Project Summary
In modern biological research, computing has become an integral component in Biological
Big Data (BBD) analysis, yet education in computing has not been fully incorporated into life
science education: many biologists are given a diluted treatment of computational genomics that
presents the methods central to the field as nothing more than a toolkit. ¿The pedagogical
challenge facing the development of a computational genomics curriculum is the need to convey
the important ideas ¿without assuming previous exposure to programming. Biologists would also
profit from knowing how to effectively apply various existing genomics software tools and, at the
same time, ¿understand how these tools work, a condition that is often violated in existing
courses.
We believe that high-quality online computational genomics education offers a particularly
attractive solution to the problem because many universities have failed to address this
challenge. It offers a promising pedagogical innovation because it is not ¿replacing anything, but
rather is fulfilling an important need. It bypasses the need for extensive curricular reform at the
level of individual universities and instead adapt to high-quality, open online resources that
lower the cost per student. We believe that our proposed online ¿Computational Genomics
Specialization will contribute to various offline courses (e.g., by enabling a flipped course) that
will be developed in response to the same NIH Funding Opportunity Announcement “Initiative to
Maximize Research Education in Genomics.”
We have published popular bioinformatics and algorithms textbooks, ¿have published papers
on various challenges of education in computational biology in reputable journals, delivered a
TEDx talk on online education, founded a conference specializing in bioinformatics education
(RECOMB-BE), developed multiple successful MOOCs in bioinformatics (including the first
bioinformatics MOOC), and advised the development of Rosalind, an open online platform for
learning bioinformatics through problem solving that has been used by over 100 professors.
Our goals are (1) to develop open, modular, extendable, and adaptable MOOCs covering a
broad range of topics in modern computational genomics, (2) use the developed MOOCs to
competitively recruit the participants into the proposed offline computational genomics short
courses and to bring underrepresented minorities to these events, and (3) establish ¿the
Computational Genomics Education Alliance, a community of educators who will help develop
open, high-quality, modular online content and serve as instructors at our annual courses.