RNA1: Last week's take home lessons
- Integration with previous topics (HMM for RNA structure)
- Goals of molecular quantitation (maximal fold-changes, clustering & classification of genes & conditions/cell types, causality)
- Genomics-grade measures of RNA and protein and how we choose (SAGE, oligo-arrays, gene-arrays)
- Sources of random and systematic errors (reproducibilty of RNA source(s), biases in labeling, non-polyA RNAs, effects of array geometry, cross-talk).
- Interpretation issues (splicing, 5' & 3' ends, editing, gene families, small RNAs, antisense, apparent absence of RNA).
- Time series data: causality, mRNA decay, time-warping