From 2b14234cabf1db9c1e956831412f128c529966e0 Mon Sep 17 00:00:00 2001 From: Jonathan Karr Date: Thu, 20 Jan 2022 19:54:10 -0500 Subject: [PATCH] feat: Added algorithms and characteristics for attractor methods in mpbn --- CHANGELOG.md | 3 + kisao.owl | 608 ++++++++++++++++++++++-------- kisao_full.owl | 2 +- libkisao/python/kisao/_version.py | 2 +- 4 files changed, 465 insertions(+), 150 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 1b60651..d55e6fd 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,8 @@ # Changelog +## 2.31 (OWL 2) +- Added algorithms and characteristics for attractor methods in mpbn + ## 2.30 (OWL 2) - Added and unified aggregation functions for SED-ML L1V4 - maximum ignoring NaN (`KISAO_0000828`) diff --git a/kisao.owl b/kisao.owl index 52bc176..14dafce 100644 --- a/kisao.owl +++ b/kisao.owl @@ -1,26 +1,26 @@ + xmlns:skos="http://www.w3.org/2004/02/skos/core#" + xmlns:kisao="http://www.biomodels.net/kisao/KISAO#" + xmlns:protege="http://protege.stanford.edu/plugins/owl/protege#"> + en Artistic License 2.0 - http://identifiers.org/pubmed/22027554 + This is a core version which contains all but deprecated classes. Kinetic Simulation Algorithm Ontology (KiSAO) - 2.30 http://co.mbine.org/standards/kisao - en + http://identifiers.org/pubmed/22027554 + 2.31 The Kinetic Simulation Algorithm Ontology (KiSAO) classifies algorithms available for the simulation and analysis of models in biology, and their characteristics and the parameters required for their use. - This is a core version which contains all but deprecated classes. @@ -14021,7 +14021,13 @@ This method only involves evaluations of f. This method is suitable for non-stif - + + + + + + + 2021-07-08 @@ -14057,6 +14063,12 @@ This method only involves evaluations of f. This method is suitable for non-stif + + + + + + 2021-07-08 JRK true @@ -14070,6 +14082,12 @@ This method only involves evaluations of f. This method is suitable for non-stif + + + + + + 2021-07-08 JRK true @@ -14540,6 +14558,258 @@ This method only involves evaluations of f. This method is suitable for non-stif + + + + + 2022-01-20 + JRK + LP + logical network + A network of logical-valued (an enumeration, such as a set of integers) variables. + + + + + + + + + 2022-01-20 + JRK + LP + boolean network + A network of Boolean-valued variables. + + + + + + + + + 2022-01-20 + JRK + LP + locally-monotone Boolean network + Boolean network where each regulator is either an activator or an inhibitor, but cannot be both. + + + + + + + + + 2022-01-20 + JRK + logical variable + A variable whose value can be one of an enumerated set of possible values such as ON/OFF, HIGH/MEDIUM/LOW, or a set integers (e.g., 0, 1, 2). + + + + + + + + + 2022-01-20 + JRK + Boolean variable + A variable whose value can be TRUE/FALSE (e.g., ON/OFF, YES/NO, 1/0). + + + + + + + + + 2022-01-20 + JRK + LP + most permissive updating policy + http://identifiers.org/doi:10.1038/s41467-020-18112-5 + The most permissive updating policy captures behaviors of any compatible quantitative model. + + + + + http://identifiers.org/doi:10.1038/s41467-020-18112-5 + Loïc Paulevé, Juraj Kolčák, Thomas Chatain, Stefan Haar. Reconciling qualitative, abstract, and scalable modeling of biological networks. Nat Commun 11(1):4256 (2020). + + + + + + + + + + + + + + + + + + + + + 2022-01-20 + JRK + LP + http://identifiers.org/biosimulators/mpbn + Paulevé ASP-based fixed point identification + + + + + http://identifiers.org/biosimulators/mpbn + mpbn + + + + + + + + + + + + + + + + + + + + + 2022-01-20 + JRK + LP + http://identifiers.org/biosimulators/mpbn + Paulevé ASP-based minimal trap space identification + + + + + http://identifiers.org/biosimulators/mpbn + mpbn + + + + + + + + + + + + + + + 2022-01-20 + JRK + LP + http://identifiers.org/biosimulators/mpbn + logical model attractor identification method + + + + + http://identifiers.org/biosimulators/mpbn + mpbn + + + + + + + + + + + + + + + + + + + + + + + + + + + 2022-01-20 + JRK + LP + http://identifiers.org/biosimulators/mpbn + Paulevé ASP-based most permissive attractor identification + + + + + http://identifiers.org/biosimulators/mpbn + mpbn + + + + + + + + + 2022-01-20 + JRK + trap space + + + + + + + + + 2022-01-20 + JRK + stable state + steady state + + + + + + + + + 2022-01-20 + JRK + minimal trap space + + + + + + + + + 2022-01-20 + JRK + attractor + + + + @@ -14960,6 +15230,147 @@ This method only involves evaluations of f. This method is suitable for non-stif The maximum of a set of values. If the values contain NaN the maximum is NaN. + + + + + + 06-03-2021 + LPS + true + model and simulation property + A variable of a model or simulation. + + + + + + + + + 06-03-2021 + LPS + time + The implied time variable of the model state. + + + + + + + + + + + + + + + + + + + + + 06-03-2021 + LPS + rate of change + rate + The rate of change of one variable with respect to a second variable. + + + + + + + + + + + + + + + 06-03-2021 + LPS + concentration control coefficient matrix (scaled) + The scaled concentration control coefficient matrix. The dimensions are species by reactions. + + + + + + + + + + + + + + + 06-03-2021 + LPS + amount + The extensive quantity amount. + + + + + + + + + + + + + + + 06-03-2021 + LPS + particle number + The extensive quantity particle number, or, the molar amount of the entity multiplied by Avogadro's number. + + + + + + + + + + + + + + + 06-03-2021 + LPS + concentration + The intensive quantity concentration, or, the amount of the entity with respect to the entity in which it resides. + + + + + + + + + + + + + + + 06-03-2021 + LPS + temperature + The intensive quantity temperature. + + + + @@ -14970,6 +15381,8 @@ This method only involves evaluations of f. This method is suitable for non-stif The minimum of a set of values. If the values contain NaN the minimum is NaN. + + @@ -14980,6 +15393,8 @@ This method only involves evaluations of f. This method is suitable for non-stif The mean of a set of values. If the values contain NaN the mean is NaN. + + @@ -14990,6 +15405,8 @@ This method only involves evaluations of f. This method is suitable for non-stif The standard deviation of a set of values. If the values contain NaN the standard deviation is NaN. + + @@ -15000,6 +15417,8 @@ This method only involves evaluations of f. This method is suitable for non-stif The standard error of a set of values. If the values contain NaN the standard deviation is NaN. + + @@ -15010,6 +15429,8 @@ This method only involves evaluations of f. This method is suitable for non-stif The sum of a set of values, ignoring Nan entries. + + @@ -15019,6 +15440,7 @@ This method only involves evaluations of f. This method is suitable for non-stif sum The sum of a set of values. If the values contain NaN the sum is NaN. + @@ -15030,6 +15452,8 @@ This method only involves evaluations of f. This method is suitable for non-stif product ignoring NaN The product of a set of values, ignoring Nan entries. + + @@ -15040,6 +15464,8 @@ This method only involves evaluations of f. This method is suitable for non-stif product The product of a set of values. If the values contain NaN the product is NaN. + + @@ -15050,6 +15476,8 @@ This method only involves evaluations of f. This method is suitable for non-stif cumulative sum ignoring NaN The cumulative sum of a set of values, ignoring Nan entries. + + @@ -15060,6 +15488,8 @@ This method only involves evaluations of f. This method is suitable for non-stif cumulative sum The cumulative sum of a set of values. If the values contain NaN the cumulative sum is NaN. + + @@ -15070,6 +15500,8 @@ This method only involves evaluations of f. This method is suitable for non-stif cumulative product ignoring NaN The cumulative product of a set of values, ignoring Nan entries. + + @@ -15081,6 +15513,8 @@ This method only involves evaluations of f. This method is suitable for non-stif The cumulative product of a set of values. If the values contain NaN the cumulative product is NaN. + + @@ -15090,6 +15524,8 @@ This method only involves evaluations of f. This method is suitable for non-stif count ignoring NaN The number of non-zero elements of a set of values, ignoring Nan entries. + + @@ -15100,6 +15536,8 @@ This method only involves evaluations of f. This method is suitable for non-stif count The number of non-zero elements of a set of values. If the values contain NaN the count is NaN. + + @@ -15110,6 +15548,8 @@ This method only involves evaluations of f. This method is suitable for non-stif length ignoring NaN The number of elements of a set of values, ignoring Nan entries. + + @@ -15120,6 +15560,8 @@ This method only involves evaluations of f. This method is suitable for non-stif length The number of elements of a set of values. + + @@ -15130,6 +15572,8 @@ This method only involves evaluations of f. This method is suitable for non-stif median ignoring NaN The median of a set of values, ignoring Nan entries. + + @@ -15141,6 +15585,8 @@ This method only involves evaluations of f. This method is suitable for non-stif The median of a set of values. If the values contain NaN the median is NaN. + + @@ -15150,6 +15596,8 @@ This method only involves evaluations of f. This method is suitable for non-stif variance ignoring NaN The variance of a set of values, ignoring Nan entries. + + @@ -15160,145 +15608,9 @@ This method only involves evaluations of f. This method is suitable for non-stif variance The variance of a set of values. If the values contain NaN the variance is NaN. - - - - - - 06-03-2021 - LPS - true - model and simulation property - A variable of a model or simulation. - - - - - - - - 06-03-2021 - LPS - time - The implied time variable of the model state. - - - - - - - - - - - - - - - - - - - - - 06-03-2021 - LPS - rate of change - rate - The rate of change of one variable with respect to a second variable. - - - - - - - - - - - - 06-03-2021 - LPS - concentration control coefficient matrix (scaled) - The scaled concentration control coefficient matrix. The dimensions are species by reactions. - - - - - - - - - - - - - - - 06-03-2021 - LPS - amount - The extensive quantity amount. - - - - - - - - - - - - - - - 06-03-2021 - LPS - particle number - The extensive quantity particle number, or, the molar amount of the entity multiplied by Avogadro's number. - - - - - - - - - - - - - - - 06-03-2021 - LPS - concentration - The intensive quantity concentration, or, the amount of the entity with respect to the entity in which it resides. - - - - - - - - - - - - - - - 06-03-2021 - LPS - temperature - The intensive quantity temperature. - - - + diff --git a/kisao_full.owl b/kisao_full.owl index 19526ba..b56de40 100644 --- a/kisao_full.owl +++ b/kisao_full.owl @@ -19,7 +19,7 @@ Kinetic Simulation Algorithm Ontology (full version, containing deprecated classes) http://co.mbine.org/standards/kisao http://identifiers.org/pubmed/22027554 - 2.30 + 2.31 The Kinetic Simulation Algorithm Ontology (KiSAO) classifies algorithms available for the simulation and analysis of models in biology, and their characteristics and the parameters required for their use. diff --git a/libkisao/python/kisao/_version.py b/libkisao/python/kisao/_version.py index 728f998..f0d1069 100644 --- a/libkisao/python/kisao/_version.py +++ b/libkisao/python/kisao/_version.py @@ -1 +1 @@ -__version__ = '2.30' +__version__ = '2.31'