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MBZUAI opens applications for first master’s and Ph.D. cohorts in computational biology

MBZUAI ·

MBZUAI has launched master’s and Ph.D. programs in computational biology, expanding its research into life sciences. This includes projects like AIDO (AI-Driven Digital Organism) and analysis of the Emirati Genome Program. The programs are part of MBZUAI’s School of Digital Public Health and aim to integrate computational biology with precision medicine. Why it matters: This initiative supports the UAE's vision for a knowledge-based economy and its ambition to become a global center for scientific and technological progress in biotechnology and healthcare.

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.

Biweekly research update

KAUST ·

KAUST Discovery Professor Jesper Tegnér collaborated with UK researchers to develop algorithms explaining decision-making in insects and rats. Assoc. Prof. Robert Hoehndorf's lab introduced a tool for identifying genetic variants linked to rare diseases based on patient symptoms. KAUST scientists also studied monkeypox infection of human skin using stem cells and marine microbiome adaptation to thermal changes. Why it matters: These diverse research projects highlight KAUST's contributions to computational biology, virology, and marine science, advancing knowledge with implications for healthcare and environmental challenges.

Generative Artificial Intelligence in RNA Biology

MBZUAI ·

Researchers at the Rosalind Franklin Institute are using generative AI, including GANs, to augment limited biological datasets, specifically mirtron data from mirtronDB. The synthetic data created mimics real-world samples, facilitating more comprehensive training of machine learning models, leading to improved mirtron identification tools. They also plan to apply Large Language Models (LLMs) to predict unknown patterns in sequence and structure biology problems. Why it matters: This research explores AI techniques to tackle data scarcity in biological research, potentially accelerating discoveries in noncoding RNA and transposable elements.

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.

Complex disease modeling and efficient drug discovery with large language models

MBZUAI ·

A KAUST alumnus presented research on using large language models for complex disease modeling and drug discovery. LLMs were trained on insurance claims of 123 million US people to model diseases and predict genetic parameters. Protein language models were developed to discover remote homologs and functional biomolecules, while RNA language models were used for RNA structure prediction and reverse design. Why it matters: This work highlights the potential of LLMs to accelerate computational biology research and drug development, with a KAUST connection.

Exploring bioinformatics

KAUST ·

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.

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.