Interactive Datamining of Large-Scale Screening Datasets

Interactive Datamining of Large-Scale
Screening Datasets
Frank Oellien, Wolf D. Ihlenfeldt
Computer-Chemie-Centrum
University Erlangen-Nuremberg

Klaus Engel, Thomas Ertl
Visualization and Interactive Systems Group
University Stuttgart

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© Oellien, Ihlenfeldt, Engel, Ertl MMWS 2002

Overview

Multi-variate and multi-dimensional datasets
• Motivation
• Information Visualization Techniques
• Examples (ChemCodes Inc., NCI)
• Demo

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Chemical
data

18000000
16000000 Merck Katalog
14000000 Synopsys PG
12000000 ACX
NCI DTP
10000000
ChemInform
8000000
Spresi
6000000 Beilstein
4000000 CAS
2000000 Current datasets
0

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Multi-Variate and Multi-Dimensional
Numeric Datasets Today

Change in chemical synthesis technology

• new technologies (HTS, combinatorial synthesis)
→ experiments generate terabytes of data per year
• development of data mining and visualization tools
could not keep pace
• most critical bottleneck in R&D today !
→ tools for interactive mining and information
visualization are needed

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Tools for Interactive Visualization of
Multi-Variate and Multi-Dimensional Data
Standard applications
• barchart, 2D and pseudo 3D
scatter plots, molecular spreadsheets
• limited to small subsets
• platform-dependent
Our goal: applications that are
• simple to use
• allow straightforward interpretation of results
• generalized access to tabular numeric data
• platform-independent

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3D Tools for Interactive
Information Visualization

Information Visualization Applications that uses
3D capabilities of modern clients

• Glyph-based InfVis approaches

• Volume-based InfVis approaches

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Glyph-based InfVis Tools

• 3 orthogonal axes
• color
• shape
• size
• transparency
• surface effects
• animation
• up to ~100 Glyphs
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Java/Java3D InfVis Applet

Java3D Tool Panel
Canvas (filters, selection
tools, details)

Control
Panel

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3D Render Panel

3D Glyphs 3D Barchart

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3D Tool Panel

Dynamic Filter Tools

Selection Tools
Detail Tools

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3D Control Panel

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Advantages of Volume-based InfVis Tools
Databases with millions of data points
– Glyph-based InfVis approaches
• produce millions of geometric
primitives
• interactive visualization not possible

– Volume-based InfVis approaches
• can handle large number of
data points
• interactive visualization using
low-cost graphics hardware is possible

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ChemCodes Reaction Database

• 100 most important FGs ~75% chemistry
• 100 standard reactions
• Limits of standard reactions
• Functional Group Compatibility
• Generating Rules

Goal: Analysis of the reaction space

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ChemCodes - Reaction Optimization I
• Goal:
Reaction Optimization: > 95% Yield

• 7 Dimensions:
reagent, solvent,
time, temperature,
stoichiometry,
reagent order,
FG-compatibility

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ChemCodes - Reaction Optimization II

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ChemCodes - Reaction Planning
Functional
Group
Compatibility
Check
H H
N

H

O

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Example 2: NCI Anti-tumor
/ Anti-viral Database

• Initiated in April 1990 (modified 1994)
• ~ 250.000 compounds
• ~ 30.000 with anti-tumor screening data

Enhanced NCI Database Browser
• > 30 different molecular properties
• up to 23 3D conformers per compound

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Lead Compound Discovery II

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Acknowledgment
• Prof. Johann Gasteiger
Computer-Chemie-Centrum
University of Erlangen-Nuremberg

• Prof. Thomas Ertl, Dipl. Inf. Klaus Engel
Visualization and interactive Systems
University of Stuttgart
• Dr. Patrick Kiser, Dr. Gary Eichenbaum
ChemCodes Inc.
• Marc Nicklaus
Laboratory of Medicinal Chemistry
NCI, NIH

• Deutsche Forschungsgemeinschaft
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Interactive Datamining of Large-Scale Screening Datasets

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