KAUST researchers organized a week-long workshop on bioinformatics, covering genomics and transcriptomics data analysis. The workshop targeted students, postdocs, and senior researchers, providing hands-on training in coding and analysis using tools like R, Python, and shell scripts. Attendees with little prior computational biology experience were introduced to fundamental concepts and tools for handling large sequencing datasets. Why it matters: The workshop addresses the increasing need for bioinformatics expertise at KAUST and in the region, crucial for advancing research in fields like evolution and complex diseases.
Søren Brunak presented deep learning approaches for analyzing disease trajectories using data from 7-10 million patients in Denmark and the USA. The models predict future outcomes like mortality and specific diagnoses, such as pancreatic cancer, using 15-40 years of patient data. Disease trajectories and explainable AI can generate hypotheses for molecular-level investigations into causal aspects of disease progression. Why it matters: This research demonstrates the potential of large-scale patient data and AI to improve disease prediction and generate hypotheses for further investigation into disease mechanisms relevant to regional healthcare systems.
This article discusses the use of artificial intelligence in precision oncology, particularly in understanding individual tumor mechanisms and aiding clinical decision-making. Dr. Xinghua Lu, with extensive experience in medicine and biomedical informatics, will present research on individualized Bayesian causal inference methods for investigating oncogenic mechanisms. These methods aim to provide clinical decision support at the cellular, tumor, and patient levels. Why it matters: AI-driven precision oncology can enable more personalized and effective cancer treatments, improving patient outcomes in the region and globally.
KAUST Professor Xin Gao, lead of the Structural and Functional Bioinformatics Group, advocates for interdisciplinarity in academic research, specifically merging AI and bioinformatics. Gao, formally trained in computer science with no formal biology training, integrated biological knowledge independently. At KAUST, he synchronized bioinformatics, machine learning, and AI, despite the challenges of dividing efforts between disciplines. Why it matters: Gao's success highlights the growing importance of interdisciplinary approaches in AI research, particularly in bridging computational methods with specialized domains like biomedicine to drive innovation.
KAUST and Abdulrahman Nasser Alagil Sons Foundation (Jarir Investment) have signed an MoU to establish an endowment supporting AI and bioinformatics training programs at the KAUST Academy. These programs target undergraduate students across Saudi Arabia. The endowment aims to develop curriculum, provide resources, and expand training opportunities. Why it matters: This partnership aligns with Saudi Vision 2030's goals of advancing R&D, promoting innovation, and building national AI capabilities.
KAUST Professor Takashi Gojobori has been elected as a Fellow of the International Society for Computational Biology (ISCB). ISCB is a scholarly society for computational biology and bioinformatics. Gojobori's research interests include comparative genomics and gene expression of neural cells, as well as the marine metagenomics of microorganisms. Why it matters: The recognition highlights KAUST's contributions to computational biology and bioinformatics and strengthens its position as a research hub in the region.
KAUST has inaugurated the Computational Bioscience Research Center. The inauguration included a two-day symposium. Why it matters: This new center will likely boost computational biology research and applications in the region.
KAUST alumnus Dimitrios Kleftogiannis (Ph.D. '16) is now a cancer researcher at the University of Bergen, Norway, using bioinformatics to study liquid biopsies for cancer research. He transitioned from computer science to bioinformatics after his Ph.D. and was inspired by Prof. Mel Greaves at the Institute of Cancer Research in London. Why it matters: This highlights the impact of interdisciplinary training at KAUST and its alumni's contributions to applying AI and computational methods to advance healthcare research.