Models
What is a Model?Filters
Underlying R script for the investigation of immune cells. Script contains basic data processing, as well as a DE and monocle analysis.
Creator: Markus Wolfien
Submitter: Markus Wolfien
Model type: Not specified
Model format: Not specified
Environment: Not specified
The exponential decay model with all parameters, observables and conditions was specified in a yaml file.
This yaml file is converted with yaml2sbml (2020 Jakob Vanhoefer, Marta R. A. Matos, Dilan Pathirana, Yannik Schaelte and Jan Hasenauer) to a PEtab problem, which contains also the SBML model.
Creator: Sebastian Höpfl
Submitter: Sebastian Höpfl
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: Not specified
The SOP creates a separate SBML model for each drug and condition, as the PEtab problem contains diffrent experimental data for them.
However, the SBML models only differ in their name as for all drugs and conditions, the same exponential decay model was assumed.
The SBMLs are automatically created by yaml2sbml, when the SOP is executed. Therefore, these files are for completeness only and are not necessary to replicate the analysis.
Creator: Sebastian Höpfl
Submitter: Sebastian Höpfl
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: Not specified
Here, we describe the index file generation of the mm10 genome, the genome alignment with kallisto, and quantification with bustools to obtain the used spliced / unspliced transcript input.
Creator: Markus Wolfien
Submitter: Markus Wolfien
Model type: Not specified
Model format: Not specified
Environment: Not specified
Here is the detailed R script to generate the input needed by scSynO for synthetic cell generation and classification model training.
The code that can be embedded into any other Seurat data processing workflow is:
cell_expression_target_cluster <- as.matrix(GetAssayData(seuratobject, slot = "data")[, WhichCells(seuratobject, ident = "target_cluster_number")]) cell_expression_all_other_clusters <- as.matrix(GetAssayData(seuratobject, slot = "data")[, WhichCells(seuratobject, ident = ...
Creator: Markus Wolfien
Submitter: Markus Wolfien
Model type: Not specified
Model format: Not specified
Environment: Not specified
Single nuclei transcriptomics data as .csv files from the Allen Brain atlas data set of mus musculus (https://celltypes.brain-map.org/) have been utilized as an input for scSynO. The underlying analysis is part of the manuscript entitled "Automated annotation of rare-cell types from single-cell RNA-sequencing data through synthetic oversampling". Data anaylsis and visalizations were mainly generated with the Seurat R package (https://satijalab.org/seurat/archive/v3.2/spatial_vignette.html)
Creator: Markus Wolfien
Submitter: Markus Wolfien
Model type: Not specified
Model format: Not specified
Environment: Not specified
Creator: Saptarshi Bej
Submitter: Markus Wolfien
Model type: Not specified
Model format: Not specified
Environment: Not specified
For the spatio-temporal dynamics of bile transport, bile canalicular dilation, mechanical stimulation and transduction of YAP signaling during liver regeneration see the open access publication and its appendix: Meyer et al. (2020) Bile canaliculi remodeling activates YAP via the actin cytoskeleton during liver regeneration. Molecular Systems Biology 16:e8985. https://doi.org/10.15252/msb.20198985
The model format is MorpheusML that can readily be loaded and run in the free and open source software ...
Creator: Lutz Brusch
Submitter: Lutz Brusch
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: Not specified
Spatio-temporal liver zonation in mouse and human with Wnt-Hh crosstalk and transport are modeled using coupled partial differential equations. The model file is in MorpheusML format and can be opened in the free, open-source multicellular modeling software Morpheus (https://morpheus.gitlab.io). In Morpheus, the model will simulate the time course (movie) of dynamic liver zonation for a 2D cross-section of several liver lobules, showing the patterns of Wnt ligands, intracellular Wnt signaling, ...
Creators: Lutz Brusch, Jörn Starruß, Michael Kücken
Submitter: Lutz Brusch
Model type: Partial differential equations (PDE)
Model format: Not specified
Environment: Not specified