Effect of Alcohol on Brain Development

1. Effect of Alcohol on Brain Development Normal Fetal Alcohol Syndrome

3. Defining cognitive disorders • by gene expression profiling: • Examples of cognitive disabilities: • Mental illness • Mental retardation • Alzheimer’s and other dementia • Traumatic brain injury • Stroke • Fetal Alcohol Syndrome • Gene profiling provides a • molecular fingerprint for susceptibility • and cause of specific cognitive disorders.

4. Microarray Expression Profiling for Understanding Cognitive Disabilitites • Defining the human genome provides the database for • profiling gene expression patterns in cognitive disabilities. • Specific cognitive disabilities will not be a single disorder • but rather multiple disorders that manifest themselves • with a common medical diagnosis. • Gene array technology allows defining the spectrum of • gene expression profiles for “normal” individuals and those • with “specific” cognitive disorders. • Gene profiling allows “molecular fingerprinting” of an • individuals cognitive disorder.

5. The Role of Informatics in Addressing Cognitive Deficits • Neuroinformatics: • Integrating data from behavioral, physiological, anatomical, cellular and molecular levels • Building and testing neural models in silico • Molecular bioinformatics • Analysis of genes, gene expression arrays, etc. • Modelling metabolic and signalling pathways • General bioinformatics • Organizing, managing and extracting relevant information from the biological literature.

6. Integrating Diverse Sources of Data • Relevant information is available from many sources, none designed to be interoperable • We have designed and implemented systems that use automated ontologies and advanced database technology to integrate diverse data from: • public and private databases • multiple institutions • multiple biological data types (e.g. QTLs & gene expression arrays)

7. Finding Patterns and Relationships • Machine learning: using data and computation to extend human intuition and statistical power • HSC bioinformatics invents new techniques, and has a powerful kit of existing tools: • Neural networks • Support vector machines • Information theory (e.g. mutual information) • Bayesian inference

8. Predictive Modelling in Complex Biological Systems • Biological systems are inherently non-linear; combinations and relationships are key • High-throughput revolution (e.g. gene expression arrays) creates enough data for pattern discovery • Sample applications: • Found a 4 gene combination that distinguishes among leukemias as well as 50 gene linear model • Combined 3 weak alcohol state markers into a near-perfect predictor from 1800 training examples.