The course will cover information aspects of molecular measurement technologies with emphasis on statistical and algorithmic approaches and on microarray technology, including a variety of applications.
Microarray technology enables parallel measurement of tens of thousands of molecular events. The technology has been suggested in the early 90s and has since developed to a standard in life-science research. Recently, the US FDA has approved a diagnostic assay that utilizes microarray based expression profiling to make a call. During the years microarrays have evolved to enable the measurement of mRNA expression levels, variations in DNA content (SNPs), variations in DNA copy number (of particular importance in cancer research and treatment), methylation status of promoters, microRNA expression levels, transcription factor binding and other molecular level events. All microarray based techniques are high-throughput, generating large datasets. The efficient use of microarrays depends on adequate statistical and algorithmic approaches to the design of the assay and to the data analysis stage.
In class we will review molecular measurement technologies and address computational tasks involved in their design and analysis, including practical implementation and work with real experimental data. We will discuss data analysis methods such as clustering, differential expression and classification, enrichment and motif analysis.
- מורה: זהר יכיני
- מורה: ישראל שטיינפלד