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

Statgraphics01:10

Statgraphics

497
Statgraphics is a comprehensive statistical software suite designed for both basic and advanced data analysis. Originating in 1980 at Princeton University under Dr. Neil W. Polhemus, it was one of the pioneering tools for statistical computing on personal computers, with its public release in 1982 marking an early milestone in data science software. Over the years, it has evolved into a robust platform for data science, offering tools for regression analysis, ANOVA, multivariate statistics,...
497
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

1.9K
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...
1.9K
Statistical Analysis System (SAS)01:14

Statistical Analysis System (SAS)

1.3K
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...
1.3K
UV–Vis Spectroscopy: Woodward–Fieser Rules01:29

UV–Vis Spectroscopy: Woodward–Fieser Rules

30.0K
UV–Visible absorption spectra of conjugated dienes arise from the lowest energy π → π* transitions. The light-absorbing part of the molecule is called the chromophore, and the substituents directly attached to the chromophore are called auxochromes. A strong correlation exists between the absorption maxima, λmax, and the structure of a conjugated π system. The Woodward–Fieser rules predict the value of λmax for a...
30.0K
Development of Analytical Methods01:21

Development of Analytical Methods

3.2K
An analytical methodology can be divided into four sequential steps: technique, method, procedure, and protocol. A technique is a scientific principle that rationalizes a specific phenomenon through chemical measurements. Adapting a technique for analyzing a sample of interest is termed a method. The procedure outlines the directions for performing the analysis via an analytical method. The protocol is the detailed guidelines on the procedure, which should be strictly followed to obtain the...
3.2K
pV-Diagrams01:18

pV-Diagrams

6.7K
The pV diagram, which is a graph of pressure versus volume of the gas under study, is helpful in describing certain aspects of the substance. When the substance behaves like an ideal gas, the ideal gas equation describes the relationship between its pressure and volume. On a pV diagram, it is common to plot an isotherm, which is a curve showing p as a function of V with the number of molecules and the temperature fixed. Then, for an ideal gas, the product of the pressure of the gas and its...
6.7K

You might also read

Related Articles

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

Sort by
Same author

A Dataset of Plausible Proton Transfer Steps for Arrow-Pushing Mechanisms.

Scientific data·2026
Same author

A workflow for deriving chemical entities from crystallographic data and its application to the Crystallography Open Database.

Journal of cheminformatics·2023
Same author

Fast Substructure Search in Combinatorial Library Spaces.

Journal of chemical information and modeling·2023
Same author

[Hemoptysis under immunosuppression].

Die Anaesthesiologie·2022
Same author

mGlu3 Metabotropic Glutamate Receptors as a Target for the Treatment of Absence Epilepsy: Preclinical and Human Genetics Data.

Current neuropharmacology·2022
Same author

Limits of Prediction for Machine Learning in Drug Discovery.

Frontiers in pharmacology·2022
Same journal

Advancing Biochemical Molecule Registration, Representation and Search for New Drug Modalities.

Journal of chemical information and modeling·2026
Same journal

A Unified Molecular Graph and Protein Language Model Framework for Predicting Human Drug-Hormone Receptor Interactions with Structure-Aware Validation.

Journal of chemical information and modeling·2026
Same journal

Intricate Role of Cholesterol in Membrane Fusion.

Journal of chemical information and modeling·2026
Same journal

tmGNN-XAI: An Explainable Graph Neural Network Tool for Predicting Electronic Properties of Transition Metal Complexes from SMILES.

Journal of chemical information and modeling·2026
Same journal

QSAR in the Browser: An Interactive Cheminformatics Web Application.

Journal of chemical information and modeling·2026
Same journal

FoldDoF: Utilizing the Primary Degrees of Freedom of Protein Backbone for Geometric Modeling and Generation.

Journal of chemical information and modeling·2026
See all related articles

Related Experiment Video

Updated: Apr 19, 2026

Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods
05:34

Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods

Published on: June 6, 2025

1.9K

DataWarrior: an open-source program for chemistry aware data visualization and analysis.

Thomas Sander1, Joel Freyss, Modest von Korff

  • 1Department of Information Management Drug Discovery, Actelion Ltd. , Gewerbestrasse 16, CH-4123 Allschwil, Switzerland.

Journal of Chemical Information and Modeling
|January 7, 2015
PubMed
Summary
This summary is machine-generated.

Chemists can now freely explore vast drug discovery datasets with DataWarrior, a new software tool. It aids in understanding chemical structures, properties, and activity cliffs for better drug development.

More Related Videos

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
10:52

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Published on: April 12, 2019

13.5K
Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
07:01

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools

Published on: August 19, 2025

1.3K

Related Experiment Videos

Last Updated: Apr 19, 2026

Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods
05:34

Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods

Published on: June 6, 2025

1.9K
Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
10:52

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Published on: April 12, 2019

13.5K
Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
07:01

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools

Published on: August 19, 2025

1.3K

Area of Science:

  • Computational chemistry and cheminformatics
  • Drug discovery and development
  • Data visualization and analysis

Background:

  • Pharmaceutical drug discovery generates massive datasets of chemical structures and assay results.
  • Interpreting this data requires understanding structure-property relationships and identifying critical structural changes.
  • Specialized software for chemically intelligent data analysis is currently limited.

Purpose of the Study:

  • To introduce DataWarrior, a freely available, in-house developed software for chemistry-aware data analysis.
  • To provide chemists with tools for interpreting complex drug discovery data.
  • To present a novel unsupervised 2D scaling algorithm for visualizing chemical and pharmacophore spaces.

Main Methods:

  • Overview of DataWarrior's functionality and architecture.
  • Implementation of a new unsupervised 2D scaling algorithm using vector-based or non-vector-based descriptors.
  • Application of the algorithm for visualizing large datasets of chemical structures and properties.

Main Results:

  • DataWarrior enables interactive exploration of chemical space, activity landscapes, and activity cliffs.
  • The presented 2D scaling algorithm effectively visualizes the chemical or pharmacophore space of large datasets.
  • The software facilitates the identification of structure-activity relationships and critical structural modifications.

Conclusions:

  • DataWarrior offers a valuable, free resource for chemists to analyze and visualize complex drug discovery data.
  • The novel visualization algorithm enhances the understanding of chemical diversity and structure-activity relationships.
  • The tool supports informed decision-making in drug discovery projects by revealing activity cliffs and key structural features.