Journal of Chemical Information and Modeling· 2015Q1
DataWarrior: An Open-Source Program For Chemistry Aware Data Visualization And Analysis
- 1,832citations
- Q1SCImago
- 2015year
Short summary
DataWarrior is a new open-source program that provides chemistry-aware data visualization and analysis, enabling chemists to interpret large datasets by identifying correlations between molecular structures, properties, and structural changes.
AI-generated from the title and abstract; the full text is not read.
Key points
- DataWarrior is an open-source program designed for chemistry-aware data visualization and analysis.
- It helps interpret large datasets by correlating molecular families, structural motifs, and property changes.
- Features an unsupervised, 2D scaling algorithm using vector-based or non-vector-based descriptors.
- Enables interactive exploration of chemical space, activity landscapes, and activity cliffs.
AI-generated from the title and abstract; the full text is not read.
Abstract
Drug discovery projects in the pharmaceutical industry accumulate thousands of chemical structures and ten-thousands of data points from a dozen or more biological and pharmacological assays. A sufficient interpretation of the data requires understanding, which molecular families are present, which structural motifs correlate with measured properties, and which tiny structural changes cause large property changes. Data visualization and analysis software with sufficient chemical intelligence to support chemists in this task is rare. In an attempt to contribute to filling the gap, we released our in-house developed chemistry aware data analysis program DataWarrior for free public use. This paper gives an overview of DataWarrior's functionality and architecture. Exemplarily, a new unsupervised, 2-dimensional scaling algorithm is presented, which employs vector-based or nonvector-based descriptors to visualize the chemical or pharmacophore space of even large data sets. DataWarrior uses this method to interactively explore chemical space, activity landscapes, and activity cliffs.
The authors' abstract, as published at the source. Journal of Chemical Information and Modeling, 2015 · DOI ↗
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Field: Computational Theory and Mathematics
Computational Theory and MathematicsComputer Science