Unpredictable and rapidly spreading, the Covid-19 coronavirus has travelled from its earlier concentration in China to reach more than 100 countries, infecting over 110,000 people and causing upwards of 4,000 deaths thus far. Given its worldwide impact, the World Health Organization last month declared the coronavirus a global health emergency.
In comparison to the last major outbreak of the SARS virus in 2003, those fighting this particular epidemic can leverage new and emerging technologies that quickly aid public health bodies in creating a valuable understanding of the coronavirus, guiding prevention efforts, augmenting human aid and support efforts, and facilitating virus research.
In recent years, AI has begun to play a significant role in the health-care sector: Advanced computing and data-analysis tools enable information sharing and diagnostic practices, and deepen the medical profession’s understanding of diseases and infections. Prompted by the urgent need to contain Covid-19, government agencies and private companies around the world are increasingly looking toward AI-based techniques to provide insight on its spread and support treatment for those who have been infected.
AI and virus research
Because of Covid-19’s unpredictable but highly-contagious nature, academic and medical communities have prioritized analyzing the structure of the virus in order to create an effective vaccine. However, this virus is particularly challenging because it belongs to a family of enveloped coronaviruses that contain single-strand RNA structures. Similar to other double-stranded viruses including HIV, Ebola, Influenza, and others, Covid-19 is capable of rapidly mutating, making vaccine development and virus analysis difficult.
To support the research, Baidu has made its Linearfold algorithm available to scientific and medical teams fighting the outbreak. The Linearfold algorithm, published in partnership with Oregon State University and the University of Rochester in 2019, is significantly faster than traditional RNA folding algorithms at predicting a virus’s secondary RNA structure. Analyzing the secondary structural changes between homologous RNA virus sequences (such as bats and humans) can provide scientists with further insight into how viruses spread across species. Due to the recent outbreak, Baidu AI scientists have used this algorithm to predict the secondary structure prediction for the Covid-19 RNA sequence, reducing overall analysis time from 55 minutes to 27 seconds, meaning it is 120 times faster.
To access the full article, click here.