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Recent Releases of biomass

biomass - v0.14.0

What's Changed

  • Delete badge and add reference by @himoto in https://github.com/biomass-dev/biomass/pull/268
  • Add Issue and Volume info by @himoto in https://github.com/biomass-dev/biomass/pull/269
  • Update citing.rst by @himoto in https://github.com/biomass-dev/biomass/pull/270
  • Update index.rst by @himoto in https://github.com/biomass-dev/biomass/pull/271
  • Allow different time points between conditions for experimental data by @k-arakane in https://github.com/biomass-dev/biomass/pull/273
  • Fix user_defined and allow multiple reactants/products by @k-arakane in https://github.com/biomass-dev/biomass/pull/277
  • [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in https://github.com/biomass-dev/biomass/pull/276
  • Release v0.14.0 by @k-arakane in https://github.com/biomass-dev/biomass/pull/278

New Contributors

  • @k-arakane made their first contribution in https://github.com/biomass-dev/biomass/pull/273

Full Changelog: https://github.com/biomass-dev/biomass/compare/v0.13.0...v0.14.0

- Python
Published by himoto about 1 year ago

biomass - v0.13.0

What's Changed

  • Update .readthedocs.yaml to resolve build error by @himoto in https://github.com/biomass-dev/biomass/pull/255
  • Use default ddof(=0) by @himoto in https://github.com/biomass-dev/biomass/pull/256
  • Remove unused variable: __version__ by @himoto in https://github.com/biomass-dev/biomass/pull/257
  • Don't use Sphinx version 7 or more by @himoto in https://github.com/biomass-dev/biomass/pull/259
  • Fix pepy badge by @himoto in https://github.com/biomass-dev/biomass/pull/263
  • Remove Sphinx version constraints by @himoto in https://github.com/biomass-dev/biomass/pull/262
  • Specify minimal sphinx-rtd-theme version by @himoto in https://github.com/biomass-dev/biomass/pull/264
  • Update MANIFEST.in by @himoto in https://github.com/biomass-dev/biomass/pull/266
  • Update citation infomation by @himoto in https://github.com/biomass-dev/biomass/pull/267
  • [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in https://github.com/biomass-dev/biomass/pull/260

Full Changelog: https://github.com/biomass-dev/biomass/compare/v0.12.0...v0.13.0

- Python
Published by himoto over 1 year ago

biomass - v0.12.0 (May 2023)

What's Changed

  • Update email address by @himoto in https://github.com/biomass-dev/biomass/pull/249
  • Remove Sphinx version constraint by @himoto in https://github.com/biomass-dev/biomass/pull/251
  • Add support for Python 3.11 and numpy 1.24 by @himoto in https://github.com/biomass-dev/biomass/pull/252
  • [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in https://github.com/biomass-dev/biomass/pull/246
  • Release v0.12.0 by @himoto in https://github.com/biomass-dev/biomass/pull/253

Full Changelog: https://github.com/biomass-dev/biomass/compare/v0.11.1...v0.12.0

- Python
Published by himoto over 2 years ago

biomass - v0.11.1

What's Changed

  • Add file name by @himoto in https://github.com/biomass-dev/biomass/pull/238
  • Update arguments of run_analysis function by @himoto in https://github.com/biomass-dev/biomass/pull/240
  • Move package setup to toml file by @himoto in https://github.com/biomass-dev/biomass/pull/243
  • Release v0.11.1 by @himoto in https://github.com/biomass-dev/biomass/pull/244

Full Changelog: https://github.com/biomass-dev/biomass/compare/v0.11.0...v0.11.1

- Python
Published by himoto almost 3 years ago

biomass - v0.11.0 (January 2023)

What's Changed

  • Set pyvis version <0.3 by @himoto in https://github.com/biomass-dev/biomass/pull/201
  • Update citation info by @himoto in https://github.com/biomass-dev/biomass/pull/197
  • Fix maxdepth to 2 by @himoto in https://github.com/biomass-dev/biomass/pull/202
  • Add CodeQL workflow for GitHub code scanning by @lgtm-com in https://github.com/biomass-dev/biomass/pull/204
  • Fix #205 by @himoto in https://github.com/biomass-dev/biomass/pull/206
  • Update template by @himoto in https://github.com/biomass-dev/biomass/pull/207
  • Update util in analysis/ by @himoto in https://github.com/biomass-dev/biomass/pull/208
  • Explicit return by @himoto in https://github.com/biomass-dev/biomass/pull/210
  • Explicitly return None by @himoto in https://github.com/biomass-dev/biomass/pull/211
  • Use Tee class instead of _Logger by @himoto in https://github.com/biomass-dev/biomass/pull/213
  • Update action/checkout@v2 -> v3 by @himoto in https://github.com/biomass-dev/biomass/pull/215
  • Fix docstring in Optimizer by @himoto in https://github.com/biomass-dev/biomass/pull/217
  • Remove LGTM.com code quality badges by @himoto in https://github.com/biomass-dev/biomass/pull/219
  • Update julia_template.py by @himoto in https://github.com/biomass-dev/biomass/pull/222
  • Update docs by @himoto in https://github.com/biomass-dev/biomass/pull/224
  • Fix a typo in state_transition rule by @himoto in https://github.com/biomass-dev/biomass/pull/225
  • Improve instructions for executing example models by @himoto in https://github.com/biomass-dev/biomass/pull/227
  • Suppress numba warning by @himoto in https://github.com/biomass-dev/biomass/pull/229
  • Update solver.py by @himoto in https://github.com/biomass-dev/biomass/pull/230
  • Update state_transition rule in Text2Model by @himoto in https://github.com/biomass-dev/biomass/pull/232
  • [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in https://github.com/biomass-dev/biomass/pull/164
  • Release v0.11.0 by @himoto in https://github.com/biomass-dev/biomass/pull/237

New Contributors

  • @lgtm-com made their first contribution in https://github.com/biomass-dev/biomass/pull/204

Full Changelog: https://github.com/biomass-dev/biomass/compare/v0.10.0...v0.11.0

- Python
Published by himoto almost 3 years ago

biomass - v0.10.0 (September 2022)

What's Changed

  • State transition by @himoto in https://github.com/biomass-dev/biomass/pull/169
  • Generalisation of mass action kinetics by @formersbach in https://github.com/biomass-dev/biomass/pull/172
  • Drop support for old template by @himoto in https://github.com/biomass-dev/biomass/pull/176
  • Fix typo in tutorial by @himoto in https://github.com/biomass-dev/biomass/pull/178
  • Fix module name: model_object by @himoto in https://github.com/biomass-dev/biomass/pull/181
  • Transfer graphing from BioMass to Text2Model by @formersbach in https://github.com/biomass-dev/biomass/pull/177
  • Update docs to be compatible with the newest features by @himoto in https://github.com/biomass-dev/biomass/pull/182
  • Fix f-string in is_phosphorylated rule by @himoto in https://github.com/biomass-dev/biomass/pull/184
  • Refactor code for sensitivity analysis by @himoto in https://github.com/biomass-dev/biomass/pull/186
  • Redirect rules by @himoto in https://github.com/biomass-dev/biomass/pull/188
  • Fix issue #189 by @formersbach in https://github.com/biomass-dev/biomass/pull/190
  • Fix docstring by @himoto in https://github.com/biomass-dev/biomass/pull/191
  • Fixes #192 by @formersbach in https://github.com/biomass-dev/biomass/pull/193
  • Update graphing tutorial to new graph function. by @formersbach in https://github.com/biomass-dev/biomass/pull/195

Full Changelog: https://github.com/biomass-dev/biomass/compare/v0.9.1...v0.10.0

- Python
Published by himoto over 3 years ago

biomass - v0.9.1

What's Changed

  • Enable running biomass without Graphviz by @himoto in https://github.com/biomass-dev/biomass/pull/162

Full Changelog: https://github.com/biomass-dev/biomass/compare/v0.9.0...v0.9.1

- Python
Published by himoto over 3 years ago

biomass - v0.9.0 (July 2022)

What's Changed

  • Adding interactive plotting option. by @formersbach in https://github.com/biomass-dev/biomass/pull/144
  • Changed how graph is passed to pygraphvis, fixing issue #147 by @formersbach in https://github.com/biomass-dev/biomass/pull/148
  • Add graph visualization tutorial, resolves #145 by @formersbach in https://github.com/biomass-dev/biomass/pull/149
  • [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in https://github.com/biomass-dev/biomass/pull/146
  • Fixes documentation and changes default save directory of graph.py by @formersbach in https://github.com/biomass-dev/biomass/pull/154
  • Remove exec by @himoto in https://github.com/biomass-dev/biomass/pull/157

Full Changelog: https://github.com/biomass-dev/biomass/compare/v0.8.0...v0.9.0

- Python
Published by himoto over 3 years ago

biomass - v0.8.0 (June 2022)

What's Changed

  • Graph representation of biological model by @formersbach in https://github.com/biomass-dev/biomass/pull/131
  • Drop support of Python <= 3.7 by @himoto in https://github.com/biomass-dev/biomass/pull/132
  • Update graph.py by @himoto in https://github.com/biomass-dev/biomass/pull/133
  • From text to model by @himoto in https://github.com/biomass-dev/biomass/pull/136
  • Release v0.8.0 by @himoto in https://github.com/biomass-dev/biomass/pull/138
  • Fix error in multiobservablesoptions by @himoto in https://github.com/biomass-dev/biomass/pull/140
  • Fix dead link by @himoto in https://github.com/biomass-dev/biomass/pull/142

New Contributors

  • @formersbach made their first contribution in https://github.com/biomass-dev/biomass/pull/131

Full Changelog: https://github.com/biomass-dev/biomass/compare/v0.7.2...v0.8.0

- Python
Published by himoto over 3 years ago

biomass - v0.7.2

What's Changed

  • Make error messages more user friendly by @himoto in https://github.com/biomass-dev/biomass/pull/123
  • Fix #124 by @himoto in https://github.com/biomass-dev/biomass/pull/125
  • Release v0.7.2 by @himoto in https://github.com/biomass-dev/biomass/pull/128

Full Changelog: https://github.com/biomass-dev/biomass/compare/v0.7.1...v0.7.2

- Python
Published by himoto over 3 years ago

biomass - v0.7.1

What's Changed

  • Create tutorial by @himoto in https://github.com/biomass-dev/biomass/pull/118
  • Update logo by @himoto in https://github.com/biomass-dev/biomass/pull/119
  • Release v0.7.1 by @himoto in https://github.com/biomass-dev/biomass/pull/121

Full Changelog: https://github.com/biomass-dev/biomass/compare/v0.7.0...v0.7.1

- Python
Published by himoto over 3 years ago

biomass - v0.7.0 (June 2022)

What's Changed

  • Add support for Python 3.10 by @himoto in https://github.com/biomass-dev/biomass/pull/110
  • Add CITATION.cff by @himoto in https://github.com/biomass-dev/biomass/pull/111
  • Add InitialPopulation by @himoto in https://github.com/biomass-dev/biomass/pull/113
  • Release v0.7.0 by @himoto in https://github.com/biomass-dev/biomass/pull/116

Renamed BioMASS modules:

| Old | New | | --- | ----- | | set_model.py | ode.py | | set_search_param.py | search_param.py | | fitness.py | problem.py |

Full Changelog: https://github.com/biomass-dev/biomass/compare/v0.6.2...v0.7.0

- Python
Published by himoto over 3 years ago

biomass - v0.6.2

What's Changed

  • Release v0.6.2 by @himoto in https://github.com/biomass-dev/biomass/pull/107

Full Changelog: https://github.com/biomass-dev/biomass/compare/v0.6.1...v0.6.2

- Python
Published by himoto over 3 years ago

biomass - v0.6.1

What's Changed

  • [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in https://github.com/biomass-dev/biomass/pull/97
  • docs: git clone biomass by @himoto in https://github.com/biomass-dev/biomass/pull/98
  • Add model of the G1/S cell cycle transition by @himoto in https://github.com/biomass-dev/biomass/pull/99
  • Set 'LSODA' as default ODE solver by @himoto in https://github.com/biomass-dev/biomass/pull/100
  • Add model for the proliferation–quiescence decision by @himoto in https://github.com/biomass-dev/biomass/pull/101
  • Update example code for ExternalOptimizer by @himoto in https://github.com/biomass-dev/biomass/pull/103
  • Release v0.6.1 by @himoto in https://github.com/biomass-dev/biomass/pull/104

Full Changelog: https://github.com/biomass-dev/biomass/compare/v0.6.0...v0.6.1

- Python
Published by himoto over 3 years ago

biomass - v0.6.0 (April 2022)

What's Changed

  • Release v0.6.0 by @himoto in https://github.com/biomass-dev/biomass/pull/95
  • [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in https://github.com/biomass-dev/biomass/pull/87

Full Changelog: https://github.com/biomass-dev/biomass/compare/v0.5.5...v0.6.0

- Python
Published by himoto over 3 years ago

biomass - v0.5.5

What's Changed

  • Fix error message for incorrect visualization options by @himoto in https://github.com/biomass-dev/biomass/pull/72
  • Fix sensitivity analysis visualization problem by @himoto in https://github.com/biomass-dev/biomass/pull/81
  • Add more tests by @himoto in https://github.com/biomass-dev/biomass/pull/83
  • Release v0.5.5 by @himoto in https://github.com/biomass-dev/biomass/pull/84
  • [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in https://github.com/biomass-dev/biomass/pull/70

Full Changelog: https://github.com/biomass-dev/biomass/compare/v0.5.4...v0.5.5

- Python
Published by himoto almost 4 years ago

biomass - v0.5.4

  • Docs:

    • Add simulation results for each model, see here

  • Core functions:

    • Add method to check model indices

  • Solver:

    • Update function to equilibrate a system (#68)

- Python
Published by himoto about 4 years ago

biomass - v0.5.3

  • Docs:

    • Fix several docstrings
    • Update references

  • Requirements:

    • Set minimal numpy version to 1.17
    • Add typing_extensions

  • Other:

    • Add link to BioMASS docker images on DockerHub

- Python
Published by himoto about 4 years ago

biomass - v0.5.2

  • Template

    • Update viz.py

    Use this template for creating models with biomass>=0.5.2

    ```python from matplotlib import pyplot as plt

    from biomass.plotting import *

    from .observable import Observable

    class Visualization(Observable): """ Plotting parameters for customizing figure properties.

    Attributes
----------
cm : matplotlib.colors.ListedColormap (default: `plt.cm.get_cmap('tab10')`)
    Choosing colormaps for `cmap`.
single_observable_options : list of SingleObservable
    Visualization options for time-course simulation (single-observable).
multiple_observables_options : MultipleObservables
    Visualization options for time-course simulation (multi-observables).
sensitivity_options : SensitivityOptions
    Visualization options for sensitivity analysis results.
"""

def __init__(self):
    super().__init__()

    self.cm = plt.cm.get_cmap("tab10")
    self.single_observable_options = [
        SingleObservable(self.cm, obs_name) for obs_name in self.obs_names
    ]
    self.multiple_observables_options = MultipleObservables(self.cm)
    self.sensitivity_options = SensitivityOptions(self.cm)

def get_single_observable_options(self):

    return self.single_observable_options

def get_multiple_observables_options(self):

    return self.multiple_observables_options

def get_sensitivity_options(self):

    return self.sensitivity_options

@staticmethod
def set_timecourse_rcParams():
    """figure/simulation"""
    plt.rcParams["font.size"] = 12
    plt.rcParams["axes.linewidth"] = 1.5
    plt.rcParams["xtick.major.width"] = 1.5
    plt.rcParams["ytick.major.width"] = 1.5
    plt.rcParams["lines.linewidth"] = 1.8
    plt.rcParams["lines.markersize"] = 12
    plt.rcParams["savefig.bbox"] = "tight"
    # plt.rcParams["savefig.format"] = "pdf"
    # plt.rcParams['font.family'] = 'Arial'
    # plt.rcParams['mathtext.fontset'] = 'custom'
    # plt.rcParams['mathtext.it'] = 'Arial:italic'

@staticmethod
def set_sensitivity_rcParams():
    """figure/sensitivity"""
    plt.rcParams["font.size"] = 12
    plt.rcParams["axes.linewidth"] = 1.2
    plt.rcParams["xtick.major.width"] = 1.2
    plt.rcParams["ytick.major.width"] = 1.2
    plt.rcParams["savefig.bbox"] = "tight"
    # plt.rcParams["savefig.format"] = "pdf"
    # plt.rcParams['font.family'] = 'Arial'

@staticmethod
def convert_species_name(name):
    """figure/sensitivity/initial_condition
    - Sensitivity for species with nonzero initial conditions
    """
    return name

    ```

  • Core functions

    • Fix default workers in optimize function (#58)

  • Parameter estimation

    • Fix a bug (#59)

  • Other

    • Bump minimal sicpy version to 1.6
    • integrate.simps was renamed to integrate.simpson

- Python
Published by himoto over 4 years ago

biomass - v0.5.1

  • Template

    • Add new key: legend_kws
    • legend_loc becomes invalid
    • Several updates to default rcParams

  • Core functions

    • Remove save_format from arguments in run_simulation and run_analysis
    • To modify save_format, edit viz.py in the model.
    • Use x_id to specify the index (indices) of parameter sets when running optimize
    • start and end become invalid
    • Add create_metrics : Dict[str, Callable[[np.ndarray], Union[int, float]]], optional to run_analysis
    • Allowing users to crete signaling metrics for sensitivity analysis

- Python
Published by himoto over 4 years ago

biomass - v0.5.0 (June 2021)

  • Dependencies

    • Add pandas (See requirements.txt)

  • Template

    • Update fitness.py
    • Create OptimizationProblem
    • Add bounds for external optimizer
    • Update viz.py
    • Add figsize (default: (4, 3)) to timecourseoptions and multiplotoptions

  • biomass.result

    • Move visualization of estimated parameter sets to biomass.OptimizationResults.savefig()

    ```python

    from biomass import Model, OptimizationResults from biomass.models import NakakukiCell2010 model = Model(NakakukiCell2010.package).create() res = OptimizationResults(model) res.savefig(figsize=(16,5), boxplot_kws={"orient": "v"}) ```

  • biomass.estimation

    • Create new class: ExternalOptimizer python >>> from scipy.optimize import differential_evolution >>> from biomass import Model >>> from biomass.models import Nakakuki_Cell_2010 >>> model = Model(Nakakuki_Cell_2010.__package__).create() >>> optimizer = ExternalOptimizer(model, differential_evolution) >>> res = optimizer.run( ... model.problem.objective, ... model.problem.bounds, ... strategy="best2bin", ... maxiter=100, ... tol=1e-4, ... mutation=0.1, ... recombination=0.5, ... disp=True, ... polish=False, ... workers=-1, ... ) > differentialevolution step 1: f(x)= 7.05589 > differentialevolution step 2: f(x)= 5.59166 > differentialevolution step 3: f(x)= 2.80301 > ... > differentialevolution step 100: f(x)= 0.538524

    ```python

    from biomass import runsimulation optimizer.importsolution(res.x, xid=0) runsimulation(model, viz_type="0") ```

- Python
Published by himoto over 4 years ago

biomass - v0.4.1

  • Create docs: https://biomass-core.readthedocs.io/en/latest/

    • Core functions
    • Update default values: https://biomass-core.readthedocs.io/en/latest/modules/core.html
    • Optimization results
    • Set estimated params and initials to be plotted in one figure

- Python
Published by himoto over 4 years ago

biomass - v0.4.0 (May 2021)

  • License

  • Template

    • Don't use exec in name2idx

    Use make_dataclass instead.

    ```python NAMES: List[str] = [...]

    NUM: int = len(NAMES)

    Parameters = makedataclass( clsname="Parameters", fields=[(name, int) for name in NAMES], namespace={"NAMES": NAMES, "NUM": NUM}, frozen=True, )

    name2idx: Dict[str, int] = {k: v for v, k in enumerate(NAMES)}

    C = Parameters(**name2idx)

    del name2idx ```

  • Model construction

    • Use Model class

    ```python

    from biomass import Model import yourmodel model = Model(yourmodel.package).create() ```

  • Sensitivity analysis

    • Fix path to save sensitivity coefficients

    {your_model}/sensitivity_coefficients/{target}/{metric}.npy

  • Other

- Python
Published by himoto over 4 years ago

biomass - v0.3.5

  • Models

    • Add the insulin-dependent AKT pathway model
    • Reference:
    • Kubota, H. et al. Temporal Coding of Insulin Action through Multiplexing of the AKT Pathway. Mol. Cell 46, 820–832 (2012). https://doi.org/10.1016/j.molcel.2012.04.018
    • BioModels:
    • Kubota2012InsulinActionAKTpathway

  • Template for BioMASS model construction

    • Update reaction_network.py

    ```python from typing import Dict, List

    from biomass.analysis.reaction import is_duplicate

    class ReactionNetwork(object): """ Reaction indices grouped according to biological processes. This is used for sensitivity analysis (target='reaction'). """

    def __init__(self) -> None:
    self.reactions: Dict[str, List[int]] = {}

def group(self):
    """
    Group reactions according to biological processes
    """
    biological_processes = []
    for process, indices in self.reactions.items():
        if not isinstance(indices, list):
            raise TypeError("Use list for reaction indices in {}".format(process))
        biological_processes.append(indices)

    if not is_duplicate(self.reactions, biological_processes):
        return biological_processes

    ```

  • Output

    • Update _writebestfit_param.py
    • Example:

    ```

    parameter set: 9

    def paramvalues(): x = [0] * C.NUM x[C.V1] = 9.152e-02 x[C.Km1] = 3.761e+02 x[C.V2] = 2.200e-01 x[C.Km2] = 3.500e+02 x[C.V3] = 7.200e-01 x[C.Km3] = 1.600e+02 x[C.V4] = 6.480e-01 x[C.Km4] = 6.000e+01 x[C.V5] = 6.913e+01 x[C.Km5] = 2.727e+01 x[C.V6] = 6.913e+01 x[C.Km6] = 2.727e+01 x[C.KimERK] = 1.200e-02 x[C.KexERK] = 1.800e-02 x[C.KimpERK] = 1.200e-02 x[C.KexpERK] = 1.800e-02 x[C.KimppERK] = 1.100e-02 x[C.KexppERK] = 1.300e-02 x[C.V10] = 4.275e+02 x[C.Km10] = 1.469e+01 x[C.n10] = 2.593e+00 x[C.p11] = 2.191e-04 x[C.p12] = 1.156e-03 x[C.p13] = 6.951e-04 x[C.V14] = 3.090e-01 x[C.Km14] = 8.111e+02 x[C.V15] = 2.049e+02 x[C.Km15] = 7.803e-03 x[C.p16] = 2.570e-04 x[C.p17] = 9.630e-05 x[C.KimDUSP] = 1.832e-03 x[C.KexDUSP] = 4.328e-02 x[C.KimpDUSP] = 1.832e-03 x[C.KexpDUSP] = 4.328e-02 x[C.V20] = 3.512e-01 x[C.Km20] = 1.321e+05 x[C.V21] = 5.249e-02 x[C.Km21] = 1.184e-03 x[C.p22] = 2.570e-04 x[C.p23] = 9.630e-05 x[C.V24] = 3.440e+00 x[C.Km24] = 1.912e+05 x[C.V25] = 1.109e+02 x[C.Km25] = 4.527e+00 x[C.KimRSK] = 2.519e-03 x[C.KexRSK] = 1.024e-02 x[C.V27] = 1.390e+01 x[C.Km27] = 4.619e+03 x[C.V28] = 4.295e-01 x[C.Km28] = 1.165e+00 x[C.V29] = 9.103e-02 x[C.Km29] = 6.333e+03 x[C.V30] = 5.958e+01 x[C.Km30] = 7.801e+00 x[C.V31] = 5.691e+01 x[C.Km31] = 1.543e-02 x[C.n31] = 1.713e+00 x[C.p32] = 1.100e-03 x[C.p33] = 1.959e-03 x[C.p34] = 7.572e-04 x[C.V35] = 5.050e+00 x[C.Km35] = 1.795e+03 x[C.V36] = 1.218e-01 x[C.Km36] = 2.394e+03 x[C.V37] = 1.178e+03 x[C.Km37] = 1.062e+02 x[C.p38] = 2.570e-04 x[C.p39] = 9.630e-05 x[C.KimFOS] = 1.205e-01 x[C.KexFOS] = 1.590e-01 x[C.KimpcFOS] = 1.205e-01 x[C.KexpcFOS] = 1.590e-01 x[C.V42] = 9.649e-02 x[C.Km42] = 5.639e+02 x[C.V43] = 3.568e-03 x[C.Km43] = 1.382e+02 x[C.V44] = 1.290e-03 x[C.Km44] = 2.725e-02 x[C.p45] = 2.570e-04 x[C.p46] = 9.630e-05 x[C.p47] = 2.140e-01 x[C.m47] = 1.288e+01 x[C.p48] = 3.351e-02 x[C.p49] = 4.279e-02 x[C.m49] = 2.331e+00 x[C.p50] = 3.491e-02 x[C.p51] = 1.053e-03 x[C.m51] = 4.536e+00 x[C.p52] = 2.140e-01 x[C.m52] = 1.288e+01 x[C.p53] = 3.351e-02 x[C.p54] = 4.279e-02 x[C.m54] = 2.331e+00 x[C.p55] = 3.491e-02 x[C.p56] = 1.053e-03 x[C.m56] = 4.536e+00 x[C.V57] = 2.366e+02 x[C.Km57] = 7.976e-04 x[C.n57] = 1.649e+00 x[C.p58] = 2.471e-09 x[C.p59] = 2.889e-06 x[C.p60] = 6.575e-02 x[C.p61] = 2.517e+00 x[C.KimF] = 2.058e-02 x[C.KexF] = 7.998e-02 x[C.p63] = 1.731e+00 x[C.KF31] = 3.337e-03 x[C.nF31] = 1.001e+00 x[C.a] = 3.380e+02 x[C.Vn] = 2.200e-01 x[C.Vc] = 9.400e-01 x[C.Ligand] = 0.000e+00 x[C.EGF] = 0.000e+00 x[C.HRG] = 1.000e+00 x[C.noligand] = 2.000e+00

    def initial_values(): y0 = [0] * V.NUM y0[V.CREBn] = 1.000e+03 y0[V.ERKc] = 9.600e+02 y0[V.Elk1n] = 1.510e+03 y0[V.RSKc] = 3.530e+02 ```

  • Visualization

    • Close #45

  • Other

    • Update function to get the steady state for the untreated condition
    • Use scipy.integrate.ode
    • Use math.isnan for single floats
    • code refactoring
    • analysis/
    • estimation/

- Python
Published by himoto over 4 years ago

biomass - v0.3.4

Updates:

Parameter estimation

  • Fix search bounds, mutation and popsize in the differential evolution method.

Models

Test

  • Update test paramter sets

- Python
Published by himoto almost 5 years ago

biomass - v0.3.3

Update optimize

  • Add new option: initial_threshold

    • initial_threshold : float (default: 1e12) > Threshold on objective function value used to generate initial population. > Default value is 1e12 (numerically solvable).

```python def optimize( model: ModelObject, start: int, end: Optional[int] = None, options: Optional[dict] = None, ) -> None: """ Run GA for parameter estimation.

Paremters
---------
model : ModelObject
    Model for parameter estimation.

start : int
    Index of parameter set to estimate.

end : int, optional
    When `end` is specified, parameter sets from `start` to `end` will be estimated.

options : dict, optional
    popsize : int (default: 5)
        A multiplier for setting the total population size.
        The population has popsize * len(search_param) individuals.

    max_generation : int (default: 10000)
        Stop optimization if Generation > max_generation.

    initial_threshold : float (default: 1e12)
        Threshold on objective function value used to generate initial population.
        Default value is 1e12 (numerically solvable).

    allowable_error : float (default: 0.0)
        Stop optimization if Best Fitness <= allowable_error.

    local_search_method : str (default: 'mutation')
        Method used in local search. Should be one of
        * 'mutation' : NDM/MGG
        * 'Powell' : Modified Powell method
        * 'DE' : Differential Evolution (strategy: best2bin)

    n_children : int (default: 200)
        (method='mutation') The number of children generated in NDM/MGG.

    maxiter : int (default: 10)
        (method='Powell' or 'DE') The maximum number of iterations
        over which the entire population is evolved.

    workers : int (default: -1 if `end` is None else 1)
        (method='DE') The population is subdivided into workers sections and
        evaluated in parallel (uses multiprocessing.Pool). Supply -1 to use
        all available CPU cores. Set workers to 1 when searching multiple
        parameter sets simultaneously.

    overwrite : bool (default: False)
        If True, the out/n folder will be overwritten.

Example
-------
>>> from biomass.models import Nakakuki_Cell_2010
>>> from biomass import optimize
>>> model = Nakakuki_Cell_2010.create()
>>> optimize(
        model=model, start=1, end=10,
        options={
            'max_generation': 10000,
            'allowable_error': 0.5
        }
    )
"""
...

```

Update run_analysis

```python def runanalysis( model: ModelObject, target: str, metric: str = "integral", style: str = "barplot", saveformat: str = "pdf", options: Optional[dict] = None, ) -> None: """ Perform sensitivity analysis to identify critical parameters, species or reactions in the complex biological network.

The sensitivity S(y,x) was calculated according to the following equation:
S(y,x) = d ln(yi) / d ln (xj), where yi is the signaling metric and xj is
each nonzero species, parameter value or reaction rate.

Paremters
---------
model : ModelObject
    Model for sensitivity analysis.

target : str
    * 'reaction'
    * 'initial_condition'
    * 'parameter'

metric : str (default: 'integral')
    * 'maximum' : The maximum value.
    * 'minimum' : The minimum value.
    * 'argmax' : The time to reach the maximum value.
    * 'argmin' : The time to reach the minimum value.
    * 'timepoint' : The simulated value at the time point set via options['timepoint'].
    * 'duration' :  The time it takes to decline below the threshold set via options['duration'].
    * 'integral' : The integral of concentration over the observation time.

style : str (default: 'barplot')
    * 'barplot'
    * 'heatmap'

save_format : str (default: "pdf")
    Either "png" or "pdf", indicating whether to save figures
    as png or pdf format.

options : dict, optional
    show_indices : bool (default: True)
        (target == 'reaction') Set to True to put reaction index on each bar.

    excluded_params : list of strings
        (target == 'parameter') List of parameters which are not used for analysis.

    excluded_initials : list of strings
        (target == 'initial_condition') List of species which are not used for analysis.

    timepoint : int (default: model.sim.t[-1])
        (metric == 'timepoint') Which timepoint to use.

    duration : float (default: 0.5)
        (metric == 'duration') 0.1 for 10% of its maximum.

Example
-------
>>> from biomass.models import Nakakuki_Cell_2010
>>> from biomass import run_analysis
>>> model = Nakakuki_Cell_2010.create()

1. Parameter
>>> run_analysis(
        model,
        target='parameter',
        options = {
            'excluded_params': [
                'a', 'Vn', 'Vc', 'Ligand', 'EGF', 'HRG', 'no_ligand'
            ]
        }
    )

2. Initial condition
>>> run_analysis(
        model,
        target='initial_condition',
    )

3. Reaction
>>> run_analysis(
        model,
        target='reaction',
    )

"""
...

```

- Python
Published by himoto almost 5 years ago

biomass - v0.3.2

Coding style

Code is formatted with black. Coding style is checked with flake8 and isort.

``` $ pip install pre-commit

$ pre-commit install ```

Display model information

Rename function: ~~show_properties~~ → show_info

```python from biomass.models import NakakukiCell2010

NakakukiCell2010.show_info() ```

↓

```

NakakukiCell2010 information

36 species 115 parameters, of which 75 to be estimated ```

Add new method to OptimizationResults: trace_obj

Visualize objective function traces for different optimization runs.

```python from biomass.models import NakakukiCell2010 from biomass.result import OptimizationResults

model = NakakukiCell2010.create() res = OptimizationResults(model)

res.trace_obj() ```

- Python
Published by himoto almost 5 years ago

biomass - v0.3.1

Updates:

New model

Dynamic pathway model of TNFα-induced NFκB signal transduction

Oppelt, A. et al. Model-based identification of TNFα-induced IKKβ-mediated and IκBα-mediated regulation of NFκB signal transduction as a tool to quantify the impact of drug-induced liver injury compounds. npj Syst. Biol. Appl. 4, 23 (2018). https://doi.org/10.1038/s41540-018-0058-z

Sensitivity analysis

New signaling metrics

  • 'argmax' : The time to reach the maximum value.
  • 'argmin' : The time to reach the minimum value.
  • 'timepoint' : The simulated value at the time point set via options['timepoint'].
  • 'duration' : The time it takes to decline below the threshold set via options['duration'].

Parameter estimation

  • Set mutation constant (differential weight: F) to 0.1

  • Set recombination constant (crossover probability: CR) to 0.9

- Python
Published by himoto almost 5 years ago

biomass - v0.3.0 (January 2021)

Updates:

  • Use BioMassModel for the first argument of core functions

Example usage

  1. Create an executable model

```python from biomass.models import NakakukiCell2010

model = NakakukiCell2010.create() ```

  1. Estimate model parameters from experimental data

```python from biomass import optimize

optimize( model=model, start=1, options={ "popsize": 3, "maxgeneration": 1000, "allowableerror": 0.5, "localsearchmethod": "DE", } ) ```

  1. Export optimized parameters in CSV format

```python from biomass.result import OptimizationResults

res = OptimizationResults(model) res.to_csv() ```

  1. Visualize simulation results

```python from biomass import run_simulation

runsimulation(model, viztype='average', show_all=False, stdev=True) ```

  1. Perform sensitivity analysis

```python from biomass import run_analysis

run_analysis(model, target='reaction', metric='integral', style='barplot') ```

- Python
Published by himoto almost 5 years ago

biomass - v0.2.3

- Python
Published by himoto about 5 years ago

biomass - v0.2.2

Updates:

Added new local search method: "Powell" and "DE"

```python def optimize(model, *args, options: Optional[dict] = None) -> None: """ Run GA for parameter estimation.

Paremters
---------
model : module
    Model for parameter estimation.

options: dict, optional
    popsize : int (default: 5)
        A multiplier for setting the total population size.
        The population has popsize * len(search_param) individuals.

    max_generation : int (default: 10000)
        Stop if Generation > max_generation.

    allowable_error : float (default: 0.0)
        Stop if Best Fitness <= allowable_error.

    local_search_method : str (default: 'mutation')
        Method used in local search. Should be one of
        - 'mutation' : NDM/MGG
        - 'Powell' : Modified Powell method
        - 'DE' : Differential Evolution (strategy: best2bin)

    n_children : int (default: 200)
        (method='mutation') The number of children generated in NDM/MGG.

    workers : int (default: -1 if len(args) == 1 else 1)
        (method='DE') The population is subdivided into workers sections and
        evaluated in parallel (uses multiprocessing.Pool). Supply -1 to use
        all available CPU cores. Set workers to 1 when searching multiple
        parameter sets simultaneously.

    overwrite : bool (default: False)
        If True, the out/n folder will be overwritten.
"""

```

Example usage

```python from biomass.models import NakakukiCell2010 from biomass import optimize

optimize( NakakukiCell2010, 1, options={ 'popsize': 3, 'allowableerror': 0.5, 'localsearch_method': 'DE' } ) ```

- Python
Published by himoto about 5 years ago

biomass - v0.2.1

Fix: - result.py

- Python
Published by himoto about 5 years ago

biomass - v0.2.0 (November 2020)

Updates: - Change sim.normalization type from bool to dict (nested): python def __init__(self): super().__init__(perturbation={}) self.normalization = {} for obs_name in observables: self.normalization[obs_name] = { 'timepoint' : None, 'condition' : [] } - 'timepoint' : Optional[int] - The time point at which simulated values are normalized. If None, the maximum value will be used for normalization.

- ```'condition'``` : list of strings
    - The experimental conditions to use for normalization. If empty, all conditions defined in sim.conditions will be used.
  • Move documentation to https://github.com/okadalabipr/biomass_docs.jl

- Python
Published by himoto about 5 years ago

biomass - v0.1.2

- Python
Published by himoto about 5 years ago

biomass - v0.1.1

- Python
Published by himoto about 5 years ago

biomass - v0.1.0 (October 2020)

- Python
Published by himoto about 5 years ago