- Introduction to DNA Micro-arrays technology: DNA Microarray types, microarray technologies (printed/spotted vs on-site synthesis), cDNA vs oligo arrays, one dye vs two dye experiments, biomedical questions that can we answered with microarrays.
- Experimentation I: Design for high throughput DNA micro-arrays: Gene-Clustering dogma, replicate experiments, reproducibility, sources of noise and biological variation.
- Experimentation II: from sample preparation to gene expression profiles: Sample preparation, RNA isolation and labeling, Chip Hybridization, Scanning, Gridding, Normalization / Data row, Gene Annotation, Validation (Quantitative PCR), TMEV-4, Go-Miner, Future directions and technology expansion.
- From Microarray Measurements to Data Analysis: Measures of expression, microarray image analysis, normalization, scaling and filtering, fold calculation and significance.
- Dissimilarity and Similarity Measures: Linear correlation, entropy and mutual information, dynamics.
- Genomic Data-Mining Techniques: Supervised vs Unsupervised, Data reduction and filtering, Clustering, Classification, PCA, Regression Analysis, Self Optimizing Maps, Support Vector Machines, Determining the Significance of Findings.
- Integrating Microarray Data with other sources of Information: Genotype, Phenotype, Genomic Sequences, Annotation, Bio-ontologies [Gene Ontology, EC Nomenclature], systems biology.
- Microarray Standards, Databases (MIAME-MGED) and related resources: Necessity for microarray standards, MGED and gene-ontology, description of MIAME ((Minimum Information About a Microarray Experiment), related inter-WEB sources, Bioconductor.
- Application of bioinformatic tools in mouse genome-wide DNA microarrays: Analysis of the liver transcriptome, in old mice and a mouse model of a DNA-damage related progeroid syndrome. Human genome-wide microarray applications in biomedicine.
- Gene expression profiling and signatures: Molecular carcinogenesis and chemo-resistance development in cancer cells, functional analysis of human diseases biomarkers in human cells.
- Micro-arrays for proteomics – Proteins arrays / Cell arrays: Types of protein-arrays, Sample preparation and hybridization, technological drawbacks and challenges, future applications.