Mini-Courses - Winter 2015
These intensive 1-3 week courses allow students to tailor their education across disciplines without requiring a full quarter's commitment and are open to postdocs. Students and Postdocs explore new directions for current research, potential postdoctoral avenues, or just topics of interest. Stanford Biosciences students and postdocs have highlighted these offerings as among the most exciting parts of their education, for the way in which they catalyze their research and open new paths.
As a reminder, more than 10 units will result in additional tuition charges. If you don't have units available (3 units max for TGR students, 10 units max for non-TGR students) please attempt to adjust your units when you enroll in a mini course as soon as possible. It is possible to adjust your research units to accomodate mini courses. If this is the case, please discuss with your PI and see your Student Services Administrator (SSA) or Julianna Prieto for help registering. For other eligibility and tuition questions please contact your SSA.
Please note, for Post Doctoral registration interest in any one of these mini courses please visit the designated Postdoc Registration link to apply. Registering is not a guarantee of enrollment or for attending the class. You will receive a separate email confirming admittance once the selection process has been completed. Selection is based on space availability and interest in course. If admitted, you must attend all days of the course. There are no fees to take these courses.
Flexible registration deadlines apply, however, space is limited and enrollment is capped so please attempt to enroll or apply by normal registration deadlines.
| Course | Description | Date & Time |
|---|---|---|
| Bios 205 | Introductory Data Analysis in R for Biomedical StudentsTopics include: basics of R (widely used, open-source programming and data analysis environment) programming language and data structures, using RStudio, reading/writing files, graphics tools for figure generation, survey of relevant R library packages. Interactive format combining lectures and computer lab. Instructor: Steven Bagley MD |
3/2 - 3/20 • M W F |
| Bios 218 | Molecular Basis of Membrane TrafficTransport of proteins through the secretory and endocytic pathways is essential for life; dysregulation causes disease and pathogens hijack these pathways to their best advantage. 3 international experts present didactic lectures and engage with students. Topics include: Nobel prize winning-genetic and biochemical experiments to identify key components; coated vesicle formation and cargo selection; control of membrane traffic by Rab GTPases; unsolved mysteries in membrane traffic. Instructor: Suzanne Pfeffer PhD |
3/9 - 3/13 • M T W Th F |
| Bios 232 | Two-photon Imaging of Neural CircuitsTwo-photon microscopy has been widely applied to investigation of synaptic physiology,dendritic integration, neuronal and glial activation, and neuronal population dynamics in vivo. The goal of this mini course is to provide solid practical training on 2-photon imaging to young researchers, particularly graduate students and postdoc fellows. Instructor: Jun Ding PhD |
3/2 - 3/13 • M T W Th F |
| Bios 234 | Personalized Genomic MedicineStudents will learn about next-generation sequencing and its implications for personalized genomic medicine. Students will gain hands-on experience with popular DNA sequence analysis tools as well as a practical understanding of the underlying algorithms and biomedicine. Instructor: Rachel Goldfeder, Dennis Wall PhD |
3/2 - 3/20 • M W F |
| Bios 237 | Investigating Biology with Fluorescent ProteinsFluorescent proteins are a proven research tool for imaging a wide range of biological phenomena and continuously uncover exciting discoveries in many areas. In this Mini-course, students will gain practical expertise in concepts, methodology, and data analysis through lectures, literature discussion, and hands-on computer exercises with "real world" data. By the end, students will be able to design and implement effective experiments using fluorescent proteins in their own research. Instructor: Frank Cochran PhD, Michael Lin MD PhD |
3/2 - 3/13 • M W F |
| Bios 239 | Synapse DevelopmentIn this course we will delve into the mechanisms of synapse development, including the role of adhesion molecules in establishing neuronal contacts, the function of synapse-inducing molecules, how pre- and postsynaptic material is transported to nascent synapses, synapse maturation, synapse elimination as well as how synaptic dysfunction may lead to neurological disorders. The course will focus on readings from primary literature. Instructor: Kang Shen PhD, Peri Kurshan PhD |
3/2 - 3/20 • M W F |
| Bios 240 | Cellular Metabolism: An Emerging Hallmark of Cancer and AgingIntroduction to cellular metabolism, including changes in metabolic flux that drive diverse disease states from cancer to aging. Topics covered will include cancer metabolism, cellular nutrient sensing, metabolism in aging, and the influence of metabolism on stem cell fate. This course will use discussion of recent advances in the field to place an emphasis on practical applications, including the integration of metabolomics into the era of “Big Data”. This mini-course will culminate with a lab section allowing the students to conduct an extracellular flux experiment using the Seahorse analyzer to study changes in mitochondrial respiration and glycolysis in cancer cells. Instructor: Amatto Giaccia PhD, Edward LaGory PhD |
3/2 - 3/19 • M Th |
| Bios 241 | Dissecting algorithms for RNA SequencingRNA-Seq is a powerful technology for quantifying RNA transcripts and discovering new features of transcription. Inference from RNA-Seq experiments almost always relies on either the application of computational algorithms or statistical models. Many tools are written as software packages that are applied by the user and often, their inner workings are not completely described. In this class, we will study a few popular and commonly used algorithms for RNA-Seq analysis. The course will dissect the algorithmic assumptions, statistical methods they use to test hypotheses about RNA expression and will evaluate properties such as robustness, sensitivity and specificity, highlighting some large "blind spots" in many algorithms. Instructor: Julia Salzman PhD |
3/2 - 3/20 • M W F |
