Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Overview table: link to respective publication #149

Merged
merged 3 commits into from
Feb 7, 2022
Merged

Overview table: link to respective publication #149

Show file tree
Hide file tree
Changes from 1 commit
Commits
Show all changes
3 commits
Select commit Hold shift + click to select a range
1309fd3
Overview table: link to respective publication
dweindl Feb 7, 2022
d807e93
Update Benchmark-Models/model_info.py
dweindl Feb 7, 2022
4959adb
review comments
dweindl Feb 7, 2022
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
27 changes: 25 additions & 2 deletions Benchmark-Models/model_info.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -2,13 +2,13 @@
"""Print some stats for each benchmark problem"""

import os
from typing import Dict
from typing import Dict, List

import libsbml
import numpy as np
import pandas as pd
import petab


markdown_columns = {
'conditions': 'Conditions',
'estimated_parameters': 'Estimated Parameters',
Expand All @@ -17,6 +17,7 @@
'name': 'Model ID',
'observables': 'Observables',
'species': 'Species',
'described_by': 'References',
}

index_column = 'name'
Expand All @@ -42,9 +43,25 @@ def get_problem_info(
len(problem.measurement_df[petab.OBSERVABLE_ID].unique()),
'species':
len(problem.sbml_model.getListOfSpecies()),
'described_by':
get_described_by(problem.sbml_model),
}


def get_described_by(sbml_model: libsbml.Model) -> List[str]:
"""Get publication URIs from SBML is-described-by annotatation"""
dweindl marked this conversation as resolved.
Show resolved Hide resolved
cv_terms = sbml_model.getCVTerms()
reference_uris = []
for anno in cv_terms:
if anno.getBiologicalQualifierType() != libsbml.BQB_IS_DESCRIBED_BY:
continue
resources = anno.getResources()
for i in range(resources.getNumAttributes()):
uri = resources.getValue(i)
reference_uris.append(uri)
return reference_uris


def get_overview_table(path: str = None) -> pd.DataFrame:
"""Get overview table with stats for all benchmark problems"""
model_list = os.scandir(path=path)
Expand All @@ -70,8 +87,14 @@ def main(
pd.options.display.width = 0

if markdown:
# directory as markdown link
df.rename(index=lambda x: f"[{x}](Benchmark-Models/{x}/)",
inplace=True)
# references to markdown links
df['described_by'] = df['described_by'].apply(
lambda x: " ".join([f"[\\[{i + 1}\\]]({uri})"
for i, uri in enumerate(x)])
)
df.index.rename(markdown_columns[index_column], inplace=True)
df.rename(columns=markdown_columns, inplace=True)
print(df.to_markdown())
Expand Down
63 changes: 32 additions & 31 deletions README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -4,37 +4,38 @@ A collection of mathematical models with experimental data in the [PEtab](https:
Contributions to the collection are very welcome. For this, please create a new branch, add your model and test your files with the provided functions, and start a pull request. We will then check your model and merge it into the collection. We are continuously working on the extension of the collection.

## Overview
| Model ID | Conditions | Estimated Parameters | Events | Measurements | Observables | Species |
|:---------------------------------------------------------------------------------------------|-------------:|-----------------------:|---------:|---------------:|--------------:|----------:|
| [Alkan_SciSignal2018](Benchmark-Models/Alkan_SciSignal2018/) | 73 | 56 | 0 | 1733 | 12 | 36 |
| [Bachmann_MSB2011](Benchmark-Models/Bachmann_MSB2011/) | 36 | 113 | 0 | 541 | 20 | 25 |
| [Beer_MolBioSystems2014](Benchmark-Models/Beer_MolBioSystems2014/) | 19 | 72 | 0 | 27132 | 2 | 4 |
| [Bertozzi_PNAS2020](Benchmark-Models/Bertozzi_PNAS2020/) | 2 | 3 | 0 | 138 | 1 | 3 |
| [Blasi_CellSystems2016](Benchmark-Models/Blasi_CellSystems2016/) | 1 | 9 | 0 | 252 | 15 | 16 |
| [Boehm_JProteomeRes2014](Benchmark-Models/Boehm_JProteomeRes2014/) | 1 | 9 | 0 | 48 | 3 | 8 |
| [Borghans_BiophysChem1997](Benchmark-Models/Borghans_BiophysChem1997/) | 1 | 23 | 0 | 111 | 1 | 3 |
| [Brannmark_JBC2010](Benchmark-Models/Brannmark_JBC2010/) | 8 | 22 | 0 | 43 | 3 | 9 |
| [Bruno_JExpBot2016](Benchmark-Models/Bruno_JExpBot2016/) | 6 | 13 | 0 | 77 | 5 | 7 |
| [Chen_MSB2009](Benchmark-Models/Chen_MSB2009/) | 4 | 155 | 0 | 120 | 3 | 500 |
| [Crauste_CellSystems2017](Benchmark-Models/Crauste_CellSystems2017/) | 1 | 12 | 0 | 21 | 4 | 5 |
| [Elowitz_Nature2000](Benchmark-Models/Elowitz_Nature2000/) | 1 | 21 | 0 | 58 | 1 | 8 |
| [Fiedler_BMC2016](Benchmark-Models/Fiedler_BMC2016/) | 3 | 22 | 0 | 72 | 2 | 6 |
| [Fujita_SciSignal2010](Benchmark-Models/Fujita_SciSignal2010/) | 6 | 19 | 0 | 144 | 3 | 9 |
| [Giordano_Nature2020](Benchmark-Models/Giordano_Nature2020/) | 1 | 50 | 0 | 313 | 7 | 13 |
| [Isensee_JCB2018](Benchmark-Models/Isensee_JCB2018/) | 123 | 46 | 0 | 687 | 3 | 25 |
| [Laske_PLOSComputBiol2019](Benchmark-Models/Laske_PLOSComputBiol2019/) | 3 | 13 | 0 | 42 | 13 | 41 |
| [Lucarelli_CellSystems2018](Benchmark-Models/Lucarelli_CellSystems2018/) | 16 | 84 | 0 | 1755 | 65 | 33 |
| [Okuonghae_ChaosSolitonsFractals2020](Benchmark-Models/Okuonghae_ChaosSolitonsFractals2020/) | 1 | 16 | 0 | 92 | 2 | 9 |
| [Oliveira_NatCommun2021](Benchmark-Models/Oliveira_NatCommun2021/) | 1 | 12 | 0 | 120 | 2 | 9 |
| [Perelson_Science1996](Benchmark-Models/Perelson_Science1996/) | 1 | 3 | 0 | 16 | 1 | 4 |
| [Rahman_MBS2016](Benchmark-Models/Rahman_MBS2016/) | 1 | 9 | 0 | 23 | 1 | 7 |
| [Raimundez_PCB2020](Benchmark-Models/Raimundez_PCB2020/) | 170 | 136 | 0 | 627 | 79 | 22 |
| [SalazarCavazos_MBoC2020](Benchmark-Models/SalazarCavazos_MBoC2020/) | 4 | 6 | 0 | 18 | 3 | 75 |
| [Schwen_PONE2014](Benchmark-Models/Schwen_PONE2014/) | 19 | 30 | 0 | 286 | 4 | 11 |
| [Sneyd_PNAS2002](Benchmark-Models/Sneyd_PNAS2002/) | 9 | 15 | 0 | 135 | 1 | 6 |
| [Weber_BMC2015](Benchmark-Models/Weber_BMC2015/) | 2 | 36 | 0 | 135 | 8 | 7 |
| [Zhao_QuantBiol2020](Benchmark-Models/Zhao_QuantBiol2020/) | 7 | 28 | 0 | 82 | 1 | 5 |
| [Zheng_PNAS2012](Benchmark-Models/Zheng_PNAS2012/) | 1 | 46 | 0 | 60 | 15 | 15 |

| Model ID | Conditions | Estimated Parameters | Events | Measurements | Observables | Species | References |
|:---------------------------------------------------------------------------------------------|-------------:|-----------------------:|---------:|---------------:|--------------:|----------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| [Alkan_SciSignal2018](Benchmark-Models/Alkan_SciSignal2018/) | 73 | 56 | 0 | 1733 | 12 | 36 | [\[1\]](http://identifiers.org/doi/10.1126/scisignal.aat0229) |
| [Bachmann_MSB2011](Benchmark-Models/Bachmann_MSB2011/) | 36 | 113 | 0 | 541 | 20 | 25 | [\[1\]](http://identifiers.org/doi/10.1038/msb.2011.50) |
| [Beer_MolBioSystems2014](Benchmark-Models/Beer_MolBioSystems2014/) | 19 | 72 | 0 | 27132 | 2 | 4 | [\[1\]](http://identifiers.org/doi/10.1039/c3mb70594c) |
| [Bertozzi_PNAS2020](Benchmark-Models/Bertozzi_PNAS2020/) | 2 | 3 | 0 | 138 | 1 | 3 | [\[1\]](http://identifiers.org/pubmed/32616574) |
| [Blasi_CellSystems2016](Benchmark-Models/Blasi_CellSystems2016/) | 1 | 9 | 0 | 252 | 15 | 16 | [\[1\]](http://identifiers.org/doi/10.1016/j.cels.2016.01.002) |
| [Boehm_JProteomeRes2014](Benchmark-Models/Boehm_JProteomeRes2014/) | 1 | 9 | 0 | 48 | 3 | 8 | [\[1\]](http://identifiers.org/doi/10.1021/pr5006923) |
| [Borghans_BiophysChem1997](Benchmark-Models/Borghans_BiophysChem1997/) | 1 | 23 | 0 | 111 | 1 | 3 | [\[1\]](http://identifiers.org/doi/10.1016/s0301-4622(97)00010-0) |
| [Brannmark_JBC2010](Benchmark-Models/Brannmark_JBC2010/) | 8 | 22 | 0 | 43 | 3 | 9 | [\[1\]](http://identifiers.org/doi/10.1074/jbc.M110.106849) |
| [Bruno_JExpBot2016](Benchmark-Models/Bruno_JExpBot2016/) | 6 | 13 | 0 | 77 | 5 | 7 | [\[1\]](http://identifiers.org/doi/10.1093/jxb/erw356) |
| [Chen_MSB2009](Benchmark-Models/Chen_MSB2009/) | 4 | 155 | 0 | 120 | 3 | 500 | [\[1\]](http://identifiers.org/doi/10.1038/msb.2008.74) |
| [Crauste_CellSystems2017](Benchmark-Models/Crauste_CellSystems2017/) | 1 | 12 | 0 | 21 | 4 | 5 | [\[1\]](http://identifiers.org/doi/10.1016/j.cels.2017.01.014) |
| [Elowitz_Nature2000](Benchmark-Models/Elowitz_Nature2000/) | 1 | 21 | 0 | 58 | 1 | 8 | [\[1\]](http://identifiers.org/doi/10.1038/35002125) |
| [Fiedler_BMC2016](Benchmark-Models/Fiedler_BMC2016/) | 3 | 22 | 0 | 72 | 2 | 6 | [\[1\]](http://identifiers.org/doi/10.1186/s12918-016-0319-7) |
| [Fujita_SciSignal2010](Benchmark-Models/Fujita_SciSignal2010/) | 6 | 19 | 0 | 144 | 3 | 9 | |
| [Giordano_Nature2020](Benchmark-Models/Giordano_Nature2020/) | 1 | 50 | 0 | 313 | 7 | 13 | [\[1\]](http://identifiers.org/pubmed/32322102) |
| [Isensee_JCB2018](Benchmark-Models/Isensee_JCB2018/) | 123 | 46 | 0 | 687 | 3 | 25 | [\[1\]](http://identifiers.org/doi/10.1083/jcb.201708053) |
| [Laske_PLOSComputBiol2019](Benchmark-Models/Laske_PLOSComputBiol2019/) | 3 | 13 | 0 | 42 | 13 | 41 | [\[1\]](http://identifiers.org/biomodels.db/BIOMD0000000463) [\[2\]](http://identifiers.org/biomodels.db/MODEL1307270000) [\[3\]](http://identifiers.org/pubmed/22593159) |
| [Lucarelli_CellSystems2018](Benchmark-Models/Lucarelli_CellSystems2018/) | 16 | 84 | 0 | 1755 | 65 | 33 | [\[1\]](http://identifiers.org/doi/10.1016/j.cels.2017.11.010) |
| [Okuonghae_ChaosSolitonsFractals2020](Benchmark-Models/Okuonghae_ChaosSolitonsFractals2020/) | 1 | 16 | 0 | 92 | 2 | 9 | |
| [Oliveira_NatCommun2021](Benchmark-Models/Oliveira_NatCommun2021/) | 1 | 12 | 0 | 120 | 2 | 9 | |
| [Perelson_Science1996](Benchmark-Models/Perelson_Science1996/) | 1 | 3 | 0 | 16 | 1 | 4 | [\[1\]](http://identifiers.org/doi/10.1126/science.271.5255.1582) |
| [Rahman_MBS2016](Benchmark-Models/Rahman_MBS2016/) | 1 | 9 | 0 | 23 | 1 | 7 | |
| [Raimundez_PCB2020](Benchmark-Models/Raimundez_PCB2020/) | 170 | 136 | 0 | 627 | 79 | 22 | |
| [SalazarCavazos_MBoC2020](Benchmark-Models/SalazarCavazos_MBoC2020/) | 4 | 6 | 0 | 18 | 3 | 75 | |
| [Schwen_PONE2014](Benchmark-Models/Schwen_PONE2014/) | 19 | 30 | 0 | 286 | 4 | 11 | [\[1\]](http://identifiers.org/doi/10.1371/journal.pone.0133653) |
| [Sneyd_PNAS2002](Benchmark-Models/Sneyd_PNAS2002/) | 9 | 15 | 0 | 135 | 1 | 6 | [\[1\]](http://identifiers.org/doi/10.1073/pnas.032281999) |
| [Weber_BMC2015](Benchmark-Models/Weber_BMC2015/) | 2 | 36 | 0 | 135 | 8 | 7 | [\[1\]](http://identifiers.org/doi/10.1186/s12918-015-0147-1) |
| [Zhao_QuantBiol2020](Benchmark-Models/Zhao_QuantBiol2020/) | 7 | 28 | 0 | 82 | 1 | 5 | [\[1\]](http://identifiers.org/pubmed/32219006) |
| [Zheng_PNAS2012](Benchmark-Models/Zheng_PNAS2012/) | 1 | 46 | 0 | 60 | 15 | 15 | [\[1\]](http://identifiers.org/doi/10.1073/pnas.1201240109) |

## License

Expand Down