& COMPARATIVE GENOMICS
November 6 - 12, 2013
Application Deadline: July 15, 2013
Pearson, University of Virginia, Charlottesville
Stubbs, University of Illinois, Urbana
note special application instructions:
Only ONE letter of reference is required along with your
application and Statement/Essay
This course presents a comprehensive overview of the theory and practice of computational methods for the identification and characterization of functional elements from DNA sequence data. The course focuses on approaches for extracting the maximum amount of information from protein and DNA sequence similarity through sequence database searches, statistical analysis, and multiple sequence alignment. Additional topics include:
Alignment and analysis of “next-gen” sequencing data, with applications from metagenomic, RNA-Seq, and CHiP-Seq experiments
The Galaxy environment for high-throughput analysis
Regulatory element and motif identification from conserved signals in aligned and unaligned sequences
Integration of genetic and sequence information in biological databases
The ENSEMBL genome browser and BioMart
The course combines lectures with hands-on exercises; students are encouraged to pose challenging sequence analysis problems using their own data. The course is designed for biologists seeking advanced training in biological sequence and genome analysis, computational biology core resource directors and staff, and for individuals in other disciplines (e.g., computer science) who wish to survey current research problems in biological sequence analysis. Advanced programming skills are not required.
lecture/lab schedule for the 2010 course can be found here.
The primary focus of the Computational & Comparative Genomics course is the theory and practice of algorithms in computational biology, with the goals of using current methods more effectively for biological discovery and developing new algorithms. Students more interested in the practical aspects of software development are encouraged to apply to the course on Programming for Biology. Students who would like in-depth training in the analysis of next-generation sequencing data (e.g., SNP calling and the detection of structural variants) should apply to the course on Advanced Sequencing Technologies & Applications.
course is supported by the National
Human Genome Research Institute