Introduction to Biological Data Analysis-E2
| Numbering Code | U-LAS14 20060 SE68 | Year/Term | 2022 ・ First semester |
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| Number of Credits | 2 | Course Type | Seminar |
| Target Year | All students | Target Student | For science students |
| Language | English | Day/Period | Tue.2 |
| Instructor name | Martin Robert (Graduate School of Pharmaceutical Sciences Program-Specific Associate Professor) | ||
| Outline and Purpose of the Course |
Biology has become a data rich science. After lagging behind physicists for many years, biologists are now uncovering large amounts of quantitative data from DNA and protein sequence (genome projects) to large scale analysis of the expression of proteins and metabolites and their interactions. Consequently, numerous databases and resources have emerged to organize, distribute, and make possible the analysis of this huge amount of data. In this course students will learn about common types of biological data that are rapidly accumulating and the related databases. They will learn to use some powerful online databases and tools that do not necessarily require programming skills. Students will use those tools to analyze DNA and protein sequences, visualize the outcome of large-scale experiments and biological networks, and learn how they can be used to derived knowledge and understanding about the system under study. |
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| Course Goals |
By the end of this course participants should be able to: - Understand and explain some of the common types of quantitative biological data - Find and analyze DNA or protein sequences using different databases, repositories, and tools - Exploit linked resources to expand knowledge across data types and resources - Explore the genome and metabolic network of model organisms - Analyze data from a model organism of choice to answer particular biological questions - Gain better understanding of a biological systems through data analysis and interpretation |
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| Schedule and Contents |
The following topics and their feedback will be covered over the course of 14 classes, not necessarily in that order: Week 1 Guidance Week 2-3 Biochemistry and biomolecules review Week 4-5 Genomics and proteomics methods and data Week 6 PubMed review and sequence databases Week 7-8 Introduction to sequence analysis using BLAST Week 9 The UniProt database (features, tools, analysis) Week 10 The KEGG database (features, tools, analysis) Week 11-12 The Biocyc and Ecocyc databases (features, tools, analysis) Week 13 Introduction to biological network analysis Week 14 Project presentation Week 16 Feedback |
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| Evaluation Methods and Policy |
20% Class attendance and participation 60% In-class exercises and homework assignments 20% Project |
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| Course Requirements | The course is targeted to beginners. A basic familiarity with biomolecules and cell biology is desirable but not essential. Students should bring a computer to class to complete in-class exercises and tutorials as well as homework assignments. | ||
| Study outside of Class (preparation and review) | Mainly in the form of assigned reading and homework assignments and work on a project. Students should expect to spend about 1-2 hours per week preparing for the class and completing assignments. | ||
| References, etc. |
Reference material and resources will be derived from various sources that will be announced in class. |
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