A team of researchers from the Agency for Science, Technology and Research’s (A*STAR) Genome Institute of Singapore (GIS) have developed a software that extracts RNA modifications (an additional layer of information above the genetic molecule RNA) from genomics data. Their research was published in Nature Biotechnology.
For RNAs, chemical molecules may change the function of the same RNA. These RNA modifications are widespread, but because they do not change the letters of the RNA, they are very difficult to identify. More than 100 RNA modifications are known to play different roles in cells. Some of these RNA modifications are associated with disease risk, while others are used in mRNA vaccines.
One of the most common modifications is the m6A methylation of the adenosine in RNAs. In the past, identifying RNA modifications required labour- and time-intensive bench-experiment assays that only very few laboratories can perform.
To overcome these limitations, the team utilised Nanopore direct RNA-sequencing, a new transcriptomic technology that sequences native RNA molecules with its modifications retained. To extract the hidden layer of RNA modifications, they developed an Artificial Intelligence (AI)-based method that re-purposes tools from AI research to precisely detect differences in RNA modifications. A property employed in the method is the consistent data of the unmodified sites, and the existence of modifications disrupts this consistency.
Similar problems occur in other data-rich areas such as finance or speech recognition that tap on machine learning. Here, they adopted an existing statistical model that is used frequently in data science, so that it can precisely identify these modified sites.
By collaborating with the National University Cancer Institute, Singapore (NCIS), the team successfully detected the m6A RNA modification using the AI tool in multiple myeloma cancer patient samples, showing the AI tool’s potential for large-scale clinical analyses. The scientists have been interested in studying m6A modification in myeloma as this may have important clinical and therapeutic implications for patients with poor outcomes. Now with the AI tool, they have an important tool to facilitate their studies.
The ability to map new RNA modifications is vital for determining their functions. Since the AI tool does not require specific reagents that specialise in identifying only a single RNA modification type, it can potentially detect other RNA modifications beyond m6A. Therefore, the AI tool’s flexibility can expedite our efforts to discover novel RNA modification functions.
Singaporean researchers have been inventing various technologies in the healthcare sector, including a mobile app for the Neonatal Intensive Care Unit. As reported by OpenGov Asia, Singaporean students decided to create a mobile app related to healthcare that can have a huge impact on society. What began as a student project became an innovative productivity tool that was actually used by doctors in the Neonatal Intensive Care Unit (ICU). Initially, the team assumed that their mobile app was meant simply as a school project, but the team did such a great job with it that it was actually implemented by doctors in the Neonatal ICU.
Initially, the brief to the team was to come up with a mobile database to merely store medical information. However, as the brief evolved, the team later identified opportunities to increase the app’s functionalities. They scoped three key workflow areas to improve on:
- Minimise human error: The previous process required manual input and calculation using Excel, and the mobile app eliminates this by providing faster and better computation on the spot. In fact, the team managed to resolve the issue of computing the formula right down to the decimal point.
- Offline capability: Since medication is updated very frequently, the team managed to create a database that could be updated not just on-the-go but also offline.
- Portable solution: In emergencies, a mobile app with its portability is definitely an advantage. In cases of infant resuscitation, a lot of medication and tubings are required, and with the app, doctors only need to input basic details to generate life-saving information.
