printer friendly pageBIOS 261: Plant anatomy and cellular structure: fundamental concepts to interpret data
Plant anatomy and cell biology. This two-week mini course will introduce the cell types of major organ systems in flowering plants through lectures and readings. Classic and modern techniques to highlight plant cell structures and dynamic processes such as changes in hormone concentration and microtubule dynamics will be presented in laboratory sections immediately following each lecture. Limited to 8 registered students. Graduate students only. Course is not open to undergraduates.
Terms: Sum
| Units: 2
Instructors:
Walbot, V. (PI)
BIOS 262: Learning to Fly: Drosophila Research Methods
This week-long course will be an overview of the fly as a model system, and the tools available to fly researchers. It will cover topics like history, anatomy, development, online databases, genetic toolkits, genome editing techniques, and stem cell, immunology, and neural research methods. Lectures will be given by experts in the field, who will also be encouraged to discuss the advantages and disadvantages of the fly, as well as how this model system differs from vertebrate systems. We will also provide an optional 2-hour lab that will expose students who have little fly experience to basic fly techniques.
Terms: Spr
| Units: 1
BIOS 263: Applied Grant-Writing Skills for Fellowships
Graduate students in the Biosciences PhD Programs develop a fellowship proposal (e.g. NIH F31) focusing on required documents: 1-page specific aims as well as research and career development plans. Students establish a writing practice and learn fundamental grant writing skills through guided exercises, including in-class review and focused faculty feedback.
Terms: Spr
| Units: 2
| Repeatable
10 times
(up to 20 units total)
BIOS 264: Introduction to Data Management and Analysis for Genomics Research
This practical, interactive workshop will introduce participants to concepts, skills and tools for effective management and analysis of genomics data using R, an open source programming language. Topics will include cloud computing for genomics, the command line, data wrangling and processing, and data analysis and processing in R. Students will engage in hands on analyses of genomics data using the Data Carpentry workshop format (see datacarpentry.org). Participants must bring their own laptop, and should plan to participate actively. This class is for any researcher who has data they want to analyze. No prior computational experience is required.
Terms: Win
| Units: 1-2
Instructors:
Cyert, M. (PI)
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