Students, faculty, and TAs of the 2013 Workshop (2013 Group Photo Key)
Welcome to the Workshop on Molecular Evolution
Directors: David Hillis (University of Texas, Austin) and Mitch Sogin (Marine Biological Laboratory, Woods Hole)
Course Dates: July 21 to July 31, 2013
2014 Course Dates: July 27 to August 6, 2014.
MBL Course Page (to apply)
Course Facebook Page
Now in its 26th year, the MBL's Workshop on Molecular Evolution at Woods Hole presents a series of lectures, discussions, and bioinformatic exercises that span contemporary topics in molecular evolution. The workshop encourages the exchange of ideas among leading theoreticians, software developers, and workshop participants. The workshop serves graduate students, postdoctoral students, and established faculty from around the world. The 2013 Workshop will use computer packages including AWTY, BEAST, BEST, FASTA, FigTree, GARLI, MIGRATE, LAMARC, MAFFT, MP-EST, MrBayes, PAML, PAUP*, STEM, STEM-hy, and SeaView to address the following topics:
- Phylogenetic analysis: theoretical, mathematical, and statistical bases; sampling properties of sequence data; Maximum likelihood theory and practice; Bayesian analysis; hypothesis testing
- Population genetics analysis using coalescence theory; maximum likelihood and Bayesian estimation of population genetic parameters
- Databases and sequence matching: database searching: protein sequence versus protein structure; homology; mathematical, statistical, and theoretical aspects of sequence database searches; multiple alignment
- Molecular evolution integrated at organism and higher levels: population biology; biogeography; ecology; systematics and conservation
- Molecular evolution and development: gene duplication and divergence; gene family organization; coordinated expression in evolution
- Comparative genomics: genome content; genome structure; genome evolution
- Molecular evolution integrated at lower levels: biochemistry; cell biology; physiology; relationship of genotype to phenotype
Students will work with computer packages on their own laptops and have the opportunity to use the high performance computer clusters at the MBL.