Conveners
[ET] Innovative Data Centric Approaches to Biomedical Research with HPC: Innovative Data of KISTI
- Minjoong Jeong
Description
This session will showcase cutting-edge research in the fields of rare disease genetics, cancer biology, and bioinformatics. The first presentation will focus on deciphering complex structural variations in rare diseases, highlighting the use of advanced genomic techniques to identify disease-causing mutations. The second presentation will discuss the identification and validation of new drug target candidates for SOX2-associated squamous cell lung cancer, highlighting the potential for precision medicine in cancer treatment. The third presentation will explore the use of spatial omics to better understand the tumour microenvironment in uveal melanoma, revealing novel insights into tumour biology and potential therapeutic targets. The final presentation will introduce bio data research and analysis platforms in KISTI, showcasing their capabilities and real-world applications. Overall, this session will provide attendees with a comprehensive overview of innovative approaches to understanding disease and developing new treatments.
The clinical relevance of de novo structural variations (dnSVs) has become manifest, but dnSVs are often overlooked during routine genetic screening. To comprehensively assess their rate, characteristics, and clinical relevance, we analysed the whole-genome-sequencing data of 12,575 families with 13,703 probands with rare genetic diseases in the U.K. 100,000 Genomes Project. We identified...
The global outbreak of SARS-CoV-2 necessitates the rapid development of new therapies against COVID-19 infection. Here, we present the identification of 200 approved drugs, appropriate for repurposing against COVID-19. We constructed a SARS-CoV-2-induced protein (SIP) network, based on disease signatures defined by COVID-19 multi-omic datasets, and cross-examined these pathways against...
spatialUM proposes to generate valuable sequencing data in relatively neglected rare cancer and further develop methods that integrate spatial omics data with computer vision/AI and molecular analysis to identify targets for cancer using a combination of single cell RNA-seq (scRNA-seq) and spatial transcriptomics (STx) data. The project will be initially applied to a well-defined and...
The current R&D trends in the field of biotechnology are receiving attention for the use of artificial intelligence (AI). The government is promoting the digital transformation of the biotechnology industry through its Digital Bio-Innovation Strategy, with the aim of driving innovation in all industries based on the biotechnology industry. Efforts are being made to create and provide...
