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METHOD:PUBLISH
X-ORIGINAL-URL:https://qcb.ucla.edu
X-WR-CALDESC:Events for Institute for Quantitative and Computational Biosciences
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TZID:America/Los_Angeles
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DTSTART:20220313T100000
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20231103T130000
DTEND;TZID=America/Los_Angeles:20231103T133000
DTSTAMP:20231103T205708Z
CREATED:20231019T182813Z
LAST-MODIFIED:20231103T205708Z
UID:25904-1699016400-1699018200@qcb.ucla.edu
SUMMARY:Research-in-Progress (RIP) Seminar: Amantha O'Keeffe (Park)\, Graduate Student in Chemical and Biomolecular Engineering
DESCRIPTION:TITLE: “Quantification of Absolute Metabolite Concentrations in T cells by Shotgun Metabolomics.” \nABSTRACT: Quantitative understanding of immunometabolism underlies improving immune functions and developing successful immunotherapies. Kinetic and thermodynamic laws rely on absolute\, not relative\, metabolite concentrations to map metabolism. However\, until now\, comprehensive absolute metabolite quantification has been inaccessible due to the need for iterative analytical procedures involving internal standards. Here we developed a simple technique to facilitate absolute metabolite quantitation. Shotgun metabolomics leverages the known absolute metabolite concentrations of model systems and 13C labeling to distinguish metabolites from two different cell types in a single extraction sample. We cultured T cells in unlabeled media and E. coli or epithelial cells in 13C-labeled media and extracted their metabolites simultaneously. Using LC-MS and known concentrations of 13C-labeled metabolites as internal standards\, we quantified ~80 metabolites en masse in human T cells. \n\nhttps://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2023/10/Samantha-OKeeffe.mp4
URL:https://qcb.ucla.edu/event/research-in-progress-rip-seminar-amantha-okeeffe-park-graduate-student-in-chemical-and-biomolecular-engineering/
LOCATION:ZOOM\, CA\, United States
CATEGORIES:QCBio Seminar Series
ATTACH;FMTTYPE=image/jpeg:https://qcb.ucla.edu/wp-content/uploads/sites/14/2023/10/samantha.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20231103T133000
DTEND;TZID=America/Los_Angeles:20231103T140000
DTSTAMP:20231103T210314Z
CREATED:20231027T181948Z
LAST-MODIFIED:20231103T210314Z
UID:25967-1699018200-1699020000@qcb.ucla.edu
SUMMARY:Research-in-Progress (RIP) Seminar: Alexis Weber (de la Torre-Ubieta and Geschwind)\, Graduate Student in Human Genetics
DESCRIPTION:TITLE: “Defining molecular dysregulation in Down Syndrome neocortex and neural progenitor cells.” \nABSTRACT: Down syndrome (DS) is the most common form of genetic\, intellectual disability\, which occurs 1 in 700 newborns and presents in patients as cognitive deficits\, particularly diminished in learning\, memory\, and language development.1\,2\,3 DS symptoms result from impaired cortical development\, which is demonstrated\, in contrast to neurotypical (NTD) brains\, by postnatally reduced whole brain weight\, volume and surface area\, lower numbers of progenitors\, excitatory neurons and oligodendrocytes\, increased numbers of astrocytes\, interneurons and microglia\, and altered neuronal morphology\, maturation\, and migration.3–10 These DS neuropathologies result through some means from the triplication of human chromosome 21 (hsa21) or trisomy 21 (T21). However\, the way in which T21 confers DS pathology and inhibits cortical development remains unclear. I hypothesize that increased hsa21 gene dosage alters global gene expression in neural progenitors\, changing neural cell fate specification and differentiation. By single nuclei Multiome sequencing\, T21 neocortices demonstrate a disproportionate increase in progenitors\, interneurons and oligodendrocyte precursor cells and decrease in excitatory neurons\, contrast to neurotypical (NT) donors. Furthermore\, T21 neocortices show cell-specific differential expression of critical neurodevelopmental genes and transcription factors. These data support potential\, cell-specific mechanisms of gene dysregulation during T21 neurodevelopment. \nhttps://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2023/10/Alexis-Weber.mp4
URL:https://qcb.ucla.edu/event/research-in-progress-rip-seminar-alexis-weber-de-la-torre-ubieta-and-geschwind-graduate-student-in-human-genetics/
LOCATION:ZOOM\, CA\, United States
CATEGORIES:QCBio Seminar Series
ATTACH;FMTTYPE=image/png:https://qcb.ucla.edu/wp-content/uploads/sites/14/2023/10/Alexis-Weber.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20231106T120000
DTEND;TZID=America/Los_Angeles:20231106T130000
DTSTAMP:20231017T091610Z
CREATED:20231017T090714Z
LAST-MODIFIED:20231017T091610Z
UID:25837-1699272000-1699275600@qcb.ucla.edu
SUMMARY:Frontiers in Computational Biosciences Seminar Series: Monica Munoz-Torres\, PhD\, Associate Professor\, Department of Biomedical Informatics\, University of Arizona
DESCRIPTION:TITLE: “TBD” \nHosted by William Hsu for Medical Informatics
URL:https://qcb.ucla.edu/event/frontiers-in-computational-biosciences-seminar-series-monica-munoz-torres-phd-associate-professor-department-of-biomedical-informatics-university-of-arizona/
LOCATION:Boyer 159\, 611 Charles E. Young Dr. E.\, Los Angeles\, CA\, 90095\, United States
CATEGORIES:QCBio Seminar Series
ATTACH;FMTTYPE=image/png:https://qcb.ucla.edu/wp-content/uploads/sites/14/2023/10/Picture3.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20231108T130000
DTEND;TZID=America/Los_Angeles:20231108T133000
DTSTAMP:20231108T223740Z
CREATED:20231102T151931Z
LAST-MODIFIED:20231108T223740Z
UID:25982-1699448400-1699450200@qcb.ucla.edu
SUMMARY:Research-in-Progress (RIP) Seminar: Jonatan Hervoso (Xiao)\, Graduate Student in Bioinformatics
DESCRIPTION:TITLE: “Splicing-specific transcriptome-wide association uncovers novel genetic mechanisms for Schizophrenia.” \nABSTRACT: Recent studies have highlighted the essential role of RNA splicing\, a key mechanism of alternative RNA processing\, in establishing connections between genetic variations and disease. Genetic loci influencing RNA splicing variations show considerable influence on complex traits\, possibly surpassing those affecting total gene expression. Dysregulated RNA splicing has emerged as a major potential contributor to neurological and psychiatric disorders\, likely due to the exceptionally high prevalence of alternatively spliced genes in the human brain. Nevertheless\, establishing direct associations between genetically altered splicing and complex traits has remained an enduring challenge. We introduce Spliced-Transcriptome-Wide Associations (SpliTWAS) to integrate alternative splicing information with GWAS to pinpoint genes linked to traits through exon splicing events. We applied SpliTWAS to two schizophrenia (SCZ) RNA-seq datasets\, BrainGVEX and CommonMind (CMC)\, revealing 137 and 88 trait-associated exons (in 84 and 67 genes)\, respectively.  Enriched biological functions in the associated gene sets converged on neuronal function and development\, immune cell activation\, cellular transport\, which are highly relevant to SCZ. SpliTWAS variants impacted RNA-binding protein (RBP) binding sites\, revealing potential disruption of RNA-protein interactions affecting splicing. We extended the probabilistic fine-mapping method FOCUS to the exon level\, identifying putative causal 36 genes and 48 exons for SCZ. We highlight VPS45 and APOPT1\, where splicing of specific exons was associated with disease risk\, eluding detection by conventional gene expression analysis. Collectively\, this study supports the substantial role of alternative splicing in shaping the genetic basis of SCZ\, providing a valuable approach for future investigations in this area. \nhttps://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2023/11/Jonatan-Hervoso.mp4
URL:https://qcb.ucla.edu/event/research-in-progress-rip-seminar-jonatan-hervoso-xiao-graduate-student-in-bioinformatics/
LOCATION:ZOOM\, CA\, United States
CATEGORIES:QCBio Seminar Series
ATTACH;FMTTYPE=image/png:https://qcb.ucla.edu/wp-content/uploads/sites/14/2023/11/Hervoso.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20231108T133000
DTEND;TZID=America/Los_Angeles:20231108T140000
DTSTAMP:20231102T152047Z
CREATED:20231018T092214Z
LAST-MODIFIED:20231102T152047Z
UID:25889-1699450200-1699452000@qcb.ucla.edu
SUMMARY:Research-in-Progress (RIP) Seminar: Xiaolu Guo (Hoffmann)\, Postdoc in Microbiology\, Immunology & Molecular Genetics
DESCRIPTION:TITLE: “Modeling the heterogenous NFκB dynamics of single immune cells.” \nABSTRACT: Macrophages function as immune sentinel cells\, initiating appropriate and specialized immune responses to a great variety of pathogens.  The transcription factor NFκB controls macrophage gene expression responses\, and its temporal dynamics enable stimulus-specificity of these responses.  Using a fluorescent reporter mouse our laboratory recently generated large amounts of single-cell NFκB dynamic data and identified dynamic features\, termed ‘signaling codons’\, that convey information to the nucleus about stimulus identity and dose.  Here\, we aimed to recapitulate the stimulus-specific but highly cell-to-cell heterogeneous NFκB dynamics with a mathematical model of the signaling network.  The parameters that are subject to biological variation provide the potential to account for the heterogeneity in observed stimulus responses.  We estimated parameter distributions using the Stochastic Approximation Expectation Maximization (SAEM) approach and then fit the individual cell data using Bayesian maximum a posteriori (MAP) estimation.  Visual inspection revealed an excellent fit with the data.  To quantitatively evaluate the fitting performance\, we compared the experimental and predicted distributions of NFκB signaling codons.  Further\, we identified biochemical reactions that may account for the cellular heterogeneity in NFκB dynamics.  We verified that the stimulus-specificity of the virtual macrophage NFκB responses was consistent with their live-cell counterparts\, as assessed by mutual information and machine learning classification. Additionally\, the mathematical model allowed us extend experimental dose response studies\, revealing the doses that maximize information. Furthermore\, the virtual NFκB macrophages enabled the exploration of individual cell responses to different ligands. Leveraging this capability\, we made predictions regarding combinatorial ligands\, that were then experimentally tested. Discrepancies between the experimental results and model predictions led to the identification of a competition mechanism between CpG and PolyIC for endosome trafficking\, resulting in non-integrative responses behavior. Our results establish a mathematical modeling tool that may be used to study the molecular determinants of response specificity and dynamical coding in immune sentinel cells at the single cell level.
URL:https://qcb.ucla.edu/event/research-in-progress-rip-seminar-xiaolu-guo-hoffmann-postdoc-in-microbiology-immunology-molecular-genetics/
LOCATION:ZOOM\, CA\, United States
CATEGORIES:QCBio Seminar Series
ATTACH;FMTTYPE=image/png:https://qcb.ucla.edu/wp-content/uploads/sites/14/2023/10/Xiaolu.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20231108T160000
DTEND;TZID=America/Los_Angeles:20231108T170000
DTSTAMP:20231024T101808Z
CREATED:20231024T101808Z
LAST-MODIFIED:20231024T101808Z
UID:25927-1699459200-1699462800@qcb.ucla.edu
SUMMARY:Special Seminar: Sara Monaco\, Managing Editor\, European Molecular Biology Organization (EMBO)
DESCRIPTION:TITLE: “The new culture of preprint peer-review”
URL:https://qcb.ucla.edu/event/special-seminar-sara-monaco-managing-editor-european-molecular-biology-organization-embo/
LOCATION:Boyer Hall 130
CATEGORIES:QCBio Seminar Series
ATTACH;FMTTYPE=image/jpeg:https://qcb.ucla.edu/wp-content/uploads/sites/14/2023/10/Sara-Monico.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20231113T120000
DTEND;TZID=America/Los_Angeles:20231113T130000
DTSTAMP:20231017T091500Z
CREATED:20231017T091008Z
LAST-MODIFIED:20231017T091500Z
UID:25841-1699876800-1699880400@qcb.ucla.edu
SUMMARY:Frontiers in Computational Biosciences Seminar Series: Haiyuan Yu\, PhD\, Tisch University Professor\, Deparment of Computational Biology\, Cornell University
DESCRIPTION:TITLE: “TBD” \nHosted by Grace Xiao for Bioinformatics
URL:https://qcb.ucla.edu/event/frontiers-in-computational-biosciences-seminar-series-haiyuan-yu-phd-tisch-university-professor-deparment-of-computational-biology-cornell-university/
LOCATION:Boyer 159\, 611 Charles E. Young Dr. E.\, Los Angeles\, CA\, 90095\, United States
CATEGORIES:QCBio Seminar Series
ATTACH;FMTTYPE=image/png:https://qcb.ucla.edu/wp-content/uploads/sites/14/2023/10/Picture4.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20231117T130000
DTEND;TZID=America/Los_Angeles:20231117T133000
DTSTAMP:20231026T193016Z
CREATED:20231026T193016Z
LAST-MODIFIED:20231026T193016Z
UID:25962-1700226000-1700227800@qcb.ucla.edu
SUMMARY:Research-in-Progress (RIP) Seminar: Mao Tian (Boutros)\, Junior Bioinformatician in JCCC Cancer Data Science
DESCRIPTION:TITLE: “Characterization of Genomics Landscape and Natural History of Anaplastic Thyroid Cancer using High Depth WGS and Subclonal Reconstruction.” \nABSTRACT: Anaplastic thyroid cancer (ATC) is among the most lethal cancer types\, with a median survival rate of approximately 12 weeks. ATC is resistant to both chemo- and radiotherapy\, a characteristic attributed to its surrounding tissues and rapid progression. Although ATC is less common than other thyroid cancers\, such as papillary thyroid carcinoma (PTC) and differentiated thyroid carcinoma (DTC)\, it frequently co-occurs with both PTC and DTC. In this study\, we assembled a 108-sample cohort consisting of 46 ATC patients and 5 thyroid cancer cell lines. We conducted high-depth (x90) whole genome sequencing on ATC samples\, as well as on adjacent PTC or DTC tissues\, and included blood controls when available. Our analysis identified both germline and somatic variants in ATC\, revealing a moderate mutation burden compared to C-type tumors and a higher incidence of recurrent SNVs and CNVs than in PTC or DTC. Notably\, ATC samples exhibited more active mutational signatures\, such as SBS2 and SBS13\, than DTC or PTC samples. Additionally\, we employed subclonal reconstruction to model the natural history of ATC in relation to cooccurring DTC and PTC.
URL:https://qcb.ucla.edu/event/research-in-progress-rip-seminar-mao-tian-boutros-junior-bioinformatician-in-jccc-cancer-data-science/
LOCATION:ZOOM\, CA\, United States
CATEGORIES:QCBio Seminar Series
ATTACH;FMTTYPE=image/jpeg:https://qcb.ucla.edu/wp-content/uploads/sites/14/2023/10/MaoTian_Headshot_2019.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20231117T133000
DTEND;TZID=America/Los_Angeles:20231117T140000
DTSTAMP:20231118T002605Z
CREATED:20231107T155230Z
LAST-MODIFIED:20231118T002605Z
UID:25997-1700227800-1700229600@qcb.ucla.edu
SUMMARY:Research-in-Progress (RIP) Seminar: Michael Cheng (Yang)\, Graduate Student in Bioinformatics
DESCRIPTION:TITLE: “scGRNdb: A Cell Type Gene Regulatory Network Atlas for Human and Mouse.” \nABSTRACT: Gene regulatory networks (GRNs) elucidate the complex regulatory landscape in cells and tissues\, making them powerful tools for understanding mechanisms in disease pathophysiology and identifying therapeutic targets. The advent of single cell RNA-sequencing (scRNAseq) enables a more granular study of disease mechanisms using cell type-specific GRNs\, but most existing GRN methods are not optimized for scRNAseq and robust network resources are scarce. We recently developed SCING\, which improves GRN performance on scRNAseq and spatial transcriptomics data compared to existing methods. Here we present scGRNdb: a GRN atlas of 1\,000+ SCING GRNs for cell types across 12 human and mouse single cell data atlases. Functional annotation of these networks revealed subnetworks that recapitulate known cell type specific pathways and gene mechanisms for neurological and cardiovascular diseases. Furthermore\, we will host scGRNdb and GRN analysis tools on a public web server to facilitate single cell research and biomedical discovery. \nhttps://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2023/11/Michael-Cheng-111723.mp4
URL:https://qcb.ucla.edu/event/research-in-progress-rip-seminar-michael-cheng-yang-graduate-student-in-bioinformatics/
LOCATION:ZOOM\, CA\, United States
CATEGORIES:QCBio Seminar Series
ATTACH;FMTTYPE=image/jpeg:https://qcb.ucla.edu/wp-content/uploads/sites/14/2023/11/michaelcheng_headshot.jpeg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20231127T120000
DTEND;TZID=America/Los_Angeles:20231127T130000
DTSTAMP:20231017T091350Z
CREATED:20231017T091350Z
LAST-MODIFIED:20231017T091350Z
UID:25845-1701086400-1701090000@qcb.ucla.edu
SUMMARY:Frontiers in Computational Biosciences Seminar Series: Qunhua Li\, PhD\, Associate Professor\, Department of Statistics\, The Pennsylvania State University
DESCRIPTION:TITLE: “TBD” \nHosted by Jingyi Jessica Li for Bioinformatics
URL:https://qcb.ucla.edu/event/frontiers-in-computational-biosciences-seminar-series-qunhua-li-phd-associate-professor-department-of-statistics-the-pennsylvania-state-university/
LOCATION:Boyer 159\, 611 Charles E. Young Dr. E.\, Los Angeles\, CA\, 90095\, United States
CATEGORIES:QCBio Seminar Series
ATTACH;FMTTYPE=image/png:https://qcb.ucla.edu/wp-content/uploads/sites/14/2023/10/Picture5.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20231129T130000
DTEND;TZID=America/Los_Angeles:20231129T133000
DTSTAMP:20231130T153643Z
CREATED:20231113T160845Z
LAST-MODIFIED:20231130T153643Z
UID:26015-1701262800-1701264600@qcb.ucla.edu
SUMMARY:Research-in-Progress (RIP) Seminar: Matthew Soldano (Pellegrini)\, Staff Research Associate\, Institute for Genomics and Proteomics at DGSOM
DESCRIPTION:TITLE: “A Non-Invasive Epigenetic Measure of Inflammation.” \nABSTRACT: Existing epigenetic phenotype tests often lack mechanistic explanations of the observed correlations between specific methylation sites and phenotypes. This raises the crucial question: are these correlations primarily a result of marginal correlations\, or do they stem from plausible biological mechanisms? To delve deeper into this question\, we conducted a Targeted Epigenome Association Study focusing on CpG sites associated with aging\, metabolism\, and obesity. Our study leveraged a clinical investigation on fitness\, encompassing comprehensive measurements of phenotypes\, traditional biomarkers linked to metabolism\, obesity\, and fitness\, as well as extensive profiling of hundreds of metabolites and proteins. Additionally\, we had access to buccal swabs for targeted bisulfite sequencing. Our analysis discovered eight CpG sites exhibiting robust associations with the complement system\, alongside indicators of adiposity and epithelial cell ratio found in the buccal swab samples. These sites reside within the region of the peptidoglycan recognition 1 gene promoter\, a protein that senses inflammatory processes. This discovery sheds light on the intricate interplay between epigenetic markers with oral and systemic inflammation pathways.\nhttps://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2023/11/Matthew-Soldano.mp4
URL:https://qcb.ucla.edu/event/research-in-progress-rip-seminar-matthew-soldano-pellegrini-graduate-student-institute-for-genomics-and-proteomics-at-dgsom/
LOCATION:ZOOM\, CA\, United States
CATEGORIES:QCBio Seminar Series
ATTACH;FMTTYPE=image/jpeg:https://qcb.ucla.edu/wp-content/uploads/sites/14/2023/11/Matthew-Soldano.jpeg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20231129T133000
DTEND;TZID=America/Los_Angeles:20231129T140000
DTSTAMP:20231130T154218Z
CREATED:20231116T191717Z
LAST-MODIFIED:20231130T154218Z
UID:26027-1701264600-1701266400@qcb.ucla.edu
SUMMARY:Research-in-Progress (RIP) Seminar: Christy Lee (Li JJ)\, Graduate Student in Statistics and Data Science
DESCRIPTION:TITLE: “scDEED: a statistical method for detecting dubious 2D single-cell embeddings and optimizing t-SNE and UMAP hyperparameters.” \nABSTRACT: Two-dimensional (2D) embedding methods are crucial for single-cell data visualization. Popular methods such as t-distributed stochastic neighbor embedding(t-SNE) and uniform manifold approximation and projection (UMAP) are commonly used for visualizing cell clusters; however\, it is well known that t-SNE and UMAP’s 2D embedding might not reliably inform the similarities among cell clusters. Motivated by this challenge\, we present a statistical method\, scDEED\, for detecting dubious cell embeddings output by any 2D-embedding method. By calculating a reliability score for every cell embedding\, scDEED identifies the cell embeddings with low reliability scores as dubious and those with high reliability scores as trustworthy. Moreover\, by minimizing the number of dubious cell embeddings\, scDEED provides intuitive guidance for optimizing the hyperparameters of an embedding method.\nhttps://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2023/11/Christy-Lee.mp4
URL:https://qcb.ucla.edu/event/research-in-progress-rip-seminar-christy-lee-li-jj-graduate-student-in-statistics-and-data-science/
LOCATION:ZOOM\, CA\, United States
CATEGORIES:QCBio Seminar Series
ATTACH;FMTTYPE=image/png:https://qcb.ucla.edu/wp-content/uploads/sites/14/2023/11/Christy_Lee_profile.png
END:VEVENT
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