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Results for "Computational Bioscience Research Center"

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.

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.

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.

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.

Hacking the SARS-CoV-2 genome

KAUST ·

KAUST researchers are analyzing the SARS-CoV-2 genome to identify potential targets for treatment and vaccine development. They are using the KAUST Metagenome Analysis Platform (KMAP) and the university's supercomputer to compare and analyze genomic data. The research focuses on identifying key genes for detection and treatment of COVID-19. Why it matters: This research contributes to the global effort to combat the pandemic and highlights KAUST's capabilities in genomic data analysis and computational bioscience.

KAUST and KACST join forces to prevent infectious diseases

KAUST ·

KAUST's Computational Bioscience Research Center (CBRC) and King Abdulaziz City for Science and Technology (KACST) have collaborated on research into methicillin-resistant Staphylococcus aureus (MRSA) within Saudi Arabia, starting in July 2018. The two-year project aims to understand MRSA drug resistance mechanisms specific to the Kingdom and its regions, with the goal of developing public health strategies. The project involves sequencing samples and performing bioinformatics analysis to support a network of researchers in the country. Why it matters: This initiative enhances Saudi Arabia's capacity to predict, prevent, and control infectious diseases, aligning with national health objectives and building local expertise in computational bioscience.

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.

Using AI to understand the pathogenesis of COVID-19

KAUST ·

A KAUST Rapid Research Response Team (R3T) is collaborating with healthcare stakeholders to combat COVID-19. Xin Gao and his Structural and Functional Bioinformatics (SFB) Group are developing an AI-based diagnosis pipeline from CT scans of COVID-19 patients. The AI pipeline aims to address the high false negative rates associated with nucleic acid detection. Why it matters: This research could improve COVID-19 diagnostics and potentially inform understanding of viral pathogenesis.