PyscesToolbox release 1.0.0

We are pleased to announce the release of PyscesToolbox version 1.0.0.

What's new in this release:

• Major changes include support for the latest versions of library dependencies:
  • ipywidgets: changes in this library required the refactoring of interactive PyscesToolbox graphs to make use of
    the Output() widget in order to display properly.
  • networkx: the version 2.x series of networkx required changes to EventfulGraph and EventfulDict and in the
    way new nodes are added, in order for the ModelGraph functionality (metabolic network display with control patterns) to work
    correctly.
• We are now for the first time providing Anaconda install packages on all three major platforms (Windows, Linux, macOS). This greatly simplifies the installation procedure, and it is now a one-line command install with either pip or conda. The only component that still has to be installed manually is Maxima. README and installation instructions in the documentation have been updated accordingly.
• A number of bug fixes.

Installation

conda install -c pysces -c sbmlteam pyscestoolbox
or
pip install pyscestoolbox
depending on your Python setup. Dependencies are pulled in automatically.

Detailed installation instructions and documentation

• https://pyscestoolbox.readthedocs.io/en/latest/installation.html (for platform-specific installation and configuration instructions)
• https://pyscestoolbox.readthedocs.io/en/latest (documentation)

PyscesToolbox release 0.9.0

We are pleased to announce the release of PyscesToolbox version 0.9.0.

What's new in this release:

• This is the first release to support Python 3! Python versions 3.6-3.8 are recommended.
• Documentation and example notebooks have been updated.
• A number of bug fixes.

Installation:
pip install pyscestoolbox
(Dependencies are pulled in automatically).

Detailed installation instructions and documentation:

• https://pyscestoolbox.readthedocs.io/en/latest/installation.html (for platform-specific installation and configuration instructions)
• https://pyscestoolbox.readthedocs.io/en/latest (documentation)

Python 2

With Python 2 having reached its end of life, binary wheels for Python 2.7 are no longer provided. However, the PyscesToolbox codebase continues to run under Python 2.7 and can be installed from source if needed.

Bug fix

This release fixes a bug that prevented PySCeSToolbox to be installed properly from PyPi.

SymCA enhancement (see note)

Note:

This release is essentially identical to 0.8.5 with the version number being increased for technical reasons. We therefore repeat the release notes of 0.8.5 here.

Summary of changes

The main changes in this release are:

• SymCA update
• Documentation and README updates
• Bugfixes

SymCA update

For this release we have improved support for SymCA to perform symbolic control analysis on models that cannot reach a steady state. Now SymCA can yield valid control coefficient expressions even if no numerical MCA values are available (values are assigned to each control coefficient based on the assumption that species concentrations, reaction rates, and elasticity coefficients are all equal to 1).

This is useful for when information regarding the control structure of a pathway is desired for systems where only the network topology is known. However, this functionality is available for any models (regardless of their ability to reach a valid steady state).

If only the network topology is known, models must be coded as described below.

Reactions with no allosteric effectors are coded as follows in the psc model:

R1:
    S1 = S2
    v1

Where R1 catalyses the conversion of the S1 species to S2, using the dummy rate v1 (set to any non-zero number elsewhere in the model).

In the case where a reaction does have an allosteric effector it is coded as follows:

R1:
    S1 = S2
    v1*S3

Thus the only change is that the allosteric effector S3 is included by multiplying the dummy rate v1 by the S3 concentration. How it is included in the dummy rate equation (through multiplication, addition, etc.) is of no consequence as the rates in this model will be meaningless in any case. This does, however, allow PySCeS to pick the species up as an allosteric effector.

After loading a model with PySCeS, must instantiate the SymCA object with the argument python ignore_steady_state set to True as follows:

mod = pysces.model('test_model.psc')
sc = psctb.Symca(mod, ignore_steady_state=True)

Further steps are the same as previously outlined (see the documentation).

Documentation and README updates

The README has been shortened with some of its contents being moved to the documentation. The documentation now includes detailed step-by-step instructions on installing PySCeSToolbox on any of Mac OS X, Linux and Windows.

Minor bugfixes

Symca now gives the correct error message when Maxima is not installed on Linux and Mac (previously a message containing reference to Windows directories was shown).

SymCA enhancement

Summary of changes

The main changes in this release are:

• SymCA update
• Documentation and README updates
• Bugfixes

SymCA update

For this release we have improved support for SymCA to perform symbolic control analysis on models that cannot reach a steady state. Now SymCA can yield valid control coefficient expressions even if no numerical MCA values are available (values are assigned to each control coefficient based on the assumption that species concentrations, reaction rates, and elasticity coefficients are all equal to 1).

This is useful for when information regarding the control structure of a pathway is desired for systems where only the network topology is known. However, this functionality is available for any models (regardless of their ability to reach a valid steady state).

If only the network topology is known, models must be coded as described below.

Reactions with no allosteric effectors are coded as follows in the psc model:

R1:
    S1 = S2
    v1

Where R1 catalyses the conversion of the S1 species to S2, using the dummy rate v1 (set to any non-zero number elsewhere in the model).

In the case where a reaction does have an allosteric effector it is coded as follows:

R1:
    S1 = S2
    v1*S3

Thus the only change is that the allosteric effector S3 is included by multiplying the dummy rate v1 by the S3 concentration. How it is included in the dummy rate equation (through multiplication, addition, etc.) is of no consequence as the rates in this model will be meaningless in any case. This does, however, allow PySCeS to pick the species up as an allosteric effector.

After loading a model with PySCeS, must instantiate the SymCA object with the argument python ignore_steady_state set to True as follows:

mod = pysces.model('test_model.psc')
sc = psctb.Symca(mod, ignore_steady_state=True)

Further steps are the same as previously outlined (see the documentation).

Documentation and README updates

The README has been shortened with some of its contents being moved to the documentation. The documentation now includes detailed step-by-step instructions on installing PySCeSToolbox on any of Mac OS X, Linux and Windows.

Minor bugfixes

Symca now gives the correct error message when Maxima is not installed on Linux and Mac (previously a message containing reference to Windows directories was shown).

First Release

This is the "first" release of PySCeSToolbox in the sense that it is the first time that the ipython-d3networkx-master.zip and Pyscestoolbox-master.zip files (which are essentially just the source code for these packages) have been made available from the release page. This is done so that users can download these files and install them with pip without the need for having git installed on their system. In the future major releases will also be published here.

The included zip files can be installed using:

pip install ipython-d3networkx-master.zip PyscesToolbox-master.zip