KAUST researchers have identified a protein complex of HuR and YB1 that stabilizes messenger RNA during muscle-fiber formation. The complex protects RNA as it carries muscle-forming code through the cell. Further research aims to elucidate the individual roles of each protein in the stabilization process. Why it matters: Understanding this RNA-stabilizing complex could lead to new therapies for muscle recovery and the prevention of muscle-related pathologies.
A new mini-batch strategy using aggregated relational data is proposed to fit the mixed membership stochastic blockmodel (MMSB) to large networks. The method uses nodal information and stochastic gradients of bipartite graphs for scalable inference. The approach was applied to a citation network with over two million nodes and 25 million edges, capturing explainable structure. Why it matters: This research enables more efficient community detection in massive networks, which is crucial for analyzing complex relationships in various domains, but this article has no clear connection to the Middle East.
KAUST PhD student Zahra Al-Saffar won first prize for her poster presentation at the 52nd European Marine Biology Symposium (EMBS) in Piran, Slovenia in September 2017. Her research was presented in poster format. The symposium focuses on marine biology research. Why it matters: This award recognizes promising research by a KAUST student in the field of marine biology.
Daisuke Kihara from Purdue University presented a seminar at MBZUAI on using deep learning for biomolecular structure modeling. His lab is developing 3D structure modeling methods, especially for cryo-electron microscopy (cryo-EM) data. They are also working on RNA structure prediction and peptide docking using deep neural networks inspired by AlphaFold2. Why it matters: Applying advanced deep learning techniques to biomolecular structure prediction can accelerate drug discovery and our understanding of molecular functions.
Michael Hickner, an Associate Professor from Penn State University, visited KAUST as part of the CRDF-KAUST-OSR Visiting Scholar Fellowship Program. Hickner specializes in Materials Science and Engineering, Chemistry, and Chemical Engineering. The visit was documented with photos by Meres J. Weche. Why it matters: Such programs foster international collaboration and knowledge exchange in science and engineering between KAUST and other leading institutions.
Saudi Crown Prince Mohammed bin Salman's recent visit to Washington signals a potential shift towards deepened strategic technology alliances between the Kingdom and the United States. Discussions included collaborations in AI, quantum computing, and other advanced technologies, aligning with Saudi Arabia's Vision 2030 goals for technological advancement. The visit underscores a mutual interest in fostering innovation and economic diversification. Why it matters: This budding tech-alliance could accelerate Saudi Arabia's AI ecosystem development while opening new market opportunities for US tech companies in the region.
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MBZUAI President Eric Xing has been named a 2023 Fellow of the Institute of Mathematical Statistics (IMS). He was honored for contributions to statistics, machine learning research, AI entrepreneurship, and AI education. The IMS will formally recognize the 2023 fellows at the Joint Statistical Meetings in Toronto in August. Why it matters: This recognition highlights the growing prominence of MBZUAI and its leadership in the international AI and statistics community.