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BIOLOGY/COMPUTER SCIENCE 251 – Spring 2006 INTRODUCTION to BIOINFORMATICS COURSE SCHEDULE Steve James 255 Science Center 337-6170 [email protected] Date Carl Leinbach 206 Glatfelter Hall 337-6641 [email protected] Lecture topic Science Ctr 274 MWF, 10 – 10:50 W, 1 - 3 lab Glatfelter 203 Laboratory Jan 20 What is Bioinformatics? Historical overview No lab Jan 23 25 27 Building blocks: DNA and RNA structure and chemistry Building blocks: Protein structure and chemistry Central Dogma – information flow in living systems Film – NOVA: “Cracking the Code” Jan Feb 30 1 3 6 8 10 Genetic code: Translation, degeneracy, and wobble hypothesis Genetic code: Synonymy, non-synonymy, and evolution Genome structure and function: Viruses Working with a single DNA sequence: C & N, Chap. 5 Genome structure and function: Bacteria Eukaryotic genome structure: Trypanosomes and fungi Eukaryotic genome structure: The Human Genome Sequence identification resources and use: C & N, Chap. 3 13 15 17 EXAM 1 Exploring whole Genomes: C & N, Chap. 3 Feb 20 22 24 Dynamic Programming and Global Alignments Semiglobal Alignments Local Alignment Wet lab: PCR amplification of human DNA Feb Mar 27 1 3 Extension of Local Alignment: FASTX and BLAST FASTX and BLAST continued Special applications: Phi- and Psi-BLAST Independent work on PCR project: Wed - Thurs - Fri. Mar 6 8 10 Multiple Sequence Alignment – Hidden Markov Models Sequence comparison: C & N, Chaps. 7,8 Feb Feb March 10-20 Mar 20 22 24 How to design PCR primers to obtain your favorite gene Simple alignments, gaps, and scoring matrices Multiple sequence alignment – ClustalW & Pileup EXAM 2 Spring Recess Evolution and natural selection Agents of variation: Meiosis, recombination, mutation Molecular clocks: Estimating rates of genetic change Multiple Sequence Alignments C & N, Chap. 9 Mar April Apr 27 29 31 3 5 7 10 12 Application of clocks to the mitochondrial Eve hypothesis Adam and the evolution of the Y chromosome Building Phylogenetic Trees Phylogenetics: producing proofs or supporting hypotheses? C & N, Chap. 13 Construction of phylogenetic trees Distance-based methods of phylogenetics Character-based methods of phylogenetics Locating Genes in a DNA Sequence C & N, Chap. 5 Genomics & gene recognition prokaryote genomes Protein Sequences C & N, Chap. 6 EXAM 3 April 13-18 Easter Recess Apr 19 21 The transcriptome: cDNA microarrays and DNA chips Oligonucleotide microarrays – medical applications Protein Visualization C & N, Chap. 13 Apr 24 26 28 Proteins, the final frontier: protein chemistry & structure The protein folding problem Protein Folding Algorithms: Visualizing protein structure Work on final project Protein Threading – Folding in Reverse Proteomics, protein chips, & medical applications Work on final project May 1 3 5 May 10 EXAM 4 FINAL PROJECT DUE BIOLOGY/COMPUTER SCIENCE 251 – Spring 2006 INTRODUCTION to BIOINFORMATICS Introduction to Bioinformatics is a hands-on course that will introduce students in biology and computer science to the emerging field of bioinformatics, where biology and computer science intersect to interpret the rapidly expanding body of biological information deriving from genome sequencing and genomic and proteomic approaches to molecular biology and evolution. Application of bioinformatic software tools to the analysis of gene sequences and protein structures will be emphasized. Students will undertake a laboratory project combining in silico and in vitro approaches to isolate and then analyze a segment of their own DNA. An introduction to computer algorithms used in bioinformatic software will be provided, though no computer science knowledge is required for this course. Three lecture hours and two laboratory hours per week, and a final project. This course serves as an elective in the Biology major and minor, the Biochemistry and Molecular Biology (BMB) major, and the Computer Science major. This course may be used to fulfill major requirements in Biology and Computer Science. As an interdisciplinary course, Bio/CS 251 Introduction to Bioinformatics will complement existing courses in Genetics (Bio 211), Cell Biology (Bio 212), Molecular Genetics (Bio 351), Biochemistry (Bio 334), Introduction to Computer Science (CS 103), Computer Science I (CS 111), Theory of Computation CS 301), Principles of Database Systems (CS 360), and Introduction to Artificial Intelligence (CS 371). Student learning goals: Students in this course will develop the following competencies - 1. Become proficient at using a wide array of in silico bioinformatic tools; use these tools to discover and analyze genes and their protein products; learn how to use bioinformatic tools to probe genome structure and genome organization; learn how to use bioinformatic tools to study molecular evolution and molecular phylogenetics, with an emphasis on the human genome. 2. Understand the increasingly important roles and contributions of bioinformatics in the management, analysis, and exploration of biological information; 3. Understand and apply basic principles of computer programming employed in the design of bioinformatic software; 4. Independently design topical hypotheses relating to gene discovery, proteomics, genome structure, and molecular evolution, and test them using bioinformatic tools and principles. Prerequisites: A 100-level biology course or permission of the instructors Recommended: CS 103 or CS 111 Instructors: Steve James, Biology Carl Leinbach, Computer Science Lecture: MWF10-10:50 am Science Center 260 255 Science Center, x6170, sjames 206 Glatfelter Hall, x6640, leinbach Laboratory: W 1-3 pm Science Center 260 Lecture text: Krane, D.E. and M.L. Raymer. 2003. Fundamental Concepts of Bioinformatics. New York: Benjamin Cummings. Laboratory text: Claverie, J-M. and C. Notredame. 2003. Bioinformatics for Dummies. New York: Wiley Publishing Company. Course Grade: Four one hour exams Bioinformatics final project Quizzes and homework Laboratory assignments 15%each 15% 5% 20% Final project: Option 1: each student choosing this option will use bioinformatic tools to perform genomic and proteomic analyses of a novel, recently released genome. The student will employ methods for gene discovery and analysis, and will study genome structure and genome evolution. The student will also employ in silico DNA microarray methods for measuring global gene expression, and will use proteomic tools for in silico analysis of the products encoded by genes that are discovered in the course of the project. Option 2: each student choosing this option will write programs in the language of to their choice to implement the algorithms that have been illustrated in class and keep an electronic portfolio of these programs with sample data from a publicly available web site. Each program must be able to read the data and analyse it. The portfolios will be inspected and programs run by the instructors at periodically announced intervals. At the end of the semester the student will use the programs in the portfolio to perform an appropriate bioinformatics investigation. Attendance policy: Attendance in lecture and lab is mandatory. A student with more than three unexcused absence from lectures, or from one laboratory, will be invited to leave the course.