文档介绍：Tue Sep 18 Intro 1: Computing, statistics, Perl, Mathematica Tue Sep 25 Intro 2: Biology, comparative genomics, models & evidence, applications Tue Oct 02 DNA 1: Polymorphisms, populations, statistics, pharmacogenomics , databases Tue Oct 09 DNA 2: Dynamic programming, Blast, multi-alignment, H idden M arkov M odels Tue Oct 16 RNA 1: Microarrays, library sequencing & quantitation concepts Tue Oct 23 RNA 2: Clustering by gene or condition, DNA/RNA motifs. Tue Oct 30 Protein 1: 3D structural genomics, homology, dynamics, function & drug design Tue Nov 06 Protein 2: Mass spectrometry, modifications, quantitation of interactions Tue Nov 13 Network 1: Metabolic ic & flux balance optimization methods Tue Nov 20 Network 2: puting, self-assembly, ic algorithms, s Tue Nov 27 Network 3: Cellular, developmental, social, ecological & commercial models Tue Dec 04 Project presentations Tue Dec 11 Project Presentations Tue Jan 08 Project Presentations Tue Jan 15 Project Presentations Bio 101: Genomics & Computational Biology DNA1: Last week's take-home lessons Types of mutants Mutation, drift, selection Binomial & exponential dx/ dt = kx Association studies ? 2 statistic Linked & causative alleles Alleles, Haplotypes, puting the first genome, the second ... New technologies Random and systematic errors DNA2: Today's story and goals z Motivation and connection to DNA1 paring types of alignments & algorithms z Dynamic programming z Multi-sequence alignment z Space-time-accuracy tradeoffs z Finding genes -- motif profiles z Hidden Markov Model for CpG Islands DNA 2 figure Intro2: Common & simple DNA1: the last 5000 generations Applications of Dynamic Programming z To sequence analysis y Shotgun sequence assembly y Multiple alignments y Dispersed & tandem repeats y Bird song alignments y Gene Expression time-warping z Through HMMs y RNA gene search & structure prediction y Distant protein homologies y Speech recognition Alignme