The textbook Bioinformatics Algorithms: an Active Learning Approach has now been adopted by 140+ instructors from 40+ countries. Since all these instructors cover similar materials, we have decided to launch a multi-university bioinformatics class that will bring multiple instructors together to enhance the educational experience of students across all participating universities and to facilitate the exchange of the course materials and pedagogical ideas between various instructors.
In Winter 2021, the multi-university class will include classes at Carnegie Mellon University, Johns Hopkins University, Princeton University, Saint Petersburg University, and University of California at San Diego. Each class at these universities will be completely independent with its own schedule, policies, HWs, exams, and grading. However, students in each class will be offered an opportunity to use various materials in the multi-university class as specified by the individual instructors. The multi-university class will use the Ed Digital Learning platform to facilitate communication between students and instructors from various universities. For example, if you decide to post a question on Ed, it can be answered by a student or a professor from other universities.
This educational collaboration will be directed by Professor Niema Moshiri. at University of California at San Diego, an expert in online education technologies (see his TEDx talk The Era of Online Learning. ). Dr. Moshiri will analyze the students’ experiences across various universities, study benefits and limitations of a multi-university class, and will evaluate whether this endeavor should be further scaled in the following years.
Learrn more about the Winter 2021 instructors on our About Us page.
Guest lectures. Each instructor in our multi-university class will share some educational materials to benefit students at all universities. In addition to teaching independent courses at their home universities, the instructors will give the following guest lectures for students at all universities:
Additionally, all students are encouraged to participate in a research-focused “HiFiAssembler” project aimed at genome assembly using the newly emerged: HiFi technology based on long and accurate reads. The genome assembly problem amounts to assembling a genome from a myriad of its error-prone and overlapping fragments, the largest jigsaw puzzle ever assembled by humans. Using overlaps between these short fragments (called reads), you need to reconstruct the genome.
The HiFi technology, developed in 2019, is revolutionizing the way we sequence the genomes – it already contributed to the COMPLETE human genome assembly by the Telomere-To-Telomere consortium in Fall 2020, the problem that remained unsolved since 2000 when the DRAFT human genome was first assembled by the Human Genome Project. See a short video explaining the benefits of HiFi technology:
However, assembly of HiFi reads remains a poorly explored area with many open questions – there are still only three HiFi assemblers and they all were developed very recently:
We will summarize these open questions and will invite you to develop a new HiFi assembler from scratch and address these questions. You will be provided with the sets of HiFi reads for E. coli, fruit fly, and the human X chromosome. Your goal is to assemble these reads, evaluate the quality of assembly, and prepare a short power point presentation (maximum 10 pages) outlining your approach and summarizing your results. The submitted assemblers will be evaluated (based on the assembly quality, the running time, and the originality of the approach) and the winning assembly team will make a short presentation for the entire multi-university class.
The participation in the HiFi assembly project is voluntary but if you are interested, we encourage you to form multi-university teams working on the HiFiAssembler project (to promote interactions between students from different universities) but teams from a single university are also OK. However, we suggest that each team includes at most 2-3 students from the same university (but you can have more students in a multi-university team).
Click here to learn more about the HiFiAssembler project, upload the datasets, and start working on your assembler!
This is our first experience in running a multi-university course and we anticipate that we may overlook something – please do not hesitate to send us your suggestions and help us to succeed!