CMSC858E: Bioinformatics for Metagenomics (Fall 2010)
Time: Monday &
Location: CSIC 2107
Mihai Pop (mpop at
Office hours: by
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
Qualifier status: this is a seminar course
and does not count for the area requirement for the PhD and MS
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,
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.
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.
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.
I expect that the students taking this class fully adhere to the
Code of Academic