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Professor Takashi Gojobori elected ISCB fellow

KAUST ·

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.

Decoding biology’s future

KAUST ·

Michael Waterman, professor at USC, and Wei Wang, director at UCLA, gave keynote addresses at KAUST. Charlotte Hauser, KAUST professor of bioscience, also gave a keynote lecture. Peer Bork (EMBL) and Martin Noble spoke with Vladimir Bajic at the event. Why it matters: This indicates KAUST's ongoing engagement with international experts to advance research in computational biology.

The Computational Bioscience Research Center inauguration

KAUST ·

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.

Examining how technology informs science

KAUST ·

KAUST's Computational Bioscience Research Center (CBRC) held a Research Conference on Big Data Analyses in Evolutionary Biology. The conference focused on the impact of large "omics" datasets on evolutionary biology, requiring big data approaches for analysis. Researchers discussed how computer science can contribute to biology and vice versa. Why it matters: Such interdisciplinary events at KAUST can foster innovation at the intersection of computational science and biology, advancing research in both fields.

Forging a career through interdisciplinarity

KAUST ·

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.

Keyes and colleagues take part in historic ISC

KAUST ·

KAUST Professor David Keyes chaired the International Supercomputing Conference (ISC) 2020, which was held virtually due to the COVID-19 pandemic. The conference featured a record registration of 4,735 specialists in high-performance computing (HPC). A paper by KAUST Ph.D. students Noha Al-Harthi and Rabab Al-Omairi on computationally simulated acoustic scattering won the 2020 Gauss Award. Why it matters: KAUST's leadership in ISC and the Gauss Award highlight Saudi Arabia's growing contributions to the global HPC community.

Enabling precision medicine with single cell omics and decentralized clinical studies

MBZUAI ·

Eduardo da Veiga Beltrame, bioinformatics lead at ImYoo (a Caltech spinout), presented on scalable methods for single-cell omics data analysis, including kallisto|bustools and scvi-tools. He highlighted their use in ImYoo's decentralized longitudinal study on Inflammatory Bowel Disease (IBD), where patients self-collect capillary blood samples. Beltrame also discussed his research on STEM education programs in Brazil as a visiting scholar at UC Berkeley. Why it matters: This highlights the growing trend of decentralized clinical studies leveraging advanced single-cell technologies for precision medicine, showcasing the potential of remote data collection and analysis in understanding complex diseases.

Many-cell sequencing: machine learning principles and methods for moving beyond single cells to population-scale analysis

MBZUAI ·

A talk discusses the challenges of single-cell data analysis, such as feature sparsity and the effects of rare cells. AI/ML strategies are uniquely positioned to model this data. ImYoo, a startup founded in 2021, is applying single-cell model architectures for unsupervised discovery of patient groupings and predicting sample-level phenotypical data in autoimmune disease. Why it matters: This highlights the growing application of AI/ML in analyzing single-cell data for population-scale human health studies, an area ripe for innovation and improvement in the Middle East's growing biotech sector.