Introduction

Course roadmap

The novel research-oriented course of bioinformatics called From Sequence to Expression and Structure is organized into three main parts listed below.

Course structure

• Statistical methods for gene expression and gene interaction using DNA-array data as well as other genomic data
• Statistical machine learning techniques for bioinformatics
• Application of computational geometry and robotics techniques to the study of biomolecules and receptor-ligand interactions

Statistical methods for gene expression

Multiple gene expression techniques allow simultaneous measurement of expression levels of up to 50,000 genes. These novel methods already are being used to classify human cancers as well as to measure expression changes in experimental conditions. This part of the course introduces the student to the techniques and experiments for obtaining gene expression data, as well as the probabilistic and statistical methods for analysis of such data.

The data generated by large scale parallel hybridization techniques, such as DNA microarrays, constitute a new generation of data requiring novel methods of statistical analysis.

You can also refer to the comprehensive presentation of the DNA-Microarray technology