Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/spatialsimulator/XitoSBML

XitoSBML - the spatial SBML plugin for ImageJ
https://github.com/spatialsimulator/XitoSBML

fiji imagej sbml spatial-sbml-plugin systems-biology

Last synced: 28 days ago
JSON representation

XitoSBML - the spatial SBML plugin for ImageJ

Awesome Lists containing this project

README 

        
XitoSBML: Spatial SBML Plugin for ImageJ

======================

XitoSBML is an [ImageJ](https://imagej.net/Welcome) plugin which creates a [Spatial SBML](http://sbml.org/Documents/Specifications/SBML_Level_3/Packages/spatial) model from segmented images.

XitoSBML is not just a converter, but also a spatial model editor so that users can add molecules(species), reactions, and advection/diffusion coefficients to the converted Spatial SBML model.



![XitoSBML](./screenshots/xitosbml.png "XitoSBML: Spatial SBML Plugin for ImageJ")



How to Install

------------------

1. Launch ImageJ (Fiji)

2. Click [Help] -> [Update...]

3. Click [Manage update sites] button on [ImageJ Updater] dialog

4. On [Manage update sites dialog], scroll down the list of update sites, turn on [XitoSBML] checkbox and press [Close] button

5. Click [Apply changes] button on [ImageJ Updater] dialog

6. ImageJ (Fiji) will download and install XitoSBML and its dependent libraries

7. Restart ImageJ (Fiji); then you will find [XitoSBML] plugin under [Plugins] menu



Here is a screencast of the above installation procedure (screencast is also

available as an [MP4 file](./screenshots/install-xitosbml.mp4)).

![install-xitosbml](./screenshots/install-xitosbml.gif "Install XitoSBML")



How to Use

-------------------

### Convert segmented (binary) images to Spatial SBML (which contains simulation space only)

**XitoSBML requires segmented images to create spatial model**.

Please prepare segmented images of original microscopic images beforehand.

The segmented images will be obtained by using pre-built [Segmentaion function in ImageJ](https://imagej.net/Segmentation).



1. Launch ImageJ (Fiji)

2. Load original images (not mandatory) and their segmented images

3. Click [Plugins] -> [XitoSBML] -> [run Spatial Image SBML Plugin]

4. On [DomainType Namer] dialog, assign an opened segmented image to each organelle (ex. nucleus, cytosol)

5. XitoSBML will ask whether you want to add SBML objects (Species, Reactions, and Parameters) to the converted Spatial SBML model. If you just want to convert your segmented image files to Spatial SBML, then just click [No]

6. Specify a filename of converted SBML model

7. XitoSBML will display the converted Spatial SBML document and Domain Hierarchy of your model to let you confirm the converted result

8. Exported SBML and the merged segmented image will be stored (where you specified in step 6)



Here is a screencast of the above procedure (screencast is also

available as an [MP4 file](./screenshots/example1.mp4)).



![example1](./screenshots/example1.gif "Convert segmented images to Spatial SBML")



### Example files

This repository also contains example 2D and 3D images and converted Spatial

SBML models under [examples](https://github.com/spatialsimulator/XitoSBML/tree/master/examples) directory.

Here is a description on example files.



#### 2D images and model

directory | filename | input or output | description

:-- | :--|:--:|:--

`examples/2D` | `Rat_Hippocampal_Neuron-Nuc.tiff` | input | 2D segmented image of nucleus

`examples/2D` | `Rat_Hippocampal_Neuron-Cyt.tiff` | input | 2D segmented image of cytosol

`examples/2D` | `example2D.xml` | output | 2D spatial SBML model generated by XitoSBML

`examples/2D` | `example2D.tiff` | output | 2D merged segmented image generated by XitoSBML

`examples/2D` | `Rat_Hippocampal_Neuron-Hoechst.tiff` | -- | Original 2D fluroscent microscopic image of nucleus

`examples/2D` | `Rat_Hippocampal_Neuron-NicotinicAcetylcholineAlpha7.tiff` | -- | Original 2D fluroscent microscopic image of cytosol



#### 3D images and model



directory | filename | input or output | description

:-- | :--|:--:|:--

`examples/3D` | `nuc-zstack.tiff` | input | 3D (Z-stack) segmented image of nucleus

`examples/3D` | `cyt-zstack.tiff` | input | 3D (Z-stack) segmented image of cytosol

`examples/3D` | `zstack.xml` | output | 3D spatial SBML model generated by XitoSBML

`examples/3D` | `zstack.tiff` | output | 3D (Z-stack) merged segmented image generated by XitoSBML



### Convert segmented (binary) images to Spatial SBML (as a mathematical model)

Next example will show how to create a Spatial SBML model, add SBML objects to the model, and make it as a mathematical model. The following figure represents the diagram of this example model. Note that species `A` and `B` diffuse inside the nucleus and cytosol with the given diffusion coefficients (`Dnuc` and `Dcyt`), respectively.



![diagram of example2](./screenshots/example2.png "Diagram of example model 2")



1. Launch ImageJ (Fiji)

2. Load original images (not mandatory) and their segmented images

3. Click [Plugins] -> [XitoSBML] -> [run Spatial Image SBML Plugin]

4. On [DomainType Namer] dialog, assign an opened segmented image to each organelle (ex. nucleus, cytosol)

5. XitoSBML will ask whether you want to add SBML objects (Species, Reactions, and Parameters) to the converted Spatial SBML model. This time, we want to add SBML objects so click [Yes]

6. In [Species] tab, add species `A` and `B`. Note that we will add species `A` to Nucleus and `B` to Cytosol

7. In [Diffusion] tab, add `Diffusion coefficient` for species `A (Dnuc)` and `B (Dcyt)`

8. In [Reaction] tab, add a reaction (`A -> B`) and its kinetic law. Please do not forget to assign reactants and products for the reaction

9. Specify a filename of converted SBML model

10. XitoSBML will display the converted Spatial SBML document and Domain Hierarchy of your model to let you confirm the converted result

11. Exported SBML and the merged segmented image will be stored (where you specified in step 9)



Here is a screencast of the above procedure (screencast is also

available as an [MP4 file](./screenshots/example2.mp4)).



![example2](./screenshots/example2.gif "Convert segmented images to Spatial SBML")



You can find example 2D and 3D images and converted Spatial SBML model under [examples](https://github.com/spatialsimulator/XitoSBML/tree/master/examples) directory.



The mathematical (spatial) model created by this example can be executed by several spatial simulators which support Spatial SBML. For example, you can use our [SpatialSimulator](https://github.com/spatialsimulator) for executing the converted model. We have provided a [Docker image](https://github.com/funasoul/docker-spatialsim) for SpatialSimulator so that you can easily install and run SpatialSimulator on your environment.



```sh

git clone https://github.com/funasoul/docker-spatialsim.git

cd ./docker-spatialsim/

# Copy example2D.xml to this directory

./docker-spatialsim.sh -t 0.2 -d 0.0001 -o 50 example2D.xml

```



SpatialSimulator will generate numbers and images of the simulation result.



Species A             |  Species B

:-------------------------:|:-------------------------:

![example2 species A](./screenshots/example2_a.gif "Simulation result of example2D.xml (species A)") | ![example2 species B](./screenshots/example2_b.gif "Simulation result of example2D.xml (species B)")



How to Compile

------------------

To whom might be interested, here is an instruction on how to compile XitoSBML from source code.



### Dependencies

XitoSBML requires the following third-party applications/libraries.



+ [JSBML](http://sbml.org/Software/JSBML "JSBML")

+ [Fiji Is Just ImageJ](http://fiji.sc/Fiji "Fiji Is Just ImageJ")

+ [ImageJ 3D Viewer](http://3dviewer.neurofly.de/ "ImageJ 3D Viewer") version 1.5 or higher

+ [Maven](https://maven.apache.org/ "Maven")



#### Build XitoSBML

```sh

% git clone https://github.com/spatialsimulator/XitoSBML.git

% mvn install -Dimagej.app.directory=/path/to/ImageJ

```

For example, if you want to build XitoSBML on Fiji.app(MacOSX), the `mvn` command will be executed as follows:

```sh

% mvn install -Dimagej.app.directory=/Applications/Fiji.app/

```



### Documentation

Javadocs of XitoSBML API are included under `apidocs` directory in the repository, and

are available on our [web site](https://fun.bio.keio.ac.jp/software/XitoSBML/apidocs/).



Here are the high-level key classes of XitoSBML, which will be a good starting point to read through the code.



Class | Plugin item on ImageJ

:-- | :--

[jp.ac.keio.bio.fun.xitosbml.xitosbml.MainImgSpatial.java](https://fun.bio.keio.ac.jp/software/XitoSBML/apidocs/jp/ac/keio/bio/fun/xitosbml/xitosbml/MainImgSpatial.html) | run Spatial Image SBML Plugin

[jp.ac.keio.bio.fun.xitosbml.xitosbml.MainModelEdit.java](https://fun.bio.keio.ac.jp/software/XitoSBML/apidocs/jp/ac/keio/bio/fun/xitosbml/xitosbml/MainModelEdit.html) | run Model Editor

[jp.ac.keio.bio.fun.xitosbml.xitosbml.MainModelValidator.java](https://fun.bio.keio.ac.jp/software/XitoSBML/apidocs/jp/ac/keio/bio/fun/xitosbml/xitosbml/MainModelValidator.html) | run Model Validation



Licensing

------------------

XitoSBML is licensed under the Apache License, Version 2.0. See [LICENSE](https://github.com/spatialsimulator/XitoSBML/blob/master/LICENSE-2.0.txt) for the full license text.