scholarly journals BioModels Parameters: a treasure trove of parameter values from published systems biology models

2020 ◽  
Vol 36 (17) ◽  
pp. 4649-4654
Author(s):  
Mihai Glont ◽  
Chinmay Arankalle ◽  
Krishna Tiwari ◽  
Tung V N Nguyen ◽  
Henning Hermjakob ◽  
...  
Keyword(s):  
Systems Biology ◽  
Model Fitting ◽  
Language Models ◽  
Supplementary Information ◽  
Rate Equations ◽  
Model Parameters ◽  
Systems Biology Markup Language ◽  
Estimation Of Model Parameters ◽  
Parameter Ranges ◽  
Parameter Values

Abstract Motivation One of the major bottlenecks in building systems biology models is identification and estimation of model parameters for model calibration. Searching for model parameters from published literature and models is an essential, yet laborious task. Results We have developed a new service, BioModels Parameters, to facilitate search and retrieval of parameter values from the Systems Biology Markup Language models stored in BioModels. Modellers can now directly search for a model entity (e.g. a protein or drug) to retrieve the rate equations describing it; the associated parameter values (e.g. degradation rate, production rate, Kcat, Michaelis–Menten constant, etc.) and the initial concentrations. Currently, BioModels Parameters contains entries from over 84,000 reactions and 60 different taxa with cross-references. The retrieved rate equations and parameters can be used for scanning parameter ranges, model fitting and model extension. Thus, BioModels Parameters will be a valuable service for systems biology modellers. Availability and implementation The data are accessible via web interface and API. BioModels Parameters is free to use and is publicly available at https://www.ebi.ac.uk/biomodels/parameterSearch. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals cd2sbgnml: bidirectional conversion between CellDesigner and SBGN formats

2020 ◽  
Vol 36 (8) ◽  
pp. 2620-2622 ◽  
Author(s):  
Irina Balaur ◽  
Ludovic Roy ◽  
Alexander Mazein ◽  
S Gökberk Karaca ◽  
Ugur Dogrusoz ◽  
...  
Keyword(s):  
Systems Biology ◽  
Web Service ◽  
Large Scale ◽  
Supplementary Information ◽  
Markup Language ◽  
File Format ◽  
Signalling Network ◽  
Lesser General Public License ◽  
Systems Biology Markup Language ◽  
General Public License

Abstract Motivation CellDesigner is a well-established biological map editor used in many large-scale scientific efforts. However, the interoperability between the Systems Biology Graphical Notation (SBGN) Markup Language (SBGN-ML) and the CellDesigner’s proprietary Systems Biology Markup Language (SBML) extension formats remains a challenge due to the proprietary extensions used in CellDesigner files. Results We introduce a library named cd2sbgnml and an associated web service for bidirectional conversion between CellDesigner’s proprietary SBML extension and SBGN-ML formats. We discuss the functionality of the cd2sbgnml converter, which was successfully used for the translation of comprehensive large-scale diagrams such as the RECON Human Metabolic network and the complete Atlas of Cancer Signalling Network, from the CellDesigner file format into SBGN-ML. Availability and implementation The cd2sbgnml conversion library and the web service were developed in Java, and distributed under the GNU Lesser General Public License v3.0. The sources along with a set of examples are available on GitHub (https://github.com/sbgn/cd2sbgnml and https://github.com/sbgn/cd2sbgnml-webservice, respectively). Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals XitoSBML: A Modeling Tool for Creating Spatial Systems Biology Markup Language Models From Microscopic Images

2019 ◽  
Vol 10 ◽  
Author(s):  
Kaito Ii ◽  
Kota Mashimo ◽  
Mitsunori Ozeki ◽  
Takahiro G. Yamada ◽  
Noriko Hiroi ◽  
...  
Keyword(s):  
Systems Biology ◽  
Language Models ◽  
Markup Language ◽  
Modeling Tool ◽  
Microscopic Images ◽  
Spatial Systems ◽  
Systems Biology Markup Language

scholarly journals The chaos in calibrating crop models

2020 ◽  
Author(s):  
Daniel Wallach ◽  
Taru Palosuo ◽  
Peter Thorburn ◽  
Zvi Hochman ◽  
Emmanuelle Gourdain ◽  
...  
Keyword(s):  
Experimental Data ◽  
Model Calibration ◽  
Crop Model ◽  
Process Models ◽  
Model Parameters ◽  
Model Structure ◽  
Crop Models ◽  
Estimation Of Model Parameters ◽  
Parameter Values ◽  
Made In

Calibration, that is the estimation of model parameters based on fitting the model to experimental data, is among the first steps in essentially every application of crop models and process models in other fields and has an important impact on simulated values. The goal of this study is to develop a comprehensive list of the decisions involved in calibration and to identify the range of choices made in practice, as groundwork for developing guidelines for crop model calibration starting with phenology. Three groups of decisions are identified; the criterion for choosing the parameter values, the choice of parameters to estimate and numerical aspects of parameter estimation. It is found that in practice there is a large diversity of choices for every decision, even among modeling groups using the same model structure. These findings are relevant to process models in other fields.

scholarly journals Connecting mathematical models to genomes: joint estimation of model parameters and genome-wide marker effects on these parameters

2020 ◽  
Vol 36 (10) ◽  
pp. 3169-3176 ◽  
Author(s):  
Akio Onogi
Keyword(s):  
Mathematical Models ◽  
R Package ◽  
Joint Estimation ◽  
Supplementary Information ◽  
Joint Analysis ◽  
Accurate Estimation ◽  
Model Parameters ◽  
Statistical Framework ◽  
Genome Wide ◽  
Estimation Of Model Parameters

Abstract Motivation Parameters of mathematical models used in biology may be genotype-specific and regarded as new traits. Therefore, an accurate estimation of these parameters and the association mapping on the estimated parameters can lead to important findings regarding the genetic architecture of biological processes. In this study, a statistical framework for a joint analysis (JA) of model parameters and genome-wide marker effects on these parameters was proposed and evaluated. Results In the simulation analyses based on different types of mathematical models, the JA inferred the model parameters and identified the responsible genomic regions more accurately than the independent analysis (IA). The JA of real plant data provided interesting insights into photosensitivity, which were uncovered by the IA. Availability and implementation The statistical framework is provided by the R package GenomeBasedModel available at https://github.com/Onogi/GenomeBasedModel. All R and C++ scripts used in this study are also available at the site. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals A NEW FOUR-PARAMETER WEIBULL DISTRIBUTION WITH APPLICATION TO FAILURE TIME DATA

2020 ◽  
Vol 4 (3) ◽  
pp. 563-575
Author(s):  
Aminu Suleiman Mohammed ◽  
Fidelis Ifeanyi Ugwuowo
Keyword(s):  
Maximum Likelihood ◽  
Weibull Distribution ◽  
Failure Time ◽  
Real Life ◽  
Model Parameters ◽  
Time Data ◽  
Lifetime Model ◽  
Estimation Of Model Parameters ◽  
Parameter Values ◽  
Maximum Likelihood Technique

A lifetime model called Transmuted Exponential-Weibull Distribution was proposed in this research. Several statistical properties were derived and presented in an explicit form. Maximum likelihood technique is employed for the estimation of model parameters, and a simulation study was performed to examine the behavior of various estimates under different sample sizes and initial parameter values. Through using real-life datasets, it was empirically shown that the new model provides sufficient fits relative to other existing models.

scholarly journals New models of atherosclerosis and multi-drug therapeutic interventions

2018 ◽  
Vol 35 (14) ◽  
pp. 2449-2457 ◽  
Author(s):  
Andrew Parton ◽  
Victoria McGilligan ◽  
Melody Chemaly ◽  
Maurice O’Kane ◽  
Steven Watterson
Keyword(s):  
Systems Biology ◽  
Computational Models ◽  
Laboratory Data ◽  
Therapeutic Interventions ◽  
Supplementary Information ◽  
Pharmaceutical Therapy ◽  
Systems Biology Markup Language ◽  
Supplementary Material

Abstract Motivation Atherosclerosis is amongst the leading causes of death globally. However, it is challenging to study in vivo or in vitro and no detailed, openly-available computational models exist. Clinical studies hint that pharmaceutical therapy may be possible. Here, we develop the first detailed, computational model of atherosclerosis and use it to develop multi-drug therapeutic hypotheses. Results We assembled a network describing atheroma development from the literature. Maps and mathematical models were produced using the Systems Biology Graphical Notation and Systems Biology Markup Language, respectively. The model was constrained against clinical and laboratory data. We identified five drugs that together potentially reverse advanced atheroma formation. Availability and implementation The map is available in the Supplementary Material in SBGN-ML format. The model is available in the Supplementary Material and from BioModels, a repository of SBML models, containing CellDesigner markup. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Process Identification Using Relay Shifting Method for Auto Tuning of PID Controller

2019 ◽  
Vol 292 ◽  
pp. 01015
Author(s):  
Milan Hofreiter ◽  
Alžběta Hornychová
Keyword(s):  
Frequency Response ◽  
Process Model ◽  
Model Fitting ◽  
Constant Load ◽  
Model Parameters ◽  
Relay Feedback ◽  
Model Transfer ◽  
Estimation Of Model Parameters ◽  
Single Relay ◽  
To Receive

The paper describes the use of a recently introduced relay shifting method for estimation parameters of a second order time delayed model. The aim is to obtain a process model for setting PID control parameters. For this purpose, an algorithm is designed for estimation of model parameters from two frequency response points obtained from a single relay feedback test without any assumptions about a model transfer function. The relay shifting method is slightly modified here by using an integrator to receive the frequency response points in positions more suitable for model fitting. This modification enables to better estimate the static gain even under constant load disturbance. The proposed solution is demonstrated on simulated examples.

Sign in / Sign up

Export Citation Format

Share Document