Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Introduction to R01:11

Introduction to R

448
R is a powerful software environment for statistical computing and graphics. Originating as an implementation of the S language, developed at Bell Laboratories, R has evolved into a robust, open-source statistical software favored by statisticians and data scientists worldwide. Its comprehensive suite includes data manipulation, calculation, and graphical display capabilities, making it versatile for data analysis and visualization. Its programming language is at the core of R's...
448
Response Surface Methodology01:16

Response Surface Methodology

195
Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
195
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

68
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
68
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

88
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
88
Econometric Views (EViews)01:29

Econometric Views (EViews)

189
Econometric Views, often stylized as EViews, is a package that merges statistical analysis with econometric studies. It is designed to provide tools for time series analysis, forecasting, and econometric model simulation. The software originated from MicroTSP software and has evolved significantly since its inception in 1981. The history of EViews is marked by a continuous effort to enhance its computational speed and user interface. It was initially developed for large computing systems but...
189
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

607
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
607

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Complexity reduction by symmetry: Uncovering the minimal regulatory network for logical computation in bacteria.

PLoS computational biology·2025
Same author

Enhancement of essential cofactors for <i>in vivo</i> biocatalysis.

Faraday discussions·2024
Same author

Resource allocation modeling for autonomous prediction of plant cell phenotypes.

Metabolic engineering·2024
Same author

Optimal enzyme profiles in unbranched metabolic pathways.

Interface focus·2024
Same author

Complexity reduction by symmetry: uncovering the minimal regulatory network for logical computation in bacteria.

ArXiv·2023
Same author

A neural-mechanistic hybrid approach improving the predictive power of genome-scale metabolic models.

Nature communications·2023
Same journal

Region-aware bridge modeling enables interpretable mesoscale representation of spatial transcriptomic tissue sections.

Bioinformatics advances·2026
Same journal

Microbiome differential abundance methodologies to detect relevant taxa associated with chemotherapy toxicity rate in colorectal cancer.

Bioinformatics advances·2026
Same journal

maldipickr dereplicates microbial MALDI-TOF spectra to facilitate multiplexed isolation.

Bioinformatics advances·2026
Same journal

RAM-MSA: an anytime memory-bounded method for exact multiple sequence alignment using path finding.

Bioinformatics advances·2026
Same journal

Interpretable machine learning for low-sample multi-omics: a case study of ferret vaccine response.

Bioinformatics advances·2026
Same journal

DeepTaxa: a hybrid CNN-BERT framework for 16S rRNA taxonomic classification.

Bioinformatics advances·2026
See all related articles

Related Experiment Video

Updated: Jul 30, 2025

High-Throughput Metabolic Profiling for Model Refinements of Microalgae
11:07

High-Throughput Metabolic Profiling for Model Refinements of Microalgae

Published on: December 4, 2021

3.8K

RBAtools: a programming interface for Resource Balance Analysis models.

Oliver Bodeit1,2,3,4, Inès Ben Samir1, Jonathan R Karr5

  • 1MaIAGE, Université Paris-Saclay, INRAE, 78350 Jouy-en-Josas, France.

Bioinformatics Advances
|May 14, 2023
PubMed
Summary
This summary is machine-generated.

Resource Balance Analysis (RBA) models organism growth. The RBAtools Python package offers a user-friendly interface for RBA model construction, simulation, and analysis, enhancing accessibility for researchers.

More Related Videos

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.0K
Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.4K

Related Experiment Videos

Last Updated: Jul 30, 2025

High-Throughput Metabolic Profiling for Model Refinements of Microalgae
11:07

High-Throughput Metabolic Profiling for Model Refinements of Microalgae

Published on: December 4, 2021

3.8K
Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.0K
Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.4K

Area of Science:

  • Systems biology
  • Computational biology
  • Metabolic modeling

Background:

  • Resource allocation is crucial for organism fitness and evolutionary success.
  • Resource Balance Analysis (RBA) computationally models growth-optimal proteome configurations.
  • Existing RBA software lacks user-friendly interfaces and interoperability.

Purpose of the Study:

  • To introduce RBAtools, a Python package providing accessible RBA modeling capabilities.
  • To offer a flexible programming interface for custom RBA workflows.
  • To facilitate the modification and analysis of genome-scale RBA models.

Main Methods:

  • Development of the RBAtools Python package.
  • Implementation of high-level functions for simulation, model fitting, and analysis.
  • Representation of models and data in structured tables for interoperability.

Main Results:

  • RBAtools provides convenient access to RBA models.
  • The package enables custom workflow implementation and model modification.
  • Functions include simulation, parameter screens, sensitivity and variability analysis, and Pareto front construction.

Conclusions:

  • RBAtools enhances the accessibility and usability of RBA for researchers.
  • The package supports advanced analyses and data export for visualization.
  • RBAtools promotes wider application of RBA in systems and computational biology.