Analytical Informatics
Chemistry 696D

Purdue University Department of Chemistry

Spring 2003
M,W 4:30-5:45 (WTHR 420)

Instructor: Randy Julian
rkjulian@miner.chem.purdue.edu

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Summary

Analytical Informatics: using information technology to enhance data analysis in analytical chemistry. Analytical Informatics has had great impact on analytical chemistry and biochemistry. It is very broadly applicable, and is used in such diverse areas as:

· Industrial analytical chemistry
· Pharmaceutical research
· Applied computational chemistry
· Genomics
· Proteomics
· Instrument development

This course will introduce many aspects of 'Informatics' in chemistry. It will take examples from analytical chemistry and life-sciences research to show how to use computer technology coupled with statistics and ideas from pattern recognition to solve real world problems.

Course Topics

Machine learning

· Linear methods: linear discriminants, least squares methods
· Logistic regression for classification
· Multi-layer neural networks
· Support Vector Machines
· Tree-based methods
· Combining classifiers
· Validations and classifier testing
· Feature selection for spectroscopy

Chemical representations and databases

· SMILES structure representation
· SQL databases
· XML

Building high performance analytical systems

· Perl programming for informatics
· Combining tools: R, Perl, mySQL
· Clusters and high performance computing
· Data interchange and raw data management