1.  Preparing undergraduates to succeed in college and beyond in a bioinformatics-rich curriculum  Discussion of existing resources, opportunities, and challenges  Relevant issues identified in the pre-conference survey include:  How do we encourage math-averse students to embrace quantitative and computational analysis?  How much knowledge and expertise in computer science and mathematics do life science majors need?

2. William Morgan, Sofia Visa The College of Wooster

3. Provide undergraduates in computer science OR biology with an interdisciplinary experience to:  Develop a bioinformatics conceptual framework  Learn to use essential bioinformatics tools  Develop programming skills  Explore questions in bioinformatics  Acquire skills and confidence to work on an interdisciplinary team

4. Segment 1: Develop a shared knowledge base  “Essentials” mini-courses Segment 2: Explore & apply bioinformatics tools, working collaboratively  Topics in computational genomics  Genome Annotation; Genome Evolution; Gene Expression  Weekly structure  Genomics / Programming / Case Study

5. Goal: Predict host-targeted proteins encoded in a pathogen genome 1. Translate ORFs of a Phytophthora genome into protein sequences 2. Based on N-terminal signal peptide, identify putative secreted proteins 3. Based on RXLR domain, identify putative host cell-targeted proteins

6.  Textbooks  The Cartoon Guide to Genetics (Updated ed.)  Python for Bioinformatics  Introduction to Computational Genomics: A Case Studies Approach

7.  Department & institutional buy-in  Coordinating instructor activities  Weekly course structure  Balancing course content  Student enrollment levels  Fostering student collaboration