Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic Models: Compartment Models in Individual and Population Analysis

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...

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

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...

Pharmacokinetic Models: Comparison and Selection Criterion

Pharmacokinetic Models: Comparison and Selection Criterion

Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.

You might also read

Related Articles

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

Sort by

Same author

Dual-channel optogenetics in yeast for multiplexed light-based control of cellular processes and pathways.

Nature communications·2026

Same author

Optimizing HMG-CoA Synthase Expression for Enhanced Limonene Production in <i>Escherichia coli</i> through Temporal Transcription Modulation Using Optogenetics.

ACS synthetic biology·2024

Same author

A biological camera that captures and stores images directly into DNA.

Nature communications·2023

Same author

Editorial.

Engineering biology·2023

Same author

Future trends in synthetic biology in Asia.

Advanced genetics (Hoboken, N.J.)·2023

Same author

Highly Reversible Tunable Thermal-Repressible Split-T7 RNA Polymerases (Thermal-T7RNAPs) for Dynamic Gene Regulation.

ACS synthetic biology·2022

Same journal

A Multitask Prediction Framework for CircRNAs, Drugs, and Diseases Based on Multi-View Information Integration and Graph Contrastive Learning.

ACS synthetic biology·2026

Same journal

Engineering Modular Cargo Loading Strategies for Carboxysome-Derived Protein Particles.

ACS synthetic biology·2026

Same journal

Suppression of Salmonella Effectors with CRISPRi Controls the Immune Response to Bacterial Therapies.

ACS synthetic biology·2026

Same journal

Rational Design of Linalool Dehydratase-Isomerase Enables Efficient Conversion of Phytol to Neophytadiene.

ACS synthetic biology·2026

Same journal

<i>De Novo</i> Biosynthesis of Polyphyllin V in <i>Nicotiana benthamiana</i> through Pathway Reconstruction and UDP-Sugar Engineering.

ACS synthetic biology·2026

Same journal

Rapid and Continuous Directed Evolution in <i>Vibrio natriegens</i> Utilizing an <i>In Vivo</i> Hypermutation System.

ACS synthetic biology·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Sep 4, 2025

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

BMSS2: A Unified Database-Driven Modeling Tool for Systematic Biomodel Selection.

Russell Jie Kai Ngo^1,2, Jing Wui Yeoh^1,2, Gerald Horng Wei Fan¹

¹Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore 117583.

ACS Synthetic Biology

|July 22, 2022

Summary

This summary is machine-generated.

This study introduces BMSS2, a unified tool for synthetic biology modeling. It automates model selection and analysis, improving the Design-Build-Test-Learn cycle for better experimental design.

Keywords:

genetic circuits identifiability analysis kinetic model model selection python package synthetic and systems biology

More Related Videos

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

An Analytical Tool-box for Comprehensive Biochemical, Structural and Transcriptome Evaluation of Oral Biofilms Mediated by Mutans Streptococci

An Analytical Tool-box for Comprehensive Biochemical, Structural and Transcriptome Evaluation of Oral Biofilms Mediated by Mutans Streptococci

Published on: January 25, 2011

Related Experiment Videos

Last Updated: Sep 4, 2025

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

An Analytical Tool-box for Comprehensive Biochemical, Structural and Transcriptome Evaluation of Oral Biofilms Mediated by Mutans Streptococci

An Analytical Tool-box for Comprehensive Biochemical, Structural and Transcriptome Evaluation of Oral Biofilms Mediated by Mutans Streptococci

Published on: January 25, 2011

Area of Science:

Synthetic biology
Systems biology
Computational biology

Background:

Kinetic models are crucial for understanding synthetic biology system dynamics.
A systematic pipeline for model selection and experimental design guidance is currently lacking.
Rational Design-Build-Test-Learn approaches require efficient model development and analysis tools.

Purpose of the Study:

To develop a unified and automated pipeline for synthetic biology model selection and analysis.
To streamline the process of identifying appropriate kinetic models and guiding experimental designs.
To enhance the reusability and traceability of models in the Design-Build-Test-Learn cycle.

Main Methods:

Developed BMSS2, a unified tool integrating information criterion ranking with analysis algorithms.
Incorporated Bayesian parameter inference, a priori and a posteriori identifiability analysis, and global sensitivity analysis.
Implemented a database-driven design for interactive model storage, retrieval, and reusability.

Main Results:

BMSS2 automates model selection and streamlines upstream and parallel analysis.
The tool facilitates interactive model manipulation, storage, and retrieval.
Enhanced model utilization for guiding experimental design within a systematic pipeline.

Conclusions:

BMSS2 provides a systematic and modular solution for synthetic biology modeling.
The tool automates complex analyses, improving efficiency and model selection.
BMSS2 facilitates better utilization of models to guide experimental design in synthetic biology.