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SALSA and Cheminformatics

This project by the SALSA Group focuses on analyzing disease-gene data using advanced mapping techniques, specifically MDS and GTM for dimensionality reduction. By handling over 930K disease and gene data points, our methods leverage 166-bit fingerprints to maintain similarity within the original data space. We present interactive visualizations that incorporate IUPAC names and chemical structures while enabling integration with external databases. The work aims to clarify the relationships between diseases, genes, and chemical data, paving the way for improved insights in biomedical research.

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SALSA and Cheminformatics

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  1. SALSA and Cheminformatics SALSA Group February 12 2010

  2. Disease-Gene Data Analysis • Workflow Disease PubChem 3D Map With Labels -. 34Ktotal -. 32K unique CIDs Union MDS/GTM -. 77K unique CIDs -. 930K disease and gene data Gene -. 2M total -. 147K unique CIDs (Num of data)

  3. MDS/GTM with PubChem • Project data in the lower-dimensional space by reducing the original dimension • Preserve similarity in the original space as much as possible • GTM needs only vector-based data • MDS can process more general form of input (pairwise similarity matrix) • We have used only 166-bit fingerprints so far for measuring similarity (Euclidean distance)

  4. PlotViz • Interactive exploring data in the 3D space • Updated to provide richer meta data • IUPAC names, chemical names, … • Chemical structure images, … • Need to add more • Can be mixed with external data sources (web site or database) • Jittering to avoid overlapping

  5. PlotViz Screenshot (I) - MDS

  6. PlotViz Screenshot (II) - GTM

  7. PlotViz Screenshot (III) - MDS

  8. PlotViz Screenshot (IV) - GTM

  9. Discussions • Relationship of disease <-> gene <-> PubChem • Fingerprint only vs. other properties • Data size : optimal size or limits • Suggested functions for PlotViz improvement

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