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X-WR-CALNAME:Institute for Quantitative and Computational Biosciences
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X-WR-CALDESC:Events for Institute for Quantitative and Computational Biosciences
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DTSTART;TZID=America/Los_Angeles:20221202T140000
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DTSTAMP:20260517T051123
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SUMMARY:QCBio Research Seminar: Matthew Soldano\, Staff Research Associate for the Pellegrini Bioinformatic's Lab
DESCRIPTION:TITLE: “Predicting Biological Aging from Epigenetics.” \nABSTRACT: Epigenetics are a proven measure of cellular health. Therefore\, a field of research has emerged that utilizes epigenetics to measure\, treat\, and potentially reverse biological age in humans. Specifically\, DNA methylation\, responsible for cell differentiation and gene expression\, has the potential to be a barcode for measuring biological age. Current DNA methylation aging tests require blood and are trained to predict chronological aging. To address this\, we are developing a buccal swab DNA methylation test that measures fitness and general health. We utilize targeted bisulfite sequencing and are testing several machine learning techniques to generate a reliable test. \n\nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2022/11/video1371794408.mp4
URL:https://qcb.ucla.edu/event/qcbio-research-seminar-matthew-soldano-pellegrini-staff-research-associate-for-the-pellegrini-bioinformatics-lab/
LOCATION:ZOOM\, CA\, United States
CATEGORIES:Research Seminars
ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2022/11/Matthew-soldano.jpeg
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SUMMARY:QCBio Research Seminar: Jee Yun Han (Boutros)\, Graduate Student in Gene Regulation\, Epigenomics\, and Transcriptomics
DESCRIPTION:TITLE: “Comprehensive study of gene expression outliers and their regulation mechanisms in pan-cancer.” \nABSTRACT: Cancer is a disease characterized by remarkable heterogeneity. Gene expression varies drastically between tumours and within cells of a single. This variability can generate extreme outliers: transcripts that show atypically high gene expression in a small percentage of cancers. These outliers increase the molecular and phenotypic diversity between individuals\, contributing to tumour heterogeneity. However\, the previous research has been limited to a single cancer type or a single gene. To fill the gap of our understanding\, this study will identify the outliers from various cancer types using our novel statistical method and explore the biological functions of outliers. With integrated analysis with the clinical outcome\, it will show how outliers affect the progression of cancer. This study is expected to deepen our understanding of the impact of outliers on different cancers by dissecting their dysregulation and will allow us to identify a novel cancer driver and potential drug target.
URL:https://qcb.ucla.edu/event/qcbio-research-seminar-jee-yun-han-li-jj-graduate-student-in-gene-regulation-epigenomics-and-transcriptomics/
LOCATION:ZOOM\, CA\, United States
CATEGORIES:Research Seminars
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