Bioinformatics Courses

MCDB 4520/5520 - Bioinformatics and Genomics (Fall 2010, Spring 2016, Spring 2017)

Computational and experimental methods in bioinformatics and genomics, and how these methods provide insights into protein structure and function, molecular evolution, biological diversity, cell biology, and human disease. Topics include database searching, multiple sequence alignment, molecular phylogeny, microarrays, proteomics, and pharmacogenomics.

CAMPUS: Boulder

MCDB 4521/5521 - Bioinformatics and Genomics Laboratory (Spring 2016, Spring 2017)

Hands on analysis of big data sets associated with genomics. Provides experience with and exposure to computational and experimental methods in bioinformatics and genomics. Students are expected to read original research papers, discuss findings, plan and execute data analysis in selected areas.

CAMPUS: Boulder

APPM 4720/5720; CSCI 4830/7000; MCDB 6440; CHEM 4921/5921 - Statistics & Computation for Genomics and Metagenomics (Spring 2012)

This is one of the two core-unit courses for the CU-IGERT graduate program. The course is designed to prepare students for interdisciplinary research in mathematics, computer science and biology, leveling and filling in students with background knowledge in these fields. It will equip students with a repertoire of concepts and methods that are rarely well known by experts mastering a single one of these disciplines. The course will demonstrate how to collaborate on new and tractable problems in metagenomics or genomics, with a hands-on approach. It will train students to pose problems in a mathematical but biologically sound and computationally tractable context, to identify the limitations of the techniques and models used, and to obtain statistically significant conclusions based on a model. Research projects as well as a major, student-driven project will be assigned during the semester.

Spring 2012 was co-taught with Dr. Manuel Lladser.

CAMPUS: Boulder
Required course for IQ Biology graduate students

Genetics Courses

MCDB 2150 - Principles of Genetics (Spring 2013, 2014, and 2015)

Introduces the behavior of genes and chromosomes in eukaryotic and prokaryotic organisms. Covers three areas: transmission genetics, molecular genetics, and population genetics. Attention is given to genetic mapping, recombinant DNA procedures, and gene expression.

Co-taught with Dr. Tin Tin Su (2013, 2014), Christy Fillman and Jenny Knight (2015).

CAMPUS: Boulder
Required course for MCDB undergraduate students

MCDB 5220 - Molecular Genetics (Methods and Logic) (Spring 2012)

This course focuses on the communication of research results through the presentation of recent journal papers within molecular biology and genetics. In Spring 2012, the papers selected focused on applications of modern sequencing techniques.

Spring 2012 was co-taught with Dr. Tom Blumenthal.

CAMPUS: Boulder
Required course for MCDB graduate students; course is taught in a team-teaching format

Guest Lectures

MCDB 5230 - Gene Expression (2-3 lectures every Fall)

Team taught course focusing on the basic principles of Molecular and Cellular Biology. Dr. Dowell's lectures focus on basic concepts in bioinformatics.

CAMPUS: Boulder
Required course for MCDB graduate students; course is taught in a team-teaching format

CPBS 7711 - Methods and Tools in Biomedical Informatics (2-3 lectures every Fall)

An introduction to the theory and practice of bioinformatics and computational biology. Topics include: the analysis of macromolecular sequences, structures, gene expression arrays, proteomics, and management of the biological literature.

CAMPUS: AMC
Required course for Computational Bioscience graduate students; course is taught in a team-teaching format

CPBS 7712 - Research Methods in Biomedical Informatics (2-3 lectures every Spring)

How to plan, develop, execute and report on research in computational biology. In this course, each faculty member in the computational bioscience program will present a number of lectures on the research currently being conducted in his or her laboratory. Students will plan, execute and report on a research project of their own. This course is a stage in the transition from well-educated students to independent researchers. The work in the course involves a series of supervised activities that introduce the activities of research.

CAMPUS: AMC
Required course for Computational Bioscience graduate students; course is taught in a team-teaching format