In this changing landscape...


With the advent of data-intensive technologies in modern biology, computational and bioinformatic approaches are quickly becoming essential parts of every biologist’s toolkit. It is therefore of great importance to provide graduate students and postdocs with the necessary skills that allow them to design, analyze, and interpret complex large-scale experiments. The Center for Computational Biology & Bioinformatics, directed by Dr. Hans Hofmann, in collaboration with the Genome Sequencing & Analysis Facility (GSAF), and the Center for Systems & Synthetic Biology (CSSB), sponsors numerous short courses, workshops, working groups, and community events that complement semester-long for-credit courses.

Scroll down to view calendar.

Summer School for Big Data in Biology

The Summer School offers intensive four-day workshops on diverse topics for analysis of large-scale DNA, RNA, and protein datasets.

LEARN MORE

CCBB Short Courses

Each long semester, the CCBB offers a variety of short courses in diverse topics for learning computational approaches to biological problems.

LEARN MORE

Informal Semester-long Courses

Each long semester, we offer several non-credit courses on topics in biological computing. Courses are for students that have no prior experience as well as intermediate to advanced users. LEARN MORE

For-credit courses

Numerous semester-long courses are offered at the undergraduate and graduate level. The Graduate Program in Cellular and Molecular Biology, Track in Bioinformatics and Computational Biology, also provides information. LEARN MORE

Collaboratorium

The Collaboratorium in FNT 1.202 and the lobby of the first floor of FNT is intended to be a collaborative working space for anyone learning, doing, or discussing bioinformatics. Contact Benni Goetz for more information.LEARN MORE

Summer Statistics

Of additional interest is the Department of Statistics and Data Sciences' Summer Statistics Institute, which offers intensive four-day workshops in diverse topics from introductory data sciences to advanced statistics. LEARN MORE