KAUST and KFSHRC have developed NanoRanger, a new gene sequencing system for identifying mutations causing genetic diseases. NanoRanger offers a faster and simpler process to detect DNA abnormalities at base resolution, building on existing long-read sequencing technologies. The system is designed to be cheaper and faster, targeting diseases prevalent in Saudi Arabia due to consanguinity. Why it matters: The technology has the potential to improve diagnosis and treatment of Mendelian diseases, which are especially prevalent in the Arab world.
KAUST and King Faisal Specialist Hospital and Research Centre (KFSHRC) are collaborating to develop an RNA sequencing tool to improve the diagnosis rate of genetic diseases. The tool analyzes RNA data to find aberrant transcripts and mutations, building on KFSHRC's clinical data and KAUST's computational expertise. The team has already solved cases that DNA sequencing alone could not, including a case of a young child with brain damage caused by a recessive gene mutation. Why it matters: This collaboration can improve disease management and preventative services in the region, directly contributing to Saudi Arabia’s national research priority of health and wellness.
The Technology Innovation Institute's (TII) Cryptography Research Center (CRC) has launched CLAASP, a cryptographic library for the automated analysis of symmetric primitives. CLAASP, built on SageMath and Python3, automates the design analysis of block ciphers, cryptographic permutations, hash functions, and stream ciphers. Released as an open-source tool with a GPLv3 license, CLAASP aims to ensure design sovereignty for organizations creating symmetric ciphers. Why it matters: This tool provides an important resource for the region to strengthen its cryptographic capabilities and contribute to global efforts in safeguarding digital infrastructure against evolving threats, including quantum computing.
KAUST researchers developed a statistical approach to improve the identification of cancer-related protein mutations by reducing false positives. The method uses Bayesian statistics to analyze protein domain data from tumor samples, accounting for potential errors due to limited data. The team tested their method on prostate cancer data, successfully identifying a known cancer-linked mutation in the DNA binding protein cd00083. Why it matters: This enhances the reliability of cancer research at the molecular level, potentially accelerating the discovery of new therapeutic targets.
KAUST alumna Sara Althubaiti (M.S. '18) is now a computer science Ph.D. student in the Bio-Ontology Research Group, focusing on using AI to prioritize cancer mutations and predict new disease treatments. Her work involves understanding the relationship between drug side effects and disease phenotypes. Althubaiti aims to continue in academia after her Ph.D., contributing to research in Saudi universities. Why it matters: This highlights KAUST's role in fostering local talent and contributing to advancements in AI-driven healthcare research within the Kingdom.
Petar Stojanov from the Broad Institute of MIT and Harvard will give a talk on cancer data analysis, covering the fundamentals of cancer, the nature of large-scale data collected, and main analysis objectives. The talk will also address open questions in cancer data analysis and how machine learning and generative modeling can help. Stojanov's research focuses on applying machine learning to genomic analysis of cancer mutation and single-cell RNA sequencing data. Why it matters: Applying AI and machine learning to cancer research can lead to a better understanding of the disease and development of new therapies.
MBZUAI hosted an AI Talks session featuring Dr. Mohammad Yaqub discussing AI's role in fighting COVID-19 and predicting future pandemics. AI can detect outbreaks by mining news and social media for unusual patterns, as demonstrated by companies flagging pneumonia cases in Wuhan before the official announcement. AI-empowered drug repurposing identified Baricitinib as a potential COVID-19 treatment and can predict virus mutations. Why it matters: This highlights the potential of AI to enhance pandemic preparedness and response in the region, particularly through institutions like MBZUAI.