CMSC858E: Bioinformatics for Metagenomics (Fall 2010)

Essential details

Time: Monday & Wednesday, 2:00-3:15pm
Location: CSIC 2107
Instructor: Mihai Pop (mpop at umiacs) x5-7245
Office hours: by appointment only
Office address: 3120F Biomolecular Sciences Building (bldg #296).
Building is usually locked. Call me from the intercom and I'll buzz you in.
3223 AVW (by appointment)
Qualifier status: this is a seminar course and does not count for the area requirement for the PhD and MS degrees


Metagenomics is a fairly new scientific field that applies high-throughput genomic technologies to the study of microbial communities. Microbes are the most abundant forms of life on this planet and inhabit virtually all areas of our environment and our bodies. Yet, we still know very little about the majority of microbes, and their contribution to our health and to the health of our environment. While many bioinformatics tools have been developed over the years for the study of single organisms, these tools can often not be readily applied to the study of communities. In this course we will read and discuss several recent papers describing computational algorithms and techniques that have been developed specifically for metagenomic applications. A particular focus will be placed on the biological questions being asked and how these questions define the requirements of the computational analyses of the data. Throughout the course we will cover a broad range of CS topics that are relevant to metagenomic applications, including: data visualization, machine learning, string matching, network algorithms, etc.


This course is intended for graduate students with a strong computational background but should be accessible to students outside of CS. No knowledge of biology is necessary though some understanding of basic biology is strongly encouraged. The relevant knowledge can be acquired during the course from the background material provided in the papers we will study and from on-line resources.


There are no required textbooks for this course. The course material is primarily recent scientific papers.

Course topics

Course outline

Coursework and grading

Students will be required to read a collection of papers and put together one or more 30 minute presentations describing papers from the reading list. In addition, the coursework includes a research project that will entail either the implementation of an algorithm/tool for metagenomic analysis, or the use of existing tools in the analysis of a metagenomic data-set. The final grade will be assigned on the basis of the quality of in-class presentations, project score, and in-class participation.

Attendance policy

This course follows the University's attendance policy. In short, if you will miss class for any reason you should let me know in advance, unless this is not possible (e.g. sudden illness). In any case, please let me know as soon as you are aware that will not be able to attend a class (e-mail is OK). I will work with you to help you catch up on homework or exams if you have to miss any of the lectures.

Academic integrity

I expect that the students taking this class fully adhere to the Code of Academic Integrity.