BISC 478 : Computational Genome Analysis Instructors: Fengzhu Sun, Ting Chen, Frank Alber Time: 9:30 – 10:50 am TTh With the development of new biotechnologies, enormous amount of data including molecular sequences, networks, pathways, structures, genetic polymorphisms, etc. have been accumulated and deposited into databases. Most biological laboratories and biotechnological companies use these data sources for research and development. The molecular data will also significantly improve our understanding of human health. This course introduces students to the basics of computational and statistical thinking within the context of biology and for data analysis. The course content includes introduction to probability and statistics, molecular sequence database searches, gene expression analysis, phylogenetic analysis, and disease gene identification. The course is essential for biology students interested in using modern computational and informatics tools to solve biological problems and students with quantitative skills to apply their skills to real world problems. This is a required course for the minor in computational biology and bioinformatics. Students with computational biology and bioinformatics backgrounds are in high demand in academia, industry, and government. BISC 478 : Computational Genome Analysis Time: 9:30 – 10:50 am TTh, Room: RRI 301 Discussion 4-4:50 TTh, Room: RRI 301 Instructors Professor Tim Chen Professor Fengzhu Sun Professor Frank Alber Phone: (213)740-2415 Email: tingchen@usc.edu Phone: (213)740-2413 Email: fsun@usc.edu Phone: (213)740-0778 Email:alber@usc.edu T:1-3pm TTH:11:00-12:30 TBA Book: Computational Genome Analysis: An Introduction. (Deonier, Tavare, Waterman, Springer 2005) Course Content This course provides an introduction to the computational side of molecular biology, with an emphasis on genome analysis. With the development of new biotechnologies, enormous amount of data including molecular sequences, networks, pathways, structures, genetic polymorphisms, e. have been accumulated and deposited into databases. Most biological laboratories and biotechnological companies use these data sources for research and development. The molecular data will also significantly improve our understanding of human health. This course introduces students to the basics of computational and statistical thinking within the context of biology and for data analysis. The course content includes introduction to probability and statistics, molecular sequence database searches, gene expression analysis, phylogenetic analysis, and disease gene identification. BISC478 Date Computational Genome Analysis Topic Lecture 1 Introduction to Genomes (Ch1, all) Lecture 2 Words/ An Introduction to Probability, 1 (Ch2; 2.1-2.3.3) Wk. 2 Lecture 3 Lecture 4 Words/ An Introduction to Probability, 2 (Ch2; 2.3.4-2.5) Words/ An Introduction to Probability, 3 (Ch2; 2.6-2.9) Wk. 3 Lecture 5 Lecture 6 Words/ An Introduction to Statistics, 1 (Ch3; 3.1-3.2) Words/ An Introduction to Statistics, 2 (Ch3; 3.3-3.4.1) Wk. 4 Lecture 7 Lecture 8 Words/ An Introduction to Statistics, 3 (Ch3; 3.4.2-3.6) Physical Mapping-1 (Ch4; 4.1-4.4) Wk. 5 Lecture 9 Mini-review Examination I Wk. 6 Lecture 10 Genome Rearrangements (Ch5;5.1-5.2) Wk. 1 Lecture 11 Genome Rearrangements (Ch5;5.3-5.4) Wk. 7 Lecture 12 Sequence Alignments (Ch6;6.1-6.4) Lecture 13 Sequence Alignments (Ch6;6.5-6.8) Wk. 8 Lecture 14 FASTA and BLAST (Ch7;7.1-7.2,7.5) Lecture 15 FASTA and BLAST (Ch7;7.3-7.4) Wk. 9 Lecture 16 Sequence Assembly (Ch8;8.1-8.3) Lecture 17 Sequence Assembly (Ch8;8.3-8.4) Spring Break Spring Break Wk. 10 Lecture 18 In-Class Discussion and Mini-review Examination II Wk. 11 Lecture 19 Clustering (Ch10; 10.1-10.3) Lecture 20 Clustering (Ch10; 10.4-10.5) Wk. 12 Lecture 21 Gene Expression (Ch11; 11.1-11.3) Lecture 22 Gene Expression (Ch11; 11.4) Wk. 13 Lecture 23 Gene Expression (Ch11; 11.5) Lecture 24 Phylogenetics (Ch12; 12.1-3) Wk. 14 Lecture 25 Phylogenetics (Ch12; 12.4-13.5) Lecture 26 Genetic Variation (Ch13; 13.1-13.3) Wk. 15 Lecture 27 Genetic Variation (Ch13; 13.4-13.6) Lecture 28 Review Final examination (Tue, 8:00-10:00 am, RRI301)