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

Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
Fundamental Mathematical Principles in Pharmacokinetics: Calculus and Graphs01:21

Fundamental Mathematical Principles in Pharmacokinetics: Calculus and Graphs

The fundamental mathematical principles, such as calculus and graphs, play crucial roles in analyzing drug movement and determining pharmacokinetic parameters. Differential calculus examines rates of change and helps to determine the dissolution rate of drugs in biofluids, as well as how drug concentrations change over time. For instance, it can help calculate the rate of elimination of a drug from the body based on its concentration-time profile.
On the other hand, integral calculus focuses on...
Mathematical Modeling: Problem Solving01:29

Mathematical Modeling: Problem Solving

Mathematical modeling transforms real-world scenarios into mathematical expressions, allowing for structured problem-solving and analysis. This process involves defining the situation, assigning variables to measurable quantities, selecting an appropriate model, and solving the resulting equation. Such models are invaluable in finance, providing precise methods to evaluate investments, loans, and repayment structures.A widely used example is the calculation of fixed monthly payments on a loan,...
Modeling and Similitude01:12

Modeling and Similitude

Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
Statistical Analysis System (SAS)01:14

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

Estimating SARS-CoV-2 exposure in asymptomatic hospitalized children with cancer in Western Kenya: A retrospective analysis of serological data.

PloS one·2026
Same author

Modeling development of tertiary lymphoid structures in pulmonary tuberculosis by 3D profiling and trajectory analysis.

bioRxiv : the preprint server for biology·2026
Same author

A multiplexed, systems-based approach for prediction of antibody neutralization breadth for soluble human receptors.

Journal of immunology (Baltimore, Md. : 1950)·2026
Same author

Breast milk antibody Fc signatures track with HIV transmission during breastfeeding in ART-naïve mothers.

iScience·2026
Same author

A scalable, low-cost, sample hashing workflow for multiomic single-cell analysis using the Seq-Well S<sup>3</sup> platform.

Nature protocols·2026
Same author

Protein networks are influenced by maternal BMI and differentiate preterm birth types.

Communications medicine·2026

Related Experiment Video

Updated: Jul 8, 2026

CorrelationCalculator and Filigree: Tools for Data-Driven Network Analysis of Metabolomics Data
07:11

CorrelationCalculator and Filigree: Tools for Data-Driven Network Analysis of Metabolomics Data

Published on: November 10, 2023

Flexible informatics for linking experimental data to mathematical models via DataRail.

Julio Saez-Rodriguez1, Arthur Goldsipe, Jeremy Muhlich

  • 1Center for Cell Decision Processes, Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA.

Bioinformatics (Oxford, England)
|January 26, 2008
PubMed
Summary

DataRail is an open-source MATLAB toolbox that manages and transforms experimental data for biological modeling. It ensures data integrity and preserves transformation histories, facilitating model calibration and increasing model value.

More Related Videos

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
09:43

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Published on: November 22, 2019

Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization
08:03

Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization

Published on: November 12, 2014

Related Experiment Videos

Last Updated: Jul 8, 2026

CorrelationCalculator and Filigree: Tools for Data-Driven Network Analysis of Metabolomics Data
07:11

CorrelationCalculator and Filigree: Tools for Data-Driven Network Analysis of Metabolomics Data

Published on: November 10, 2023

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
09:43

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Published on: November 22, 2019

Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization
08:03

Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization

Published on: November 12, 2014

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Systems Biology

Background:

  • Linking experimental data to biological mathematical models is challenging due to inadequate data management and transformation software.
  • Preserving links to training data and transformation histories is crucial for model calibration and enhancing model utility.

Purpose of the Study:

  • To introduce DataRail, an open-source MATLAB-based toolbox designed to streamline the management and transformation of experimental data for biological modeling.
  • To enhance data integrity and facilitate the creation of robust biological models by preserving data provenance.

Main Methods:

  • DataRail stores experimental data in flexible multi-dimensional arrays.
  • It imposes a metadata standard (MIDAS format) and uses universal identifiers for data organization.
  • A history of all data transformations is stored with the arrays to ensure reproducibility.

Main Results:

  • DataRail successfully processed approximately 22,000 measurements of protein activities from human liver cells.
  • The toolbox maintains data integrity through a containment hierarchy and a proposed metadata standard.
  • It enables the construction of models using internal or external tools with preserved data transformation history.

Conclusions:

  • DataRail provides a robust solution for managing and transforming experimental data in biological research.
  • The toolbox facilitates model calibration and increases the value of biological models by ensuring data integrity and provenance.
  • DataRail is available as open-source software under the GNU General Public License.