This course covers current methods for making use of large molecular data sets to identify the genes that control traits, to characterize genes' functions, and to infer genetic relationships among individuals. It focuses on case studies and current research in agriculture, environmental biology, and medicine to introduce molecular data analysis methods, including analyzing genome sequences, constructing nucleotide alignments, constructing phylogenies, and finding motifs and genes in biological sequences. Lab sessions include an introduction to Unix and Python/R for the biologist and hands-on use of several molecular data analysis problems. Offered conjunction with BIOL*3300. Distinct work is required of graduate students.
This course covers current methods for making use of large molecular data sets to identify the genes that control traits, to characterize genes' functions, and to infer genetic relationships among individuals. It focuses on case studies and current research in agriculture, environmental biology, and medicine to introduce molecular data analysis methods, including analyzing genome sequences, constructing nucleotide alignments, constructing phylogenies, and finding motifs and genes in biological sequences. Lab sessions include an introduction to Unix and Python/R for the biologist and hands-on use of several molecular data analysis problems. Offered conjunction with BIOL*3300. Distinct work is required of graduate students.
