BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Institute for Quantitative and Computational Biosciences - ECPv6.16.3//NONSGML v1.0//EN CALSCALE:GREGORIAN METHOD:PUBLISH 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 REFRESH-INTERVAL;VALUE=DURATION:PT1H X-Robots-Tag:noindex X-PUBLISHED-TTL:PT1H BEGIN:VTIMEZONE TZID:America/Los_Angeles BEGIN:DAYLIGHT TZOFFSETFROM:-0800 TZOFFSETTO:-0700 TZNAME:PDT DTSTART:20200308T100000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0700 TZOFFSETTO:-0800 TZNAME:PST DTSTART:20201101T090000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0800 TZOFFSETTO:-0700 TZNAME:PDT DTSTART:20210314T100000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0700 TZOFFSETTO:-0800 TZNAME:PST DTSTART:20211107T090000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0800 TZOFFSETTO:-0700 TZNAME:PDT DTSTART:20220313T100000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0700 TZOFFSETTO:-0800 TZNAME:PST DTSTART:20221106T090000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0800 TZOFFSETTO:-0700 TZNAME:PDT DTSTART:20230312T100000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0700 TZOFFSETTO:-0800 TZNAME:PST DTSTART:20231105T090000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220525T113000 DTEND;TZID=America/Los_Angeles:20220525T120000 DTSTAMP:20260616T100639 CREATED:20220519T183319Z LAST-MODIFIED:20220601T233916Z UID:21718-1653478200-1653480000@qcb.ucla.edu SUMMARY:QCBio Research Seminar: Connor Razma (Hoffmann)\, BS/MS Student DESCRIPTION:TITLE: “Baseline MEthylation Patterns prior to flu vaccination.” \nABSTRACT: Influenza affects millions worldwide each year with responses varying from individual to individual. Influenza can be broken down into subtypes specifically H1N1\, H3N2\, Yamagata\, and Victoria. One way to measure the immune response to influenza is to measure a person’s antibody response to influenza. To measure how many antibodies are present in a sample\, a hemagglutination inhibition assay (HAI) is used. DNA methylation is an epigenetic mechanism used to regulate gene expression in cells. Its mechanism of action is the addition of a methyl group to cytosine at a cytosine-guanine pair. DNA methylation has been shown to change in response to stimuli such as viral or bacterial infections. DNA methylation can be measured by bisulfite sequencing\, specifically reduced representation bisulfite sequencing in our case. In this study\, data was taken from patients who had the flu vaccination. Their antibody data was measured using the HAI assay by the University of Georgia and their methylation data was measured using reduced representation bisulfite sequencing by the Pellegrini and Reed lab at UCLA. Using various statistical learning algorithms we were able to find methylated sites that were good predictors of vaccine response. Elastic net regression proved to be a particularly good predictor of vaccine response\, and after further analysis\, it was revealed that the best prediction happened with only a few significant sites. Some of these significant sites seem to be involved in regulating immune response and membrane function. Further work will be done to determine the prediction accuracy of these algorithms with just these sites. Ideally\, after this future work and other experiments\, these methylated sites can be used as biomarkers to indicate response to flu vaccination. \n\nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2022/05/Connor-Razma-edited.mp4 URL:https://qcb.ucla.edu/event/qcbio-research-seminar-connor-razma-hoffmann-undergraduate-bioinformatics-researcher/ LOCATION:ZOOM\, CA\, United States CATEGORIES:Research Seminars ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2022/05/281170460_1052299975682517_1062133480470997117_n-copy.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220518T123000 DTEND;TZID=America/Los_Angeles:20220518T130000 DTSTAMP:20260616T100639 CREATED:20220502T135810Z LAST-MODIFIED:20220519T173324Z UID:21633-1652877000-1652878800@qcb.ucla.edu SUMMARY:QCBio Research Seminar: Jackson Chin (Meyer)\, Graduate Student in Bioengineering DESCRIPTION:TITLE: “Tensor Factorization for Interpreting the Mechanisms of MRSA Persistence.” \nABSTRACT: \nMethicillin-resistant Staphylococcus aureus (MRSA) bacteria is an increasingly common and life-threatening infection. While some antibiotics resolve MRSA infections in vitro\, these same antibiotics often fail to clear an infection when used to treat patients\, suggesting that MRSA persistence is a confluence of both host and bacterial factors. While recent research has identified critical genetic and proteomic determinants of MRSA persistence\, the mechanisms that drive MRSA persistence are still poorly understood. Here\, to better understand these mechanisms\, we implement tensor-based factorization to integrate genetic and proteomic data collected from two cohorts of patients with MRSA infections. We find that our factorization process identifies patterns across biological modalities and is able to explain 75% of the variance observed in genetic and proteomic data with just 8 components. Additionally\, this data integration improves persistence prediction accuracy as prediction models trained on these integrated factors demonstrate accuracies as high as 80% over subsets of the cohorts. Interpretation of these components further reveals mechanisms that drive the infection response and highlight processes critical for MRSA persistence. Overall\, these results suggest that tensor-based factorization can identify the mechanisms underlying MRSA persistence across host factors and improve our ability to predict and understand MRSA persistence. \nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2022/05/Jackson-Chin-edited.mp4 URL:https://qcb.ucla.edu/event/qcbio-research-seminar-jackson-chin-meyer-graduate-student-in-bioengineering/ LOCATION:ZOOM\, CA\, United States CATEGORIES:Research Seminars ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2022/05/20201202_135158_headshot.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220518T120000 DTEND;TZID=America/Los_Angeles:20220518T123000 DTSTAMP:20260616T100639 CREATED:20220502T135343Z LAST-MODIFIED:20220519T170741Z UID:21628-1652875200-1652877000@qcb.ucla.edu SUMMARY:QCBio Research Seminar: Yue Wang (Chou)\, Postdoc\, Department of Computational Medicine DESCRIPTION:TITLE: “Stochastic Model and Optimization of SELEX.” \nABSTRACT: Systematic Evolution of Ligands by EXponential enrichment (SELEX) is a process to select the best aptamer sequence in a huge aptamer library that binds a specified target molecule with the highest affinity. There has been a deterministic model of SELEX\, and we develop a fully discrete stochastic model to obtain more accurate results when the mass action law does not hold. Specifically\, we find that the optimal SELEX protocol in the stochastic model differs from that predicted by the deterministic model. \nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2022/05/Yue-Wang-edited.mp4 URL:https://qcb.ucla.edu/event/qcbio-research-seminar-yue-wang-chou-postdoc-department-of-computational-medicine/ LOCATION:ZOOM\, CA\, United States CATEGORIES:Research Seminars ATTACH;FMTTYPE=image/png:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2022/05/Yue.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220511T123000 DTEND;TZID=America/Los_Angeles:20220511T130000 DTSTAMP:20260616T100639 CREATED:20220504T232818Z LAST-MODIFIED:20220512T161538Z UID:21658-1652272200-1652274000@qcb.ucla.edu SUMMARY:QCBio Research Seminar: Heather Zhou (Li JJ)\, Graduate Student in Statistics DESCRIPTION:TITLE: “PCA outperforms popular hidden variable inference methods for QTL mapping.” \nABSTRACT: Estimating and accounting for hidden variables is widely practiced as an important step in quantitative trait locus (QTL) analysis for improving the power of QTL identification. However\, few benchmark studies have been performed to evaluate the efficacy of the various methods developed for this purpose. Here we benchmark popular hidden variable inference methods including surrogate variable analysis (SVA)\, probabilistic estimation of expression residuals (PEER)\, and hidden covariates with prior (HCP) against principal component analysis (PCA)—a well-established dimension reduction and factor discovery method—via 362 synthetic and 110 real data sets. We show that PCA not only underlies the statistical methodology behind the popular methods but is also orders of magnitude faster\, better-performing\, and much easier to interpret and use. The preprint is available at https://www.biorxiv.org/content/10.1101/2022.03.09.483661v1. \nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2022/05/Heather-Zhou-edited.mp4 URL:https://qcb.ucla.edu/event/qcbio-research-seminar-heather-zhou-li-jj-graduate-student-in-statistics/ LOCATION:ZOOM\, CA\, United States CATEGORIES:Research Seminars ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2022/05/Heather-Zhou.jpeg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220511T120000 DTEND;TZID=America/Los_Angeles:20220511T123000 DTSTAMP:20260616T100639 CREATED:20220505T154246Z LAST-MODIFIED:20220512T161022Z UID:21666-1652270400-1652272200@qcb.ucla.edu SUMMARY:QCBio Research Seminar: Keunseok Park (Park)\, Grad Student\, Chemical and Bimolecular Engineering DESCRIPTION:TITLE: “G-Flux: a metabolic flux and free energy analysis software for interpreting 13C\, 2H\, 18O\, and 15N isotope tracing data.” \nABSTRACT: Metabolic fluxes offer insights into pathway utilization\, kinetics\, and thermodynamics. Stable isotope tracing and metabolic footprinting are widely used for inferring metabolic fluxes. However\, quantitative flux measurement across broad metabolism remains challenging due to our inability to convert multiple isotope distributions into fluxes and integrate exometabolomics data. Here we develop a software application\, G-Flux\, for computing metabolic fluxes by tracing 13C\, 2H\, 18O\, and 15N. Using the ratio of forward to backward fluxes\, G-Flux can compute reaction Gibbs free energies (ΔG). We use G-Flux to compute fluxes and ΔG in E. coli and mammalian cells. Using these results and G-Flux’s ability to simulate isotope labeling\, we find that [6-18O1]glucose is ideal for quantifying ΔG of glycolytic reactions and dual tracing of [U-13C6]glucose and [U-15N2]glutamine for quantifying fluxes and ΔG of transaminase and amino acid degradation. Thus\, G-Flux facilitates comprehensive metabolic flux and free energy analysis. \nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2022/05/Keunseok-Park-edited.mp4 URL:https://qcb.ucla.edu/event/qcbio-research-seminar-keunseok-park-park-grad-student-chemical-and-bimolecular-engineering/ LOCATION:ZOOM\, CA\, United States CATEGORIES:Research Seminars ATTACH;FMTTYPE=image/png:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2022/05/KEUNSEOK-PARK-PHOTO.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220412T000000 DTEND;TZID=America/Los_Angeles:20220414T000000 DTSTAMP:20260616T100639 CREATED:20220331T193754Z LAST-MODIFIED:20220331T193754Z UID:21560-1649721600-1649894400@qcb.ucla.edu SUMMARY:W28: Introduction to Phylogenetics DESCRIPTION:Phylogenetics – the reconstruction of the evolutionary history of a the variety of species known to us\, is among the most fundamental and traditional tasks in Biology. With the dramatic developments in molecuar biology and the exponential growth in annotated genetic sequences\, novel directions and goals have been developed in this seemingly stagnant field. Phylogenetic analysis is now an integral part not only in traditional areas like Evolution\, Zoology\, or Ecology\, but also in imunology\, medicine\, and other disciplines. \nIn this workshop\, I will review the scientific basis behind the various approaches in phylogenesis\, in particular statistical/quantitative approaches that became standard in any modern molecular biology research. A chapter dedicated to the COVID-19 pandemic will be included. URL:https://qcb.ucla.edu/event/w28-intro-to-phylogenetics/ LOCATION:529 Boyer Hall\, 611 Charles E Young Dr E\,\, Los Angeles\, CA\, 90095\, United States CATEGORIES:Workshops,Interactive Workshop ATTACH;FMTTYPE=image/png:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2020/02/1dNLbh0n_400x400.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220402T100000 DTEND;TZID=America/Los_Angeles:20220402T190000 DTSTAMP:20260616T100639 CREATED:20220225T190947Z LAST-MODIFIED:20220225T191456Z UID:21130-1648893600-1648926000@qcb.ucla.edu SUMMARY:11th Annual Southern California Systems Biology Symposium DESCRIPTION:https://socalsysbio.qcb.ucla.edu URL:https://qcb.ucla.edu/event/11th-annual-southern-california-systems-biology-symposium/ LOCATION:Geffen Hall\, 885 Tiverton Drive\, Los Angeles\, CA\, 90095\, United States CATEGORIES:Symposium ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2022/02/REGISTRATION-IS-OPEN-scaled.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220307T160000 DTEND;TZID=America/Los_Angeles:20220307T170000 DTSTAMP:20260616T100639 CREATED:20220103T174232Z LAST-MODIFIED:20220103T174232Z UID:20372-1646668800-1646672400@qcb.ucla.edu SUMMARY:Bioinformatics/Human Genetics Seminar Series: King Jordan\, PhD\, Professor and Director\, Bioinformatics Graduate Program DESCRIPTION:TITLE: “Genomics for precision public health in Colombia” \nHosted by Juan De La Hoz. URL:https://qcb.ucla.edu/event/bioinformatics-human-genetics-seminar-series-king-jordan-phd-professor-and-director-bioinformatics-graduate-program/ 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/14/2022/01/8.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220228T160000 DTEND;TZID=America/Los_Angeles:20220228T170000 DTSTAMP:20260616T100639 CREATED:20220103T174045Z LAST-MODIFIED:20220103T174045Z UID:20368-1646064000-1646067600@qcb.ucla.edu SUMMARY:Bioinformatics/Human Genetics Seminar Series: Jason Moore\, PhD\, Founding Chair of the Department of Computational Biomedicine\, Cedars-Sinai DESCRIPTION:TITLE: “Automated genetic analysis” \nHosted by Nandita Garud. URL:https://qcb.ucla.edu/event/bioinformatics-human-genetics-seminar-series-jason-moore-phd-founding-chair-of-the-department-of-computational-biomedicine-cedars-sinai/ 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/14/2022/01/7.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220223T123000 DTEND;TZID=America/Los_Angeles:20220223T130000 DTSTAMP:20260616T100639 CREATED:20211207T224209Z LAST-MODIFIED:20220214T212656Z UID:20099-1645619400-1645621200@qcb.ucla.edu SUMMARY:QCBio Research Seminar: Chenghao (Trevor) Zhu (Boutros)\, Postdoc in Human Genetics DESCRIPTION:TITLE: “moPepGen: a fast custom database generator from multi-omics data for proteogenomics.” \nABSTRACT: Cancers are driven by genomic variants such as SNV (single nucleotide variants) and INDEL\, often accompanied by many transcriptional variants. Modern mass spectrometry based proteomics is able to identify and quantify peptides and proteins comprehensively\, however the variant-harboring peptides that are absent in canonical databases are largely under-studied. A common problem in custom database construction is the large number of combinations of variants to consider. Thus major proteogenomic studies often choose a strategy that only captures peptides harboring a single variant. Existing algorithms also suffer from limited sources of variation. We developed moPepGen (multi-omics peptide database generator) that aims at accelerating proteogenomic researching by generating custom peptide database from variety of genomic and transcriptional variants. MoPepGen uses a graph-based algorithm that achieves a linear time complexity in integrating variants in contrast to the exponential complexity of exhaust searching. MoPepGen integrates variants from a variety of sources including SNV\, indel\, transcription fusion\, alternative splicing\, RNA editing\, and circRNA. It is able to generate peptides harboring any combinations of variants on the single peptide. MoPepGen is also highly extensible for other types of genomic and transcriptional variants. \n  URL:https://qcb.ucla.edu/event/qcbio-research-seminar-chenghao-trevor-zhu-boutros-postdoc/ LOCATION:ZOOM\, CA\, United States CATEGORIES:Research Seminars ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2021/12/Chenghao-Trevor-Zhu-scaled.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220223T120000 DTEND;TZID=America/Los_Angeles:20220223T123000 DTSTAMP:20260616T100639 CREATED:20211207T223900Z LAST-MODIFIED:20220223T222057Z UID:20094-1645617600-1645619400@qcb.ucla.edu SUMMARY:QCBio Research Seminar: Matthew Heffel (Luo)\, Graduate Student in Bioinformatics DESCRIPTION:TITLE: “Multimodal Single-Cell Epigenomic Sequencing of the Developing Human Cerebral Cortex.” \nABSTRACT: Single cell epigenomic technologies allow the measurement of unique molecular signatures within cells\, however cell type complexity remains highly enigmatic. Emerging methods have enabled multiple modalities of epigenomic sequencing to be gathered from the same cell. Single-nucleus methyl-3C sequencing (sn-m3C-seq) delivers the capacity to capture chromatin conformation and DNA methylation information of 5’-methylcytosines with single cell fidelity. Developing neurons accumulate significant DNA methylation at non-CG sites (mCH)\, adjust patterns of CG methylation (mCG)\, and endure rearrangements of chromatin domains. These patterns of mCH\, mCG\, and chromatin interactions are specific to neuronal subtypes. We collected prefrontal cortex samples from 13 individuals at several developmental time stamps divided into four major age groups\, second trimester (2T)\, third trimester (3T)\, infant\, and adult. Applying sn-m3C-seq to our data of >29\,000 cells we identify 27 adult cell types and their developmental trajectories from five 2T cell types. The methylation features allow for intricate\, deeply specific cell type annotations and while the 3C modality highlights less specific cell types\, it can pick up forward trajectory signals that methylation either does not or that resolve as a single heterogeneous cell type in methylation; We observe developing glial progenitor cells identified in 3C that cluster as radial glia in the methylation feature space alone. The temporal forward stepping of the 3C feature set further allows us to validate cell types in different sample age groups. The integration of single cell modalities in sn-m3C-seq allows for the highly robust cell type classification as well as strong downstream analysis of epigenetic divergences of developing cell lineages. \nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2021/12/Matthew-Heffel-edited.mp4\n  URL:https://qcb.ucla.edu/event/qcbio-research-seminar-matthew-heffel-luo-graduate-student-in-bioinformatics/ LOCATION:ZOOM\, CA\, United States CATEGORIES:Research Seminars ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2021/12/Matthew-Heffel.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220214T160000 DTEND;TZID=America/Los_Angeles:20220214T170000 DTSTAMP:20260616T100639 CREATED:20220103T173906Z LAST-MODIFIED:20220103T173906Z UID:20364-1644854400-1644858000@qcb.ucla.edu SUMMARY:Bioinformatics/Human Genetics Seminar Series: Leila Jamal\, PhD\, Genetic Counselor and Bioethicist\, Associate Director for Cancer Genomics\, National Cancer Institute and the Johns Hopkins Bloomberg School of Public Health DESCRIPTION:TITLE: “Walking the line between progress and paternalism in genetic counseling.” \nHosted by Christina Palmer. URL:https://qcb.ucla.edu/event/bioinformatics-human-genetics-seminar-series-leila-jamal-phd-genetic-counselor-and-bioethicist-associate-director-for-cancer-genomics-national-cancer-institute-and-the-johns-hopkins-bloomberg-sch/ 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/14/2022/01/6.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220209T123000 DTEND;TZID=America/Los_Angeles:20220209T130000 DTSTAMP:20260616T100639 CREATED:20211209T230759Z LAST-MODIFIED:20220209T224043Z UID:20138-1644409800-1644411600@qcb.ucla.edu SUMMARY:QCBio Research Seminar: Richard Law (Park)\, Graduate Student in Chemical and Biomolecular Engineering DESCRIPTION:TITLE: “Quantitative flux analysis reveals redistribution of glycolytic pathways in dynamic nutrient environments.” \nABSTRACT: Optimal operation of metabolic fluxes is critical for an organism to be evolutionarily competitive. Textbook glycolysis is a conserved pathway that optimally utilizes carbohydrates for growth. However\, it is unclear why some organisms simultaneously possess the parallel Entner-Doudoroff (ED) pathway\, which has a lower bioenergetic yield. By integrating stable isotope tracing\, mass spectrometry\, and mathematical modeling\, we measure fluxes of these pathways in near-real time. Here\, we identify the benefits of the ED pathway under transitory environments. We utilized these tools for flux analysis to study central carbon metabolism in dynamic nutrient conditions. Specifically\, we hypothesized that parallel pathways enable cells to rapidly upshift their overall glycolytic flux to benefit growth in response to sudden nutrient availability. Our studies revealed that parallel yet specialized pathways enable dynamic redistribution of metabolic fluxes that are linked to rapid changes in metabolism and broader biological phenotypes.\nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2021/12/Richard-Law-Edited.mp4 URL:https://qcb.ucla.edu/event/qcbio-research-seminar-richard-law-park-graduate-student-in-chemical-and-biomolecular-engineering/ LOCATION:ZOOM\, CA\, United States CATEGORIES:Research Seminars ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2021/12/Richard-Law-.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220209T120000 DTEND;TZID=America/Los_Angeles:20220209T123000 DTSTAMP:20260616T100639 CREATED:20211207T223237Z LAST-MODIFIED:20220209T224539Z UID:20086-1644408000-1644409800@qcb.ucla.edu SUMMARY:QCBio Research Seminar: Apeksha Singh (Hoffmann)\, Graduate Student in Biomathematics DESCRIPTION:TITLE: “Characterizing distinct cell states based on stimulus-response dynamics.” \nABSTRACT: Macrophages show remarkable functional pleiotropy that is dependent on microenvironmental context. Prior studies have characterized how polarizing cytokines alter epigenetic or signaling mechanisms\, but how they affect specific macrophage functions has not been characterized systematically. One hallmark function of macrophages is to mount immune-threat appropriate responses\, in part via the signaling dynamics of transcription factor NFκB. Here\, we measured single-cell nuclear NFκB trajectories in macrophages polarized into 6 states and stimulated with 8 different stimuli resulting in a vast dataset. Linear Discriminant Analysis revealed how NFκB signaling codons compose the immune threat level of stimuli\, placing polarization states along a linear continuum between the M1/M2 dichotomy. Machine learning classification revealed losses of stimulus distinguishability with polarization\, which reflect a switch from sentinel to effector functions. However\, the stimulus response dynamics and discrimination patterns did not fit the M1/M2 continuum. Instead\, our analysis suggests macrophage functional niches within a multi-dimensional polarization landscape.\nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2021/12/Apeksha-Singh-Edited.mp4 URL:https://qcb.ucla.edu/event/qcbio-research-seminar-apeksha-singh-hoffmann-graduate-student-in-biomathematics/ LOCATION:ZOOM\, CA\, United States CATEGORIES:Research Seminars ATTACH;FMTTYPE=image/png:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2021/12/Apeksha-Singh-1.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220208T090000 DTEND;TZID=America/Los_Angeles:20220211T120000 DTSTAMP:20260616T100639 CREATED:20210908T213711Z LAST-MODIFIED:20220103T224653Z UID:18781-1644310800-1644580800@qcb.ucla.edu SUMMARY:W10: Mathematical Modeling of Cell Signaling DESCRIPTION:Molecular biology has taught us a great deal about what is happening inside a cell\, that is that pathways can get very complicated and life is not just independent pathways but networks. Fortunately\, we can use computational tools to understand dynamics of complex networks. This workshop introduces the basic concepts of modeling cell signaling pathways. In this workshop we will describe signaling pathways and network motifs using mathematical equations and will be using MATLAB to solve and plot dynamical solutions. This workshop will cover zero-\, first-\, and second- order chemical reaction networks and their differential equations\, including how to solve them. We will explore simple signaling pathways like the MAP Kinase cascade and other simplified cascades. Finally\, this workshop will go over network motifs as they relate to signaling such as positive and negative feedback\, double positive and negative feedback\, and feedforward loops. This workshop will include many hands-on activities with MATLAB. URL:https://qcb.ucla.edu/event/w10-mathematical-modeling-of-cell-signaling/ LOCATION:529 Boyer Hall\, 611 Charles E Young Dr E\,\, Los Angeles\, CA\, 90095\, United States CATEGORIES:Workshops,Interactive Workshop ATTACH;FMTTYPE=image/png:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2020/02/1dNLbh0n_400x400.png ORGANIZER;CN="QCB Collaboratory":MAILTO:collaboratory@ucla.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220207T160000 DTEND;TZID=America/Los_Angeles:20220207T170000 DTSTAMP:20260616T100639 CREATED:20220103T173705Z LAST-MODIFIED:20220103T174530Z UID:20359-1644249600-1644253200@qcb.ucla.edu SUMMARY:Bioinformatics/Human Genetics Seminar Series: Dana Pe'er\, PhD\, Chair\, Computational and Systems Biology Program\, Sloan Kettering Institute DESCRIPTION:TITLE: “Cellular plasticity in Cancer.” \nHosted by Jason Ernst. URL:https://qcb.ucla.edu/event/bioinformatics-human-genetics-seminar-series-dana-peer-phd-chair-computational-and-systems-biology-program-sloan-kettering-institute/ 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/14/2022/01/5.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220202T120000 DTEND;TZID=America/Los_Angeles:20220202T123000 DTSTAMP:20260616T100639 CREATED:20211216T231745Z LAST-MODIFIED:20220202T224019Z UID:20174-1643803200-1643805000@qcb.ucla.edu SUMMARY:QCBio Research Seminar: Xinzhou Ge (Li JJ)\, Postdoc in Statistics DESCRIPTION:TITLE: “P-value-free solution to fix exaggerated false positives by popular differential expression methods.” \nABSTRACT: We report a surprising phenomenon that popular bioinformatics methods for identifying differentially expressed genes (DEG) between two conditions have unexpectedly high false discovery rates (FDRs) on large-sample-size RNA-seq datasets. Failed FDR control is likely due to the invalid p-values which rely on unrealistic assumptions. To address this issue\, we use a general statistical framework Clipper to control the FDR in DEG analysis without relying on p-values. \nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2021/12/Xinzhou-Ge-edited.mp4 URL:https://qcb.ucla.edu/event/qcbio-research-seminar-xinzhou-ge-li-jj-postdoc-in-statistics/ LOCATION:ZOOM\, CA\, United States CATEGORIES:Research Seminars ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2021/12/Xinzhou-Ge.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220131T160000 DTEND;TZID=America/Los_Angeles:20220131T170000 DTSTAMP:20260616T100639 CREATED:20220103T173410Z LAST-MODIFIED:20220118T170814Z UID:20355-1643644800-1643648400@qcb.ucla.edu SUMMARY:Bioinformatics/Human Genetics Seminar Series: Doc Edge\, PhD\, Assistant Professor\, Quantitative and Computational Biology\, USC DESCRIPTION:TITLE: “The new forensic genetics: ‘long-range’ search and genetic privacy.” \nHosted by Nandita Garud. URL:https://qcb.ucla.edu/event/bioinformatics-human-genetics-seminar-series-doc-edge-phd-assistant-professor-quantitative-and-computational-biology-usc/ LOCATION:ZOOM\, CA\, United States CATEGORIES:Research Seminars ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2022/01/4.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220124T160000 DTEND;TZID=America/Los_Angeles:20220124T170000 DTSTAMP:20260616T100639 CREATED:20220103T173144Z LAST-MODIFIED:20220118T170727Z UID:20350-1643040000-1643043600@qcb.ucla.edu SUMMARY:Bioinformatics/Human Genetics Seminar Series: Jennifer Wilson\, PhD\, Assistant Professor\, Bioengineering\, UCLA DESCRIPTION:TITLE: “Deriving network parameters for understanding drug effects.” \nHosted by Jason Ernst. URL:https://qcb.ucla.edu/event/bioinformatics-human-genetics-seminar-series-jennifer-wilson-phd-assistant-professor-bioengineering-ucla/ LOCATION:ZOOM\, CA\, United States CATEGORIES:Research Seminars ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2022/01/3.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220121T110000 DTEND;TZID=America/Los_Angeles:20220121T120000 DTSTAMP:20260616T100639 CREATED:20220112T152603Z LAST-MODIFIED:20220112T152708Z UID:20585-1642762800-1642766400@qcb.ucla.edu SUMMARY:CAPS/RISE Workshop: Copying with Stress DESCRIPTION: URL:https://qcb.ucla.edu/event/caps-rise-workshop/ LOCATION:ZOOM\, CA\, United States CATEGORIES:Workshops ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2022/01/CAPS-workshops-flyer-for-monitors-scaled.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220112T123000 DTEND;TZID=America/Los_Angeles:20220112T130000 DTSTAMP:20260616T100639 CREATED:20211202T150300Z LAST-MODIFIED:20220114T205155Z UID:20052-1641990600-1641992400@qcb.ucla.edu SUMMARY:QCBio Research Seminar: Dongyuan Song (Li JJ)\, Graduate Student in Bioinformatics DESCRIPTION:TITLE: “scDesign3: an all-in-one statistical framework that generates realistic single-cell omics data and infers cell heterogeneity structure.” \nABSTRACT: The generation of realistic synthetic data is essential for benchmarking numerous computation tools developed for single-cell omics data. Here we propose an all-in-one statistical framework that generates single-cell omics data from various cell heterogeneity structures\, including discrete cell types\, continuous cell trajectories\, and spatial cell locations. Our framework uses a unified probabilistic model with accessible likelihood. This probabilistic formulation is advantageous in that it enables a straightforward discernment of the heterogeneity structure that best fits a single-cell omics dataset\, by leveraging the statistical model selection principle. \nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2021/12/Dongyuan-Song-edited.mp4\n  URL:https://qcb.ucla.edu/event/qcbio-research-seminar-dongyuan-song-li-jj-graduate-student-in-bioinformatics/ LOCATION:ZOOM\, CA\, United States CATEGORIES:Research Seminars ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2021/12/DongyuanISMB2021.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220112T113000 DTEND;TZID=America/Los_Angeles:20220112T120000 DTSTAMP:20260616T100639 CREATED:20211209T201215Z LAST-MODIFIED:20220118T163732Z UID:20116-1641987000-1641988800@qcb.ucla.edu SUMMARY:QCBio Research Seminar: Evan Maltz (Wollman)\, Graduate Student in BMSB (Biochemistry\, Molecular and Structural Biology) DESCRIPTION:TITLE: “Phenotypic consequences of gene expression variability.” \nABSTRACT: The central dogma of biology proposes that information flows from genes to RNA to protein\, determining protein identity and abundance. Single cell transcriptome measurements provide ample information about RNA abundance in cells. While the expression of individual genes clearly matters for determining phenotype\, they do not work independently. How the information in RNA abundances is combined to determine cellular phenotype remains unclear. Here we address this question for a single cellular phenotype\, the dynamic Ca2+ signaling response to a ligand. Using an information theory approach\, we estimated the mutual information between the expression of subsets of 83 genes in the Ca2+ signaling network and the dynamic Ca2+ response in the same cell. We found a high degree of dependency that corresponds to 60% of Ca2+ signal entropy\, yet most genes have redundant information. Furthermore\, a relatively small group of genes preserve most of the dependency. Our results demonstrate a high degree of regulatory elasticity with small changes in RNA abundance informing an emergent cellular phenotype. \nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2021/12/Evan-Maltz-edited.mp4\n  \nVideos can also be viewed on the QCBio YouTube Channel URL:https://qcb.ucla.edu/event/qcbio-research-seminar-evan-maltz-wollman-graduate-student/ LOCATION:ZOOM\, CA\, United States CATEGORIES:Research Seminars ATTACH;FMTTYPE=image/png:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2021/12/Malt-Evan.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220110T160000 DTEND;TZID=America/Los_Angeles:20220110T170000 DTSTAMP:20260616T100639 CREATED:20220103T172801Z LAST-MODIFIED:20220103T174408Z UID:20345-1641830400-1641834000@qcb.ucla.edu SUMMARY:Bioinformatics/Human Genetics Seminar Series: Lauren McIntyre\, PhD\, Professor\, Molecular Genetics & Microbiology\, University of Florida DESCRIPTION:TITLE: “Climate change and maize response to pollutants: gene content\, expression and regulation.” \nHosted by Kirk Lohmueller. URL:https://qcb.ucla.edu/event/bioinformatics-human-genetics-seminar-series-lauren-mcintyre-phd-professor-molecular-genetics-microbiology-university-of-florida/ LOCATION:ZOOM\, CA\, United States CATEGORIES:Research Seminars ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2022/01/2.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220105T120000 DTEND;TZID=America/Los_Angeles:20220105T123000 DTSTAMP:20260616T100639 CREATED:20211209T225609Z LAST-MODIFIED:20220106T165920Z UID:20130-1641384000-1641385800@qcb.ucla.edu SUMMARY:QCBio Research Seminar: Jianxiao Yang (Suchard)\, Grad Student in Biomathematics DESCRIPTION:TITLE: “Massive parallelization of massive sample-size survival analysis.” \nABSTRACT: \nLarge-scale observational health databases are increasingly popular for conducting comparative effectiveness and safety studies of medical products. However\, increasing number of patients poses computational challenges when fitting survival regression models in such studies. In this paper\, we use graphics processing units (GPUs) to parallelize the computational bottlenecks of massive sample-size survival analyses. Specifically\, we develop and apply time andmemory efficient single-pass parallel scan algorithms for Cox proportional hazardsmodels and forward-backward parallel scan algorithms for Fine-Gray models for analysis with and without a competing risk using a cyclic coordinate descent optimization approach. We demonstrate that GPUs accelerate the computation of fitting these complex models in large databases by orders-of-magnitude as compared to traditional multi-core CPU parallelism. Our implementation enables efficient large-scale observational studies involving millions of patients and thousands of patient characteristics. \nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2021/12/Jianxiao-Yang-edited.mp4 URL:https://qcb.ucla.edu/event/qcbio-research-seminar-jianxiao-yang-suchard-grad-student-in-biomathematics/ LOCATION:ZOOM\, CA\, United States CATEGORIES:Research Seminars ATTACH;FMTTYPE=image/png:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2021/12/Jianxiao-Yang.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220105T113000 DTEND;TZID=America/Los_Angeles:20220105T120000 DTSTAMP:20260616T100639 CREATED:20211207T185642Z LAST-MODIFIED:20220106T165152Z UID:20078-1641382200-1641384000@qcb.ucla.edu SUMMARY:QCBio Research Seminar: Jee Yun Han (Boutros)\, Graduate Student in MBIDP (Molecular Biology Interdepartmental Doctoral Program) DESCRIPTION:TITLE: “Comprehensive study of gene expression outliers and their regulation mechanisms in pan-cancer.” \nABSTRACT: With the ultimate aim of improving the management of cancer\, many groups have studied the molecular characteristics of tumors. Typically\, the heterogeneity of cancer evolves rapidly to adapt to its microenvironment\, helping cancer evade selective pressures and progress. These various subclones result in resistance to anti-cancer therapies. The extreme dysregulation of some gene such as oncogene is a prominent feature of cancer that can play a critical role in cancer tumorigenesis and accelerating cancer evolution by providing cancer cells with a selective growth advantage. Further research is needed to understand cancer heterogeneity and the extreme gene dysregulation\, and these studies will enable us to solve many limitations and obstacles for the inhibition and effective treatment of cancer. In previous studies\, cancer outliers such as BCR-ABL and TMPRSS2-ERG were identified as cancer drivers or drug targets\, and those showed strong associations with clinical outcomes. The gene expression outliers of cancer are likely to be caused by the diverse genetic and epigenetic variation frequently occurred in cancer. Despite of the important pathological function of cancer outliers\, to date\, the researches related to outliers have been only limited to a single type of cancer or a single gene\, which is insufficient for characterizing them and comprehending their pathological roles in cancer. To fill the gap of our understanding regarding cancer outliers\, this proposal will identify the outliers from various cancer types using our novel statistical method and explore the biological functions of outliers in individual cancer\, figuring out the unique feature of each cancer. With integrated analysis of the clinical outcome data and the features of outliers within and across cancer types\, it will show how outliers affect the progression of cancer. Comparative analysis transcriptome and proteome data analysis will address whether RNA outliers can be propagated into the protein level\, prioritizing candidates. Furthermore\, the molecular mechanisms for outlier generation in terms of genetic and epigenetic variation will be investigated in cancer\, enabling us to understand the central pathways associated with extremely abnormal gene expression in individual cancers. The proposed study is expected to deepen our understanding of the impact of outliers on different cancers by dissecting their dysregulation\, and\, in turn\, will allow us to identify a novel cancer driver and potential drug target. \nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2021/12/Jee-Yun-Han-edited.mp4\n  URL:https://qcb.ucla.edu/event/qcbio-research-seminar-jee-yun-han-boutros-graduate-student-in-mbidp/ LOCATION:ZOOM\, CA\, United States CATEGORIES:Research Seminars ATTACH;FMTTYPE=image/png:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2021/12/JeeYun.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220103T160000 DTEND;TZID=America/Los_Angeles:20220103T170000 DTSTAMP:20260616T100639 CREATED:20220103T172107Z LAST-MODIFIED:20220103T174333Z UID:20336-1641225600-1641229200@qcb.ucla.edu SUMMARY:Bioinformatics/Human Genetics Seminar Series: Shantanu Joshi\, PhD\, Assistant Professor\, Neurology\, Brain Mapping Center\, UCLA DESCRIPTION:TITLE: “Aligning Shape Data from Brain Imaging: applications to fMRI time series\, diffusion tractography.” \nHosted by Jason Ernst. URL:https://qcb.ucla.edu/event/bioinformatics-human-genetics-seminar-series-shantanu-joshi-phd/ LOCATION:ZOOM\, CA\, United States CATEGORIES:Bioinformatics Weekly Seminar,Research Seminars ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2022/01/1.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20211129T110000 DTEND;TZID=America/Los_Angeles:20211129T120000 DTSTAMP:20260616T100639 CREATED:20210916T154748Z LAST-MODIFIED:20210916T154748Z UID:18855-1638183600-1638187200@qcb.ucla.edu SUMMARY:Bioinformatics/Human Genetics Seminar Series: Stephen Piccolo\, Associate Professor\, Biology\, Member of Simmons Center for Cancer Research\, Brigham Young University DESCRIPTION:TITLE: “TBD” \nHosted by Sarah Spendlove URL:https://qcb.ucla.edu/event/bioinformatics-human-genetics-seminar-series-stephen-piccolo-associate-professor-biology-member-of-simmons-center-for-cancer-research-brigham-young-university/ LOCATION:ZOOM\, CA\, United States CATEGORIES:Research Seminars ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2021/09/Piccolo.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20211122T110000 DTEND;TZID=America/Los_Angeles:20211122T120000 DTSTAMP:20260616T100639 CREATED:20210916T154109Z LAST-MODIFIED:20210916T154109Z UID:18851-1637578800-1637582400@qcb.ucla.edu SUMMARY:Bioinformatics/Human Genetics Seminar Series: Katie Peichel\, Head of the Division Evolutionary Ecology\, University of Bern DESCRIPTION:“The role of chromosome evolution in adaptation and speciation in stickleback fish” \nHosted by Kirk Lohmueller URL:https://qcb.ucla.edu/event/bioinformatics-human-genetics-seminar-series-katie-peichel-head-of-the-division-evolutionary-ecology-university-of-bern/ LOCATION:ZOOM\, CA\, United States CATEGORIES:Research Seminars ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2021/09/Peichel.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20211119T110000 DTEND;TZID=America/Los_Angeles:20211119T123000 DTSTAMP:20260616T100639 CREATED:20201023T193859Z LAST-MODIFIED:20211105T153339Z UID:14420-1637319600-1637325000@qcb.ucla.edu SUMMARY:W26: Careers in Biotechnology for Bachelor’s and Master’s students DESCRIPTION:The QCB Collaboratory presents the ‘Careers in Biotechnology for Bachelor’s and Master’s students ’ workshop. Moderated by our Director\, Dr. Matteo Pellegrini\, this workshop features former members of the QCB community who are now working professionally in private industry. During this workshop\, we will cover topics such as pathways for undergraduates and masters’ degree students who may be interested in careers in computational biology in general. Participants who enroll to this workshop will be ask to contribute a question for our panelist. \nThe Collaboratory\, a central component of the Institute for Quantitative & Computational Biosciences (QCB)\, brings together experimental and computational biologists for collaboration and skill development. By teaching workshops and providing expert consulting\, Collaboratory fellows have enabled hundreds of experimentalists that include contemporary genomic technologies in their research\, and make novel discoveries. URL:https://qcb.ucla.edu/event/w26-careers-in-computational-biology/ LOCATION:ZOOM\, CA\, United States ORGANIZER;CN="QCB Collaboratory":MAILTO:collaboratory@ucla.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20211117T130000 DTEND;TZID=America/Los_Angeles:20211117T133000 DTSTAMP:20260616T100639 CREATED:20210930T174023Z LAST-MODIFIED:20211117T223438Z UID:19185-1637154000-1637155800@qcb.ucla.edu SUMMARY:QCBio Research Seminar: Paheli Desai-Chowdhry (Savage)\, Grad student in Biomathematics DESCRIPTION:TITLE: “Asymmetric Branching Scale Factors as Features in Neuronal Cell-Type Classification” \nABSTRACT: Neurons are connected by complex branching processes – axons and dendrites – that process information for organisms to respond to their environment. Classifying neurons according to differences in structure or function is a fundamental piece of neuroscience. In previous work\, we constructed a biophysical theory that establishes a correspondence between neuron structure and function as mediated by principles such as time or power minimization\, using undetermined Lagrange multipliers to predict scaling ratios for axon and dendrite sizes across branching levels. Here\, we relax the assumption of symmetrical branching in the model to determine asymmetric branching powers that differ across different cell types due to functional tradeoffs. Furthermore\, we use scale factors related to asymmetric branching as features in machine learning classification to distinguish between different cell types. We find significant distinctions in the asymmetric scaling ratios between Purkinje cells and motoneurons. The performance of these classification methods gives us important insights into the correspondence between structure and function across different cell types. \nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2021/09/Paheli-Desai-Chowdhri.mp4 URL:https://qcb.ucla.edu/event/qcbio-research-seminar-paheli-desai-chowdhry-savage-grad-student-in-biomathematics/ 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/14/2021/09/Paheli-Desai-Chowdhry.jpg END:VEVENT END:VCALENDAR