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X-WR-CALNAME:Institute for Quantitative and Computational Biosciences
X-ORIGINAL-URL:https://qcb.ucla.edu
X-WR-CALDESC:Events for Institute for Quantitative and Computational Biosciences
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20221202T140000
DTEND;TZID=America/Los_Angeles:20221202T143000
DTSTAMP:20260517T043302
CREATED:20221108T002920Z
LAST-MODIFIED:20221203T003811Z
UID:22603-1669989600-1669991400@qcb.ucla.edu
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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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20221202T143000
DTEND;TZID=America/Los_Angeles:20221202T150000
DTSTAMP:20260517T043302
CREATED:20221108T004446Z
LAST-MODIFIED:20221108T142947Z
UID:22615-1669991400-1669993200@qcb.ucla.edu
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
ATTACH;FMTTYPE=image/png:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2022/11/JeeYun.png
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20221207T110000
DTEND;TZID=America/Los_Angeles:20221207T113000
DTSTAMP:20260517T043302
CREATED:20221109T215644Z
LAST-MODIFIED:20221202T183112Z
UID:22650-1670410800-1670412600@qcb.ucla.edu
SUMMARY:QCBio Research Seminar: Mark Xiang (Hoffmann)\, Graduate Student in Bioinformatics
DESCRIPTION:TITLE: “Heterogeneity in cell states: Is it important whether cell states are heritable or change rapidly?” \nABSTRACT: Cells of the same cell type show molecular and phenotypic heterogeneity. Is the particular cell state of a given cell heritable from one generation to the next?  Previous work in liver cancer cells indicates that the molecular network that controls cell death may change within hours\, but the data from B-cells shows that their cell state is durable and heritable.  In this project\, I address this question by formulating a model of B-cell-mediated antibody responses.  This model recapitulates the Darwinian selection process to produce high affinity antibodies against an antigen. I then test how heterogeneity in the cell states affects the antibody repertoire\, and then what the effect of heritability of those cell states might be. The preliminary results from model simulation will be presented and discussed.
URL:https://qcb.ucla.edu/event/qcbio-research-seminar-mark-xiang-hoffmann-graduate-student-in-bioinformatics/
LOCATION:Boyer Hall 159
CATEGORIES:Research Seminars
ATTACH;FMTTYPE=image/png:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2022/11/Mark_Xiang_Profile_Photo-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20221207T120000
DTEND;TZID=America/Los_Angeles:20221207T123000
DTSTAMP:20260517T043302
CREATED:20221108T003622Z
LAST-MODIFIED:20221207T211458Z
UID:22610-1670414400-1670416200@qcb.ucla.edu
SUMMARY:QCBio Research Seminar: Guanao Yan (Li JJ)\, Graduate Student in Statistics
DESCRIPTION:TITLE: “scReadSim: a single-cell RNA-seq and ATAC-seq read simulator.” \nABSTRACT: Rapid advances of single-cell RNA-seq and ATAC-seq technologies have propelled the development of many computational tools\, benchmarking of which demands realistic simulators. However\, few simulators can generate sequencing reads\, and none of the existing read simulators aim to mimic real cells\, hindering the benchmarking of low-level computational tools that process reads. To fill this gap\, we propose scReadSim\, a single-cell RNA-seq and ATAC-seq read simulator that generates synthetic cells which mimic real cells. Trained on real data\, scReadSim can generate synthetic data in FASTQ and BAM formats. By deploying scReadSim on sci-ATAC-seq and 10x Multiome (ATAC+RNA) data\, we show that the scReadSim synthetic data resemble real data at both read and count levels. Moreover\, as a flexible simulator\, scReadSim enables users to arbitrarily specify open chromatin regions for the synthetic scATAC-seq reads\, and is also capable of allowing varying the cell number and sequencing depths for the synthetic data. To illustrate the versatile usage of scReadSim\, we include two exemplar benchmark studies to show that scReadSim provides unique molecular identifier (UMI) counts for benchmarking scRNA-seq deduplication tools and can accommodate user-specified open chromatin regions (“ground truths”) to generate single-cell ATAC-seq data. Our benchmark applications of scReadSim show that cellranger is a preferred scRNA-seq deduplication tool\, and MACS3 achieves top performance in scATAC-seq peak calling. \nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2022/11/video1156562562.mp4
URL:https://qcb.ucla.edu/event/qcbio-research-seminar-guanao-yan-li-jj-graduate-student-in-statistics/
LOCATION:Boyer 159\, 611 Charles E. Young Dr. E.\, Los Angeles\, CA\, 90095\, United States
CATEGORIES:Research Seminars
ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2022/11/Guanao.jpeg
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20221215T130000
DTEND;TZID=America/Los_Angeles:20221215T133000
DTSTAMP:20260517T043302
CREATED:20221128T171205Z
LAST-MODIFIED:20221215T225915Z
UID:22840-1671109200-1671111000@qcb.ucla.edu
SUMMARY:QCBio Research Seminar: Roni Haas (Boutros)\, Postdoc in Human Genetics
DESCRIPTION:TITLE: “Proteogenomic characterization of the molecular determinants of prostate cancer radioresistance.” \nABSTRACT: Prostate Cancer (PC)\, the second most common cause of cancer death in men\, is frequently treated using radiotherapy with curative intent. Despite its effectiveness\, radiotherapy often results in aggressive PC relapse characterized by radioresistance. The diversity in therapeutic response to radiotherapy\, and the molecular processes underlining radioresistance are not fully understood. Here we integrated genomic\, transcriptomic\, and proteomic investigations to comprehensively characterize the molecular determinants of PC radioresistance. To model radioresistance\, we have created Conventional-Fractionation (CF) and Hypo-Fractionated (HF) isogenic radioresistant cells that represent different therapeutic regimens: the traditional CF radiotherapy with daily small radiation doses over weeks\, and the relatively new HF radiotherapy with high radiation doses across several single treatments. We discovered that CF radioresistant cells gained twice the number of somatic single-nucleotide variants than HF. Nevertheless\, the gained mutations\, irrespective of the treatment schedule\, converged on mutational signatures associated with mismatch DNA repair. CF radioresistant cells demonstrated strong and exclusive dysregulation of driver and hallmark-cancer genes in RNA abundance profiles. The differences in protein abundance display cell-fraction-dependent clusters\, foremost of which are elevated levels of DNA repair proteins in CF radioresistant cell nuclei. Collectively\, we observed a far more aggressive phenotype in CF radioresistant cells compared to HF. The clinical relevance of our top potential therapeutic targets was assessed using a cohort of 380 PC patients. Our study provides a platform for the development of therapies for radio-recurrent PC. Ongoing proteogenomic integration will help understand the relationships amongst radioresistance-associated changes at the DNA\, RNA\, and protein levels. \nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2022/11/Roni-Haas.mp4
URL:https://qcb.ucla.edu/event/qcbio-research-seminar-roni-haas-boutros-postdoc-in-human-genetics/
LOCATION:Boyer Hall 159
CATEGORIES:Research Seminars
ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2022/11/RoniHaas1-scaled.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20221215T133000
DTEND;TZID=America/Los_Angeles:20221215T140000
DTSTAMP:20260517T043302
CREATED:20221125T154144Z
LAST-MODIFIED:20221215T225950Z
UID:22826-1671111000-1671112800@qcb.ucla.edu
SUMMARY:QCBio Research Seminar: Zhiqian Zhai (Li JJ)\, Graduate Student in Statistics
DESCRIPTION:TITLE: “Supervised capacity preserving mapping: a clustering guided visualization method for scRNA-seq data.” \nABSTRACT: Recently\, various computational methods have been developed to analyze the scRNAseq data\, such as clustering and visualization. However\, current visualization methods\, including t-SNE and UMAP\, are challenged by the limited accuracy of rendering the geometric relationship of populations with distinct functional states. Most visualization methods are unsupervised\, leaving out information from the clustering results or given labels. This leads to the inaccurate depiction of the distances between the bona fide functional states. In particular\, UMAP and t-SNE are not optimal to preserve the global geometric structure. They may result in a contradiction that clusters with near distance in the embedded dimensions are in fact further away in the original dimensions. Besides\, UMAP and t-SNE cannot track the variance of clusters. Through the embedding of t-SNE and UMAP\, the variance of a cluster is not only associated with the true variance but also is proportional to the sample size. Here\, we present supCPM\, a robust supervised visualization method\, which separates different clusters\, preserves the global structure and tracks the cluster variance. \nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2022/11/Zhiqian-Zhai-edited.mp4\n 
URL:https://qcb.ucla.edu/event/qcbio-research-seminar-zhiqian-zhai-li-jj-graduate-student-in-statistics/
LOCATION:Boyer Hall 159
CATEGORIES:Research Seminars
ATTACH;FMTTYPE=image/png:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2022/11/Zhiqian-Zhai-picture.png
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