Robin teaches both undergraduate and graduate courses listed in several departments (MCD Biology, Applied Math, Computer Science, Chemistry) at the University of Colorado Boulder. She also regularly serves as a guest lecturer for graduate courses in the Computational Bioscience Program at the University of Colorado Anschutz Medical Campus. Students seeking information on the courses Robin teaches should follow the link below.
Most of our learning in science takes place outside the classroom. The foundational material we cover in classes and educational labs serves as a stepping stone to the exciting work of actually doing science, be it in the field, research lab, or computer room. Our goal is to equip "antedisciplinary" scientists to capably address modern biological questions that interest them. We recognize that achieving this goal can require knowledge of a diverse set of skills that cross traditional academic boundaries. To that end, we recruit graduate students from across the biological and computational sciences. We accept graduate students from CU-Boulder's Molecular, Cellular, and Developmental Biology, Computer Science, and Applied Mathematics departments, as well as CU-Denver's Computational Bioscience Program and the BioFrontiers Institute's program in Interdisciplinary Quantitative Biology (IQ Biology).
iGEM is an undergraduate synthetic biology competition, featuring over 200 collegiate teams from around the world. CU-Boulder's team is led by Dowell Lab grad students Tim Read and Joe Rokicki. iGEM is a summer-long, project-based research experience where teams of undergraduates engage in a synthetic biology competition, working to design, construct, and operate biological circuits of their own design in living cells (typically E. coli). At the end of the summer, they present their creations at the iGEM Jamboree, an international science fair-styled competition. Follow the link below for more information about the CU-Boulder iGEM team.
The IQ Biology program, offered through the BioFrontiers Institute, trains scientists to effectively utilize computational and mathematical resources to address biological questions. Students learn in an interdisciplinary community before choosing a final PhD degree program. Robin is an IQ Biology faculty member, and accepts graduate students for rotation in the lab. For more information about the IQ Biology program, follow the link below.
In addition to our work in the classroom and the lab, we often offer informal educational seminars and online training in various aspects of computational biology. We also engage with local high school students, both by inviting them into the lab and by working with them on their campuses. David Knox, a grad student in the lab, recently worked with the NSF-funded eCSite Project to incorporate computational biology training into high school biology classes.
The goal of the Dowell Lab HackCon 2018 Nascent Workshop is to introduce the analysis pipeline used when analyzing nascent transcription data obtained through high-throughput sequencing (HTS). We will compare and constrast this pipeline to that of steady-state analysis (e.g. RNA-seq), as well as describe future directions for interrogating this data.
For the purposes of this workshop, we are providing access to a draft of a tutorial for transcription analysis which will eventually become readily available to the public. Keep in mind, most of the pages are not yet built, but you can begin to explore the format and access useful instruction for parts of this workshop, including the integrative genomics viewer (IGV) and DESeq2 (still under construction).
If you have any feedback or input for future directions regarding the tutorial, please contact Margaret Gruca @ firstname.lastname@example.org.
Python is one of the most popular computer programming languages, especially in the field of bioinformatics. Take our free, online course in Python programming to learn the basics of using this powerful and fun language to analyze biological datasets!
The goal of this workshop is to teach the fundamental computational skills necessary for many short read sequencing analysis. In the first five days of this course participants will learn basic Unix/Linux, how to use large compute servers, read quality control, and read mapping. In the last three days we will cover the basic fundamentals of commonly used genomic short read sequencing approaches (DNA-seq, RNA-seq, and ChIP-seq). Our goal is to provide the basic skills necessary for participants to be enabled to learn how to analyze their own data after the course (though some self-study after the course will be necessary).
The format of this course will be a reverse classroom. Attendees will be asked to watch video lectures outside of class. During classroom time (1pm to 5pm) attendees will be working through example analysis. In addition, each day we will provide attendees with homework activities that they can optionally complete on their own time to further improve their computational skills.
The goal of this workshop is to teach the experimental details of preparing nascent transcription libraries.