparison with RNA-seq expression data reveals a strong overlap between highly expressed genes and those distinguished by high mobilities in the present study, in support of the role of the intrinsic spatial dynamics of chromatin as a determinant of cell differentiation. (Read more)
Nanoscale co-organization and coactivation of AMPAR, NMDAR, and mGluR at excitatory synapses
Work by TR&D2 Investigators and collaborators provide insights into the nanometer scale organization of postsynaptic glutamate receptors using a combination of dual-color superresolution imaging, electrophysiology, and computational modeling. (Read more)
Parallel Tempering with Lasso for model reduction in systems biology
TR&D3 Investigators and collaborators develop PTLasso, a Bayesian model reduction approach that combines Parallel Tempering with Lasso regularization, to automatically extract minimal subsets of detailed models that are sufficient to explain experimental data. On both synthetic and real biological data, PTLasso is an effective method to isolate distinct parts of a larger signaling model that are sufficient for specific data. (Read more)
Image-derived models of cell organization changes during differentiation and drug treatments
Our work on modeling PC12 cells undergoing differentiation into neuron-like morphologies (under C&SP11, completed) has been published in Molecular Biology of the Cell. We have also made the large dataset of 3D images collected in that study available through Dryad. (Read more)
Monoamine transporters: structure, intrinsic dynamics and allosteric regulation
T&RD1 investigators Mary Cheng and Ivet Bahar published an invited review article in Nature Structural & Molecular Biology, addressing recent progress in the elucidation of the structural dynamics of MATs and their conformational landscape and transitions, as well as allosteric regulation mechanisms. (Read more)
Trimerization of dopamine transporter triggered by AIM-100 binding
The Bahar (TR&D1) and Sorkin (DBP3) labs explored the trimerization of dopamine transporter (DAT) triggered by a furopyrimidine, AIM-100, using a combination of computational and biochemical methods, and single-molecule live-cell imaging assays. (Read more)
Pre-post synaptic alignment through neuroligin-1 tunes synaptic transmission efficiency
TR&D2 investigators and collaborators describe organizing role of neuroligin-1 to align post-synaptic AMPA Receptors with pre-synaptic release sites into trans-synaptic “nano-columns” to enhance signaling.(Read more)
Inferring the Assembly Network of Influenza Virus
In an article in PLoS Computational Biology, MMBioS TR&D4 members Xiongto Ruan and Bob Murphy collaborated with Seema Lakdawala to address this question of the assembly network of the Influenza virus.(Read more)
Our findings highlight an important mechanism by which proteins genetically implicated in Parkinson’s disease (PD; PINK1) and frontotemporal dementia (FTD; VCP) interact to support the health and maintenance of neuronal arbors.(Read more)
Improved methods for modeling cell shape
In a recent paper in Bioinformatics, Xiongtao Ruan and Bob Murphy of TR&D4 addressed the question of how best to model cell and nuclear shape.(Read more)
New tool to predict pathogenicity of missense variants based on structural dynamics: RHAPSODY
We demonstrated that the analysis of a protein’s intrinsic dynamics can be successfully used to improve the prediction of the effect of point mutations on a protein functionality. This method employs ANM/GNM tools (Read more)
New method for investigating chromatin structural dynamics.
By adapting the Gaussian Network Model (GNM) protein-modeling framework, we were able to model chromatin dynamics using Hi-C data, which led to the identification of novel cross-correlated distal domains (CCDDs) that were found to also be associated with increased gene co-expression. (Read more)
Structural elements coupling anion conductance and substrate transport identified
We identified an intermediate anion channeling state (iChS) during the global transition from the outward facing (OF) to inward facing state (IFS). Our prediction was tested and validated by experimental study conducted in the Amara lab (NIMH). Critical residues and interactions were analyzed by SCAM, electrophysiology and substrate uptake experiments (Read more)
Integrating MMBioS technologies for multiscale discovery
TR&D teams driven by individual DBPs are naturally joining forces, integrating their tools to respond to the needs of the DBP, and creating integrative frameworks for combining structural and kinetic data and computing technologies at multiple scales. (Read more)
Large scale visualization of rule-based models.
Signaling in living cells is mediated through a complex network of chemical interactions. Current predictive models of signal pathways have hundreds of reaction rules that specify chemical interactions, and a comprehensive model of a stem cell or cancer cell would be expected to have many more. Visualizations of rules and their interactions are needed to navigate, organize, communicate and analyze large signaling models. (Read more)
Integration of MCellR into MCell/CellBlender
Using spatial biochemical models of SynGAP/PSD95, MMBioS investigators were able to merge the MCellR code-base with the MCell code-base and validate its utility and correctness of this sophisticated technology now easily accessible through the MCell/CellBlender GUI. (Read more)
Causal relationships of spatial distributions of T cell signaling proteins
The idea is to identify a relationship in which a change in the concentration of one protein in one cell region consistently is associated with a change in the concentration of another protein in the same or a different region. We used the data from our Science Signaling paper reported last year to construct a model for T cells undergoing stimulation by both the T cell receptor and the costimulatory receptor. (Read more...)
BioNetGen modeling helps reveal immune system response decision
To attack or to let be is an important decision that our immune systems must make to protect our bodies from foreign invaders or protect bodily tissues from an immune attack. Using modeling and experiments, we have painted a sharper picture of how T cells make these critical decisions. (Read more)
Tools for determining the spatial relationships between different cell components
An important task for understanding how cells are organized is determining which components have spatial patterns that are related to each other.Read more
Pipeline for creation of spatiotemporal maps
Using a combination of diffeomorphic methods and improved cell segmentation, we developed a CellOrganizer pipeline for use in DPB4 to construct models of the 4D distributions of actin and 8 of its regulators during the response of T cells to antigen presentation. Read more
Multi-scale Hybrid Methodology
The hybrid methodology, coMD, that we have recently developed [1] has been recently extended to construct the energy landscape near the functional states of LeuT (Fig 1) [2]. This is the first energy landscape constructed for this NSS family member. Read more
Insights into the cooperative dynamics of AMPAR
Comparative analysis of AMPAR and NMDAR dynamics reveals striking similarities, opening the way to designing new modulators of allosteric interactions. Read more
Improved Sampling of Cell-Scale Models using the WE Strategy
The WE strategy for orchestrating a large set of parallel simulations has now been extended to spatially resolved cell-scale systems. The WESTPA implementation of WE has been used to control MCell simulations, including models built using a BioNetGen-CellOrganizer pipeline for situating complex biochemistry within spatially realistic cell models. Read more
Anatomy and Function of an Excitatory Network in the Visual Cortex
MMBioS researcher Greg Hood’s collaboration with Wei-Chung Allen Lee of Harvard University and R. Clay Reid of the Allen Institute for Brain Science concerning the reconstruction of an excitatory nerve-cell network in the mouse brain cortex at a subcellular level using the AlignTK software has been published in Nature. Read more
Molecular Mechanism of Dopamine Transport by hDAT
Dopamine transporters (DATs) control neurotransmitter dopamine (DA) homeostasis by reuptake of excess DA, assisted by sodium and chloride ions. The recent resolution of DAT structure (dDAT) from Drosophila permits us for the first time to directly view the sequence of events involved in DA reuptake in human DAT (hDAT). Read more
Synaptic Facilitation Revealed
An investigation of several mechanisms of short-term facilitation at the frog neuromuscular junction concludes that the presence of a second class of calcium sensor proteins distinct from synaptotagmin can explain known properties of facilitation. Read more
Sparse Graphical Models of Protein:Protein Interactions
DgSpi is a new method for learning and using graphical models that explicitly represent the amino acid basis for interaction specificity and extend earlier classification-oriented approaches to predict ΔG of binding. Read more
Advancing Parallel Bio-simulations
A new non-Markovian analysis can eliminate bias in estimates of long-timescale behavior, such as the mean first-passage time for the dissociation of methane molecules in explicit solvent. Read more