While school is in session, EECS invites a distinguished researcher or practitioner in a computer science or electrical and computer engineering-related field to present their ideas and/or work. Talks are generally targeted to electrical engineering and computer science graduate students. This colloquium series is free and open to everyone.

Upcoming Colloquia

AI Seminar: Linear-Time Algorithm to Find the Achilles' Heels of SARS-CoV-2 Genomes

Wednesday, January 26, 2022 - 1:00pm to 2:00pm
Zoom: https://oregonstate.zoom.us/j/93591935144?pwd=YjZaSjBYS0NmNUtjQzBEdzhPeDZ5UT09

Speaker Information

Liang Huang
Associate Professor
Computer Science
Oregon State University


The constant emergence of COVID-19 variants reduces the effectiveness of existing vaccines and test kits. Therefore, it is critical to identify conserved structures in SARS-CoV-2 genomes as potential targets for variant-proof diagnostics and therapeutics. However, the algorithms to predict these conserved structures, which simultaneously fold and align multiple RNA homologs, scale at best cubically with sequence length and are thus infeasible for coronaviruses, which possess the longest genomes (∼30,000 nt) among RNA viruses. As a result, existing efforts on modeling SARS-CoV-2 structures resort to single-sequence folding as well as local folding methods with short window sizes, which inevitably neglect long-range interactions that are crucial in RNA functions.

Here we present LinearTurboFold, a linear-time algorithm for folding RNA homologs that scales linearly with sequence length, enabling unprecedented global structural analysis on SARS-CoV-2. Furthermore, LinearTurboFold identifies undiscovered conserved structures and conserved accessible regions as potential targets for designing efficient and mutation-insensitive small-molecule drugs, antisense oligonucleotides, small interfering RNAs (siRNAs), CRISPR-Cas13 guide RNAs, and RT-PCR primers. LinearTurboFold is a general technique that can also be applied to other RNA viruses and full-length genome studies and will be a useful tool in fighting the current and future pandemics.

This work has been published at Proceedings of National Academy of Sciences, marking the first PNAS paper ever from OSU EECS.

Speaker Bio

Liang Huang (PhD, UPenn, 2008) is an Associate Professor of Computer Science at Oregon State University and a Distinguished Scientist at Baidu Research USA. He is a leading computational linguist, and was recognized at ACL 2008 (Best Paper Award) and ACL 2019 (Keynote Speech), but in recent years he has been more interested in applying his algorithmic expertise to biology problems such as RNA folding and RNA design. Since the outbreak of COVID-19, he has shifted his attention to the fight against the virus, which resulted in high-impact work such as efficient algorithms for stable mRNA vaccine design (under review at Science, being used by 30+ companies), and for homologous folding of RNA genomes (PNAS, 2021).

Past Colloquia

Stephen Gould
Wednesday, January 19, 2022 - 1:00pm to 2:00pm
Alan Fern
Wednesday, January 5, 2022 - 1:00pm to 2:00pm
Noam Brown
Wednesday, December 1, 2021 - 1:00pm to 2:00pm
Stefan Lee
Wednesday, November 17, 2021 - 1:00pm to 2:00pm
Lihong Li
Wednesday, November 10, 2021 - 1:00pm to 2:00pm
Jing Sun
Monday, November 8, 2021 - 3:00pm to 4:00pm
Caelan Garrett
Wednesday, November 3, 2021 - 1:00pm to 2:00pm
Javad Azimi
Wednesday, October 20, 2021 - 1:00pm to 2:00pm