Dr. Takashi Gojobori, a KAUST professor and expert in molecular evolution, received an honorary doctoral degree from National Cheng Kung University (NCKU) in Taiwan. The degree recognizes Gojobori's contributions to evolutionary genomics and molecular evolution. A KAUST delegation led by VP James A. Calvin attended the conferring ceremony. Why it matters: The recognition highlights KAUST's faculty quality and contributions to international research collaborations.
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.
NYU Professor Michael Purugganan presented at KAUST's 2014 Winter Enrichment Program (WEP 2014) on the origins of crop species. He discussed how genome sequencing is improving our understanding of crop evolution, using date fruits collected in Jeddah as an example. His research on rice showed that two varieties, japonica and indica, share a single common ancestor, contrary to previous assumptions. Why it matters: Understanding crop evolution can help adapt crops to changing environments, which is crucial for food security in regions like the Middle East.
Janet Kelso from the Max Planck Institute and Sudhir Kumar from Temple University discussed evolutionary biology in a KAUST Facebook Live interview. Kelso's research focuses on interactions between modern humans and Neanderthals, finding similarities in DNA and benefits for environmental adaptation. Kumar's work, highly cited, involves big data analyses in evolutionary biology. Why it matters: The interview highlights KAUST's engagement with international experts in bioinformatics and evolutionary biology, promoting interdisciplinary research and knowledge dissemination.
Shozo Yokoyama, a biology professor at Emory University specializing in color vision evolution, was interviewed by KAUST. Yokoyama's lab identified amino acids regulating red-green and UV vision in vertebrates. He emphasizes the importance of young scientists developing fresh perspectives on evolution and learning directly from animals. Why it matters: While not directly an AI story, the piece highlights KAUST's broader research focus and its investment in attracting and showcasing international scientific expertise, relevant to building a strong research ecosystem.
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.
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 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.