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

Molecular Models

Molecular Models

Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.

BIBO stability of continuous and discrete -time systems

BIBO stability of continuous and discrete -time systems

System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....

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...

Fluid Mosaic Model

Fluid Mosaic Model

Scientists identified the plasma membrane in the 1890s and its principal chemical components (lipids and proteins) by 1915. The model for plasma membrane structure, proposed in 1935 by Hugh Davson and James Danielli, was the first model to be widely accepted in the scientific community. The model was based on the plasma membrane's "railroad track" appearance in early electron micrographs. Davson and Danielli theorized that the plasma membrane's structure resembled a sandwich...

The Fluid Mosaic Model

The Fluid Mosaic Model

The fluid mosaic model was first proposed as a visual representation of research observations. The model comprises the composition and dynamics of membranes and serves as a foundation for future membrane-related studies. The model depicts the structure of the plasma membrane with a variety of components, which include phospholipids, proteins, and carbohydrates. These integral molecules are loosely bound, defining the cell’s border and providing fluidity for optimal function.

Statistical Analysis System (SAS)

Statistical Analysis System (SAS)

SAS, short for Statistical Analysis System, is a powerful data analysis, management, and visualization tool. Developed by the SAS Institute in the early 1970s, SAS has evolved into a comprehensive software suite used across various industries for statistical analysis, business intelligence, and predictive modeling.
Applications: SAS finds applications in numerous fields, including healthcare for clinical trial analysis, finance for risk assessment, marketing for customer data analysis, and...

You might also read

Related Articles

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

Sort by

Same author

Comparative proteome analyses of human natural killer cells from patients after allogeneic stem cell transplantation and healthy individuals challenged with <i>Aspergillus fumigatus</i>.

microLife·2026

Same author

DNA methylation signatures associated with bipolar disorder in peripheral blood improve prediction models.

EBioMedicine·2026

Same author

FungiNetDB: a uniform (pre-)processing platform for fungal expression data.

microLife·2026

Same author

Methylome-Wide Association Study of Obsessive-Compulsive Disorder.

Biological psychiatry·2026

Same author

Factors Influencing Undesirable Sensory Properties in Protein Hydrolysates and Remediation Strategies for Food Applications.

Journal of food science·2026

Same author

Caspofungin enhances antifungal immunity in human blood through transcriptional reprogramming.

microLife·2026

Same journal

OpenIMC: an open-source platform for analyzing single-cell and spatial proteomics by imaging mass cytometry.

BMC bioinformatics·2026

Same journal

NAP: an open source pipeline for cross-domain microbiome profiling using Nanopore sequencing-derived amplicon data.

BMC bioinformatics·2026

Same journal

SurvGME: an R package for survival analysis with graphical and measurement error models.

BMC bioinformatics·2026

Same journal

SimMapNet: a Bayesian framework for gene regulatory network inference using gene ontology similarities as external hint.

BMC bioinformatics·2026

Same journal

Dual channel drug-drug interactions extraction based on cross attention.

BMC bioinformatics·2026

Same journal

FeSseqdb: a curated sequence-level database and interpretable machine learning framework for identifying iron-sulfur proteins.

BMC bioinformatics·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Feb 27, 2026

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Published on: July 16, 2017

SBMLmod: a Python-based web application and web service for efficient data integration and model simulation.

Sascha Schäuble¹, Anne-Kristin Stavrum², Mathias Bockwoldt³

¹Jena University Language & Information Engineering (JULIE) Lab, Friedrich-Schiller-University Jena, Jena, Germany.

BMC Bioinformatics

|June 26, 2017

Summary

This summary is machine-generated.

SBMLmod automates the integration of high-throughput data into Systems Biology Markup Language (SBML) models. This user-friendly platform simplifies model modification and simulation, making complex analyses accessible to more researchers.

Keywords:

Data integration Model simulation Web application Web service

More Related Videos

Modeling an Enzyme Active Site using Molecular Visualization Freeware

Modeling an Enzyme Active Site using Molecular Visualization Freeware

Published on: December 25, 2021

A Web Tool for Generating High Quality Machine-readable Biological Pathways

A Web Tool for Generating High Quality Machine-readable Biological Pathways

Published on: February 8, 2017

Related Experiment Videos

Last Updated: Feb 27, 2026

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Published on: July 16, 2017

Modeling an Enzyme Active Site using Molecular Visualization Freeware

Modeling an Enzyme Active Site using Molecular Visualization Freeware

Published on: December 25, 2021

A Web Tool for Generating High Quality Machine-readable Biological Pathways

A Web Tool for Generating High Quality Machine-readable Biological Pathways

Published on: February 8, 2017

Area of Science:

Systems Biology
Bioinformatics
Computational Biology

Background:

Systems Biology Markup Language (SBML) is the standard for representing biological models.
Integrating diverse datasets into SBML models enhances predictive power but often requires specialized skills.
Automating data integration and analysis is crucial for advancing systems biology.

Purpose of the Study:

To develop an automated tool for integrating high-throughput data into SBML models.
To provide a user-friendly platform for model modification and simulation.
To enhance the accessibility of complex systems biology analyses.

Main Methods:

Developed SBMLmod, a Python-based web application and service.
Automated the integration of high-throughput data into SBML models.
Integrated steady-state analysis via the COPASIWS web service.

Main Results:

SBMLmod successfully integrated gene expression data from healthy and cancer tissues into a mammalian tryptophan metabolism model.
Demonstrated the utility of SBMLmod for automated model enrichment.
Provided a web application, web service, and downloadable package for broader access.

Conclusions:

SBMLmod offers a user-friendly platform for automated model modification and simulation.
The tool facilitates the integration of experimental data into biological models.
SBMLmod aims to democratize advanced systems biology analyses for a wider research community.