Models, Tools & Databases
Content posted to this wiki are contributions made by the IMAG research community.
Any questions or concerns should be directed to the individual authors. Full disclaimer statement found here.
GranSim is a hybrid agent-based computational model (ABM) that describes the formation and function of a granuloma during Mycobacterium tuberculosis infection in the lung. Although granulomas are 3D entities, due to the high computational costs associated to simulate a 3D version, GranSim has been developed and curated since 2004 only in 2D.
3D Hybrid Multi-scale Model of CRPC progression
Prostate cancer (PCa) is the most commonly diagnosed malignancy and the second leading cause of cancer-related death in American men. Androgen deprivation therapy (ADT) has become a standard treatment strategy for advanced PCa. Although a majority of patients initially respond to ADT well, most of them will eventually develop castration-resistant PCa (CRPC).
A Computational Pipeline to Predict Cardiotoxicity:From the Atom to the Rhythm
In a new linkage, we connected atomistic scale information to protein, cell and tissue scales by predicting drug binding affinities and rates from simulation of ion channel and drug structure interactions and then used these values to model drug effects on the hERG channel.
A Gestalt inference model for auditory scene segregation
The auditory stream segregation model leverages the multiplexed and non-linear representation of sounds along an auditory hierarchy and learns local and global statistical structure naturally emergent in natural and complex sounds.
A multiscale model via single-cell transcriptomics reveals robust patterning mechanisms during early mammalian embryo development
During early mammalian embryo development, a small number of cells make robust fate decisions at particular spatial locations in a tight time window to form inner cell mass (ICM), and later epiblast (Epi) and primitive endoderm (PE).
A software to develop personalized treatment strategies for COVID-19
The main goal of this project is to develop a software based on a novel mathematical framework that uses individual COVID-19 patient data to obtain accurate personalized treatment strategies.
Active learning of cortical connectivity from two-photon imaging data
Cardio-ventilatory coupling: sensory input in synchronizing inspiratory-onset activity.
The respiratory control system produces the rhythm that underlies breathing. But this rhythm is not restricted to just the respiratory system.
Cross-Spectral Factor Analysis
The purpose of this resource is a computational framework of a machine learning technique to analyze multi-region electrophysiological recordings and learn electrical connectome networks that are related to outcomes of interest (e.g., mouse model of depression). The learned networks are visualizable and explainable.
The lung model integrates mechanics and cell models. The mechanics model utilizes imaging-based, high-fidelity computational technologies for three-dimensional (3D) fluid and solid mechanical systems to predict airflow-induced shear stress, tissue stress and particle deposition at a local level in the realistic human lung models.
Dynamic Regularity Extraction (D-REX) Model
The D-REX model is designed for exploring the computational mechanisms in the brain involved in statistical regularity extraction from dynamic sounds.
GranSim, the Agent-based model (ABM) describing tuberculosis (TB) granuloma formation and function in the lung, was developed based on four basic concepts: an environment (section of the lung parenchyma), agents (immune cells), ABM rules that govern the agents and their interactions, and the time-step (Δt) used to update events.
Hippocampal Large-Scale Model
The project is to develop a full-scale model of rat hippocampus using compartmental models of individual neurons. The code available can be used to construct the connectivity for an entorhinal-dentate network with lateral and medial entorhinal cortical cells as spike generators and compartmental models of dentate granule cells and basket cells.
Innate Immune Response Agent-based Model (IIRABM)
The Innate Immune Response Agent-Based Model (IIRABM) is a two-dimensional abstract representation of the human endothelial-blood interface. This abstraction is designed to model the endothelial-blood interface for a traumatic (in the medical sense) injury, and does so by representing this interface as the unwrapped internal vascular surface of a 2D projection of the termin
Microconnectomics of motor cortex: a multiscale computer model
We developed a model of primary motor cortex (M1) microcircuits  with over 10,000 biophysically detailed neurons and 30
Models of Protein Biomaterials
-Replica exchange molecular dynamics is used to develop a structure for the silk chimeras.
-MD is also used to explain the change in integrin folding associated with its activation due to interactions with inorganic surfaces
Modular design of multiscale models, with an application to the innate immune response to fungal respiratory pathogens
When completed, the model will have a web-based user interface that allows immunologists and other researchers to interact with the model, gain insights into the early stages of the infection and test potential alternative, host centric interventions.
Multi-fidelity surrogate models for skin growth
Tissue growth and remodeling (G&R) has been modeled in a continuum mechanics framework with an approach similar to plasticity named 'finite growth model'. Computationally, G&R has been simulated with custom finite element implementations.
Multiple granuloma model (MultiGran)
Hybrid multi-scale computational model that tracks whole-lung Mycobacterium tuberculosis infection and predicts factors that inhibit dissemination.
Multiscale Imaging-based Cluster Analysis (MICA) - bridging individual and population scales of the human lungs
MICA is an imaging clustering analysis method that employs imaging-based metrics at local and global scales of the human lungs constructed from 3D computed tomography (CT) lung images to identify homogeneous subgroups, known as clusters, in healthy, asthma and COPD populations.
Multiscale Model for Functionalized Nanocarrier Targeting for Drug Delivery
Multiscale Model of Platelet in Blood Flow
We will use an integrated Dissipative Particle Dynamics (DPD) and Coarse Grained Molecular Dynamics (CGMD) approach that allows platelets to continuously change their shape and synergistically activate by a biomechanical transductive linkage chain, interact with other blood constituents and clotting factors, aggregate, and interact and adhere to the blood vessels and
Multiscale model of the retina
The code and methodology presented here describe a computational model aimed at investigating the effects of current waveforms of electrical stimulation of the retina used in prosthetic devices aimed at restoring partial vision lost to retinal degenerative diseases.
Neuroanatomic Propagation of ALS within the Spinal Cord
Amyotrophic lateral sclerosis (ALS) is the most common Motor Neuron Disease. It is a progressive neurodegenerative disease that affects motor neurons in the brain and the spinal cord. The progressive degeneration of motor neurons in the spinal cord causes patients to lose their ability to control their muscle movement.
National Toxicology Program (NTP) Interagency Center for the Evaluation of Alternative Toxicological Methods (NICEATM)
Open Knee(s): virtual biomechanical representations of the knee joint
This resource is a project website to provide free access to three-dimensional finite element representations of the knee joint and open development of knee models for collaborative testing and use.
Physics-based mass action dynamics of central metabolism including regulation and thermodynamics
This is a physics-based model of central metabolism of Neurospora crassa, a filamentous fungi, in which physiologically reasonable rate constants are inferred from data and physical principles.
Polarization of the PLC/PKC pathway for chemotactic gradient sensing
These models are composed of partial differential equations and boundary conditions that model the receptor-mediated activation of phospholipase C (PLC) and protein kinase C (PKC) enzymes in mammalian cells. PLC hydrolyzes the membrane lipid, PIP2, to produce the lipid second messenger, diacylglycerol (DAG), which mediates PKC activation at the plasma membrane.
Reference Models for Multi-Layer Tissue Structures
This resource is the project website to provide fundamental data, open and freely accessible databases of tissue mechanical and anatomical properties, models of multi-layer tissue structures of musculoskeletal extremities.
Reproducibility in simulation-based prediction of natural knee mechanics
This project aims for understanding the influence of modelers’ approaches and decisions (essentially their art) throughout the lifecycle of modeling and simulation. It will demonstrate the uncertainty of delivering consistent simulation predictions when the founding data to feed into models remain the same.
The Reference Model for Disease Progression
The Reference Model is:
Virtual Population Obesity Prevention (VPOP) Labs: Computational, Multi-Scale Models for Obesity Solutions
3D Printer Designs for Clearing and Imaging Large Samples
3D printer designs for clearing and imaging mouse whole brains. Two designs are provided:
A) A falcon holder for clearing large samples is provided to clear in parallel up to 8 mouse whole brains using a 2L beaker.
A modular computational framework for medical digital twins
This paper presents a modular software design for the construction of computational modeling technology that will help implement precision medicine. In analogy to a common industrial strategy used for preventive maintenance of engineered products, medical digital
A statistical framework to assess cross-frequency coupling while accounting for confounding analysis effects
Between-brain-area functional influence from simultaneous population recordings
Neural representations of for instance task-relevant information are often distributed across multiple brain areas. These representations could have independent dynamics, or could influence each other.
Building analysis tools and a theory framework for inferring principles of neural computation from multi-scale organization in brain recordings
CellChat: Inference and analysis of cell-cell communication using CellChat
Inferring, clustering, and downstream analysis for cell-cell communications in scRNA-seq data.
Data and Model Sharing Group
Data and Model Sharing
My original text was lost and I'm trying to pieice it tgether again......
Data and Model Sharing Group
Science is a social activity requiring transparency, collab
DEEPsc: A Deep Learning-Based Map Connecting Single-Cell Transcriptomics and Spatial Imaging Data
DEEPsc uses a neural network to obtain a data-adaptive projection of cells in scRNA-seq to the corresponding spatial imaging or spatial transcriptomic data of the same tissue.
DNF: A differential network flow method to identify rewiring drivers for gene regulatory networks
Differential network analysis has become an important approach in identifying driver genes in development and disease. However, most studies capture only local features of the underlying gene-regulatory network topology. These approaches are vulnerable to noise and other changes which mask driver-gene activity.
Elementary Flux Mode Workshop
Hands on workshop for learning or teaching genome-enabled, metabolic modeling. Materials include presentations, step-by-step guides, example metabolic models and completed exercises.
Full morphology networks
Human Neocortical Neurosolver
Magneto- and electro-encephalography (MEG/EEG) non-invasively record human brain activity with millisecond resolution providing reliable markers of healthy and disease states.
iCLOTS: interactive Cell Labeled Observation and Tracking Software
LabGym: Quantification of user-defined animal behaviors using learning-based holistic assessment
Quantifying animal behavior is important for biological research. Identifying behaviors is the prerequisite of quantifying them. Current computational tools for behavioral quantification typically use high-level properties such as body poses to identify the behaviors, which constrains the information available for a holistic assessment.
Luxendo to TeraStitcher Image Converter
LuxendoToTeraStitcherConverter (LTC) is a tool that converts the Luxendo microscope format into the TeraStitcher format.
mBrainAligner: Cross-Modality Coherent Registration of Whole Mouse Brains
Recent whole brain mapping projects are collecting large-scale 3D images using powerful and informative modalities, such as STPT, fMOST, VISoR, LSFM or MRI. Registration of these multi-dimensional whole-brain images onto a standard atlas is essential for characterizing neuron types and constructing brain wiring diagrams.
Multi-Scale Cell Detector for Large Samples
MassiveMultiScaleCellDetector (MMSCD) is a tool adapted to efficiently extract anatomical features from large brain images on the order of Terabytes.
NCI-DOE Collaboration Capabilities
NetPyNE: data-driven multiscale modeling of brain circuits
NetPyNE is a Python package to facilitate the development, simulation, parallelization, analysis, and optimization of multi
Neural Encoding Model System (NEMS)
Neuromusculoskeletal Modeling Pipeline
Model-based personalized treatment design for neurologic and orthopedic movement impairments. The software is developed entirely in Matlab and adds Model Personalization and Treatment Optimization capabilities to OpenSim.
nlvelo: an R package for RNA velocity estimation using nonlinear models
OpenSim: easy-to-use, extensible software for modeling, simulating, controlling, and analyzing the musculoskeletal system
OpenSim is a software platform for modeling humans, animals, robots, and the environment, and simulating their interaction and movement. OpenSim has a graphical user interface (GUI) for visualizing models and generating and analyzing simulations.
Prediction of metabolite concentrations, rate constants and post-translational regulation
This tool consists of Jupyter notebooks, contained in the Supplementary Information to the linked article, for a new approach to modeling the mass action kinetics of metabolism. The central metabolism of Neurospora crassa, a filamentous fungi, is used for demonstration purposes.
PsyTrack: tracking behavioral parameters
Understanding how animals update their decision-making behavior over time is an important problem in neuroscience. Decision-making strategies evolve over the course of learning, and continue to vary even in well-trained animals. However, the standard suite of behavioral analysis tools is ill-equipped to capture the dynamics of these strategies.
QuanTC: Inference and multiscale model of epithelial-to-mesenchymal transition via single-cell transcriptomic data
An unsupervised learning of single-cell transcriptomic data for identification of individual cells making transition between all cell states, and inference of genes that mark transitions.
ROOTS: Ruled-Optimum Ordered Tree System
ROOTS is a package designed to take experimentally determined morphometric data and return an artificial neuronal arbor which satisfies the user-defined parameters.
scAI: an unsupervised approach for the integrative analysis of parallel single-cell transcriptomic and epigenomic profiles
scEpath: energy landscape-based inference of transition probabilities and cellular trajectories from single-cell transcriptomic data
scEpath is an approach that calculates energy landscapes and probabilistic directed graphs in order to reconstruct developmental trajectories.
scFAN: Predicting transcription factor binding in single cells through deep learning
scFAN is a deep learning model that predicts the probability of a TF binding at a given genomic region, with inputs of ATAC-seq, DNA sequence, and DNA mapability data from that region.
scMC learns biological variation through the alignment of multiple single-cell genomics datasets
scMC is an R toolkit for integrating and comparing multiple single cell genomic datasets from single cell RNA-seq and ATAC-seq experiments across different conditions, time points and tissues.
scRCMF: Identification of Cell Subpopulations and Transition States From Single-Cell Transcriptomes
scRCMF is an unsupervised method that identifies stable cell states and transition cells by adopting a nonlinear optimization model that infers the latent
substructures from a gene-cell matrix.
SHAPED Dendritic Morphology Generation
This project measures statistical properties from sets of digital reconstructions of dendritic morphologies. It then stochastically generates new morphologies based on the measured statistical distributions.
SoptSc: Cell lineage and communication network inference via optimization for single-cell transcriptomics.
Implementation of pattern recognition algorithms and visualization tools for similarity and communication between cells and populations of cells.
SpaOTsc: Inferring spatial and signaling relationships between cells from single cell transcriptomic data
SpaOTsc uses optimal transport to 1) project between scRNA-seq data and spatial data, 2) infer spatial cell-cell communications of scRNA-seq data, and 3) identify spatially localized subpopulations.
StochSS: an integrated development environment for simulation of biochemical networks
Discrete stochastic simulation has become an important and widely-used tool for modeling of biological systems at the molecular scale.
The MIcro Simulation Tool (MIST)
The MIcro Simulation Tool is free software to support disease modeling. It is a Monte-Carlo micro-simulation compiler that employs High Performance Computing.
MIST has unique population generation capabilities.
MIST runs over the cloud!
The Reference Model for Disease Progression uses MIST as its engine
Variational Joint Filtering
Variational Joint Filtering (VJF) is a flexible framework that online learns latent nonlinear state dynamics and filters latent states from high-dimensional spike trains.
Virtual Imaging Clinical Trials for Regulatory Evaluation (VICTRE)
The Virtual Imaging Clinical Trials for Regulatory Evaluation (VICTRE) computer modeling pipeline is a set of tools that allow for the generation of in silico breast radiographic images for the evaluation of digital mammography (DM) and digital breast tomosynthesis (DBT) devices.
COVID-19 Open Research Dataset
A Free, Open Resource for the Global Research Community
EDGAR Electrocardiographic Imaging Database
The Experimental Data and Geometric Analysis Repository (EDGAR) is a free, web-based repository hosted by the SCI Institute at the University of Utah. The purpose of EDGAR is to share and collate electrocardiological data, specifically for the validation and advancement of electrocardiographic imaging (ECGI) problems amongst a worldwide consortium of academic institutions.
MIDRC - Medical Imaging and Data Resource Center
Neurospora crassa Pathway-Genome Knowledgebase
Reference in vivo data for anatomy and mechanics of multi-layer tissue structures
Data to understand the mechanics of multi-layer tissue structures of the limbs, particularly of the lower and upper legs and arms. Anatomical and mechanical data were collected on extremities of 100 adult subjects (50 male, 50 female) from the general population.
Scientific Guidance on COVID-19 caused by SARS-CoV-2
Actionable scientific guidance on COVID-19 by SARS-CoV-2. Only such portal that deals extensively with each dimension of the disease succinctly and graphically and caters to everybody from novice to healthcare professional alike.
Simulation guidance of ablation therapy for persistent atrial fibrillation (U01-HL-141074)
Virtual Family (VF)
The Virtual Family (VF) is a set of four highly detailed, anatomically correct whole-body models of an adult male, an adult female, and two children.The four VF models are based on high-resolution magnetic resonance imaging (MRI) data of healthy volunteers.
Whole brain images of a Down syndrome mouse model database
Whole brain images of a Down syndrome (DS) mouse model (Ts65Dn). The Thy1-eYFP-H was crossed with Ts65Dn mouse model for imaging excitatory neurons.The images of DS mice model (TS) and their wild type littermates (WT) were acquired with light sheet fluorescence microscopy (MuVi-SPIM, Luxendo), cleared with CLARITY. The whole brain dataset consist of 13 WT (8 males and 5 females) and 17 TS (11 males and 6 females). Magnification: 15x.