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X-ORIGINAL-URL:https://ds.dfci.harvard.edu
X-WR-CALDESC:Events for Dana-Farber Cancer Institute
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240110T120000
DTEND;TZID=America/New_York:20240110T130000
DTSTAMP:20260407T192144
CREATED:20240104T202615Z
LAST-MODIFIED:20240104T202615Z
UID:4773-1704888000-1704891600@ds.dfci.harvard.edu
SUMMARY:ImmunoPROFILE: An Multiplex Immunofluorescence Based Immune Cell Profiling Test and Data Resource; An Overview and Analysis Vignette Using GNNs
DESCRIPTION:Elevate @ Eleven: Comp Bio Connections \nWednesday January 10th\, 2023\n12:00-1:00PM\nIn-person only\, Zelen Commons\, 11th floor of the Center for Life Sciences Building \nKatharina Hoebel\, Research Fellow\, Department of Data Science\, Dana-Farber Cancer Institute\nJames Lindsay\, Director\, Software Engineer\, Department of Data Science\, Dana-Farber Cancer Institute \nLunch is provided.
URL:https://ds.dfci.harvard.edu/event/immunoprofile-an-multiplex-immunofluorescence-based-immune-cell-profiling-test-and-data-resource-an-overview-and-analysis-vignette-using-gnns/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2024/01/katharina_james2.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240116T130000
DTEND;TZID=America/New_York:20240116T140000
DTSTAMP:20260407T192144
CREATED:20230927T113715Z
LAST-MODIFIED:20240119T180817Z
UID:4572-1705410000-1705413600@ds.dfci.harvard.edu
SUMMARY:Methods for the Analysis of Data with Missing Values
DESCRIPTION:Frontiers in Biostatistics Seminar \nTuesday January 16\, 2023 @ 1pm ET\nCenter for Life Sciences Building\, Room 11081 \nRoderick Little\, PhD\nRichard D. Remington Distinguished University Professor of Biostatistics\nProfessor\, Department of Statistics\nResearch Professor\, Institute for Social Research\nUniversity of Michigan School of Public Health \nYouTube Video \nAbstract: I review methods for handling missing data in empirical studies. I define missing data\, provide a taxonomy of main approaches to analysis\, including complete-case and available-case analysis\, weighting\, maximum likelihood (ML)\, Bayes\, single and multiple imputation (MI)\, and augmented inverse-probability weighting (AIPW). Assumptions about the missingness mechanism are key to the performance of alternative methods; I define missingness mechanisms\, which play a key role in the performance of methods. Approaches to robust inference\, and to inference when the mechanism is potentially missing not at random\, are discussed. I’ll also discuss recent developments in the treatment of missing data in interventional studies\, as evidenced by the International Council for Harmonization E9 Addendum on estimands. \nWant to get our weekly events newsletter? Click here!
URL:https://ds.dfci.harvard.edu/event/frontiers-in-biostatistics-seminar-roderick-little/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2023/09/rlittle_crop.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240124T120000
DTEND;TZID=America/New_York:20240124T130000
DTSTAMP:20260407T192144
CREATED:20240111T154411Z
LAST-MODIFIED:20240201T125325Z
UID:4827-1706097600-1706101200@ds.dfci.harvard.edu
SUMMARY:Tracing the Mutational Footprints of Cancer to Guide Personalized Therapy
DESCRIPTION:Elevate @ Eleven: Comp Bio Connections \nWednesday January 24th\, 2023\n12:00-1:00PM\nIn-person only\, Zelen Commons\, 11th floor of the Center for Life Sciences Building \nDoğa Gülhan\, Principal Investigator\, Mass General Cancer Center\, KF-CCR \nLunch is provided.
URL:https://ds.dfci.harvard.edu/event/tracing-the-mutational-footprints-of-cancer-to-guide-personalized-therapy/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2024/01/gulhan-square.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240206T130000
DTEND;TZID=America/New_York:20240206T140000
DTSTAMP:20260407T192144
CREATED:20240126T132133Z
LAST-MODIFIED:20240209T201454Z
UID:4874-1707224400-1707228000@ds.dfci.harvard.edu
SUMMARY:Quantitative Methods in Implementation Research: Concepts\, Goals\, and Applications
DESCRIPTION:Frontiers in Biostatistics Seminar \nTuesday February 6\, 2024 @ 1pm ET\nCenter for Life Sciences Building\, Room 11081 \nYou Tube Link \nDonna Spiegelman\, ScD\nSusan Dwight Bliss Professor of Biostatistics and Professor of Cardiovascular Medicine\, Yale School of Medicine Professor\, Department of Statistics and Data Science\, Yale University \nThis talk will provide an overview of the key concepts and goals of quantitative methods that are popular in implementation research\, with a wide range of real-world applications. Randomized\, quasi-experimental and observational designs will be covered.
URL:https://ds.dfci.harvard.edu/event/frontiers-in-biostatistics-donna-spiegelman/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2024/01/spiegelman-crop.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240207T120000
DTEND;TZID=America/New_York:20240207T130000
DTSTAMP:20260407T192144
CREATED:20240129T134117Z
LAST-MODIFIED:20240209T142125Z
UID:4891-1707307200-1707310800@ds.dfci.harvard.edu
SUMMARY:Reconstructing the Chronology of Somatic Events From Precursor Conditions to Advanced Stage Myeloma
DESCRIPTION:Elevate @ Eleven: Comp Bio Connections \nWednesday February 7th\, 2024\n12:00-1:00PM\nIn-person only\, Zelen Commons\, 11th floor of the Center for Life Sciences Building \nMehmet Samur\, Senior Research Scientist\, Department of Data Science \nLunch is provided.
URL:https://ds.dfci.harvard.edu/event/reconstructing-the-chronology-of-somatic-events-from-precursor-conditions-to-advanced-stage-myeloma/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2020/04/samur_mehmet.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20240301
DTEND;VALUE=DATE:20240302
DTSTAMP:20260407T192144
CREATED:20240209T142504Z
LAST-MODIFIED:20240304T124147Z
UID:4928-1709251200-1709337599@ds.dfci.harvard.edu
SUMMARY:Call for Abstracts: Health Disparities and Cancer
DESCRIPTION:We invite students\, postdocs\, residents\, clinical fellows\, and early career faculty to submit abstracts for consideration as a lightning talk at the 2024 Marvin Zelen Memorial Symposium. Submit via this form by Friday March 1st\, speakers will be notified by Friday March 8th. \n  \nFriday April 5\, 2024\n1:00-5:30PM ET \nYawkey Conference Center\n450 Brookline Ave\, Boston\, MA \nRegistration for in person and virtual attendance. \nInvited speakers: \n\nAdewole Adamson\, MD\, MPP\, Dell Medical School at the University of Texas at Austin\nCynthia Dwork\,PhD\, Harvard University\nNate Fillmore\,PhD\, VA Boston Healthcare System and Harvard Medical School\nCarmen E. Guerra\, MD\, MSCE\, University of Pennsylvania\nJinani Jayasekera\, PhD\, National Institute on Minority Health and Health Disparities\nBogdan Pasaniuc\,PhD\, University of California Los Angeles\n\n 
URL:https://ds.dfci.harvard.edu/event/call-for-abstracts-health-disparities-and-cancer/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2024/02/Zelen2024_forwebsite_image.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240312T130000
DTEND;TZID=America/New_York:20240312T140000
DTSTAMP:20260407T192144
CREATED:20240104T203211Z
LAST-MODIFIED:20240311T185258Z
UID:4778-1710248400-1710252000@ds.dfci.harvard.edu
SUMMARY:Frontiers in Biostatistics: A Framework for Personalizing the Timing of Surveillance Testing
DESCRIPTION:**This seminar has been canceled. A new date will be announced shortly**\nFrontiers in Biostatistics Seminar \nTuesday March 12\, 2024 @ 1pm ET \n  \nAasthaa Bansal\, PhD\nAssociate Professor\, The Comparative Health Outcomes\, Policy\, and Economics (CHOICE) Institute\, University of Washington\nJoint Associate Professor\, Public Health Sciences Division\nJoint Associate Professor\, Hutchinson Institute for Cancer Outcomes Research (HICOR)\nFred Hutch Cancer Center \nAbstract: Frequent surveillance testing using biomarkers is recommended and routinely conducted in several disease settings. Although surveillance tests provide information about current disease status and present an opportunity to detect disease progression early\, the complications and costs of frequent tests may not be justified for patients who are at low risk of progression. I will discuss our recently developed Personalized Risk-Adaptive Surveillance (PRAISE) framework\, a method for embedding dynamic predictions into a sequential decision-making framework to determine the time point at which the next collection of biomarker data would be most valuable. I will demonstrate a preliminary application of the framework in cystic fibrosis and ongoing work in colorectal cancer to develop more cost-effective and personalized surveillance strategies.
URL:https://ds.dfci.harvard.edu/event/frontiers-in-biostatistics-aasthaa-bansal/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2024/01/aasthaa_headshot_square-scaled-e1708014759804.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240411T160000
DTEND;TZID=America/New_York:20240411T170000
DTSTAMP:20260407T192144
CREATED:20240311T124600Z
LAST-MODIFIED:20240415T133053Z
UID:5053-1712851200-1712854800@ds.dfci.harvard.edu
SUMMARY:Data Integration in Statistical Inference and Risk Prediction
DESCRIPTION:Joint Seminar with Harvard TH Chan School of Public Health \nThursday April 11\, 2024 @ 4pm ET\nFXB Building Room 301 \nYu Shen PhD\nConversation with a Living Legend Professor & Chair ad interim\nDepartment of Biostatistics\nThe University of Texas MD Anderson Cancer Center \nIn comparative effectiveness research and risk prediction for rare types of cancer\, it is desirable to combine multiple sources of data\, e.g.\, the primary cohort data together with aggregate information derived from cancer registry databases. Such integration of data may improve statistical efficiency and accuracy of risk prediction\, but also pose statistical challenges for incomparability between different sources of data. We develop the adaptive estimation procedures\, which used the combined information to determine the degree of information borrowing from the aggregate data of the external resource. We apply the proposed methods to evaluate the long-term effect of several commonly used treatments for inflammatory breast cancer by tumor subtypes\, while combining the inflammatory breast cancer patient cohort at MD Anderson and external data.
URL:https://ds.dfci.harvard.edu/event/data-integration-in-statistical-inference-and-risk-prediction/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2024/03/yushen-crop.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240417T120000
DTEND;TZID=America/New_York:20240417T130000
DTSTAMP:20260407T192144
CREATED:20240415T133033Z
LAST-MODIFIED:20240423T144756Z
UID:5314-1713355200-1713358800@ds.dfci.harvard.edu
SUMMARY:Deconvolving Clonotype from High-Throughput Perturb-Seq and Novel Splice Identification of Prematurely Terminated mRNA
DESCRIPTION:Elevate @ Eleven CompBio Connections \nWednesday April 17th\, 2024\n12:00 – 1:00 PM\nZelen Commons\, Center for Life Sciences Building \nJared Brown\, PhD\, Research Fellow\, Data Science \n  \nLunch is provided.
URL:https://ds.dfci.harvard.edu/event/deconvolving-clonotype-from-high-throughput-perturb-seq-and-novel-splice-identification-of-prematurely-terminated-mrna/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2021/08/Brown_Jared.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240501T120000
DTEND;TZID=America/New_York:20240501T130000
DTSTAMP:20260407T192144
CREATED:20240415T145532Z
LAST-MODIFIED:20240502T125348Z
UID:5322-1714564800-1714568400@ds.dfci.harvard.edu
SUMMARY:Identifying Transcription Factor Binding using Open Chromatin\, Transcriptome\, and Methylation Data
DESCRIPTION:Elevate @ Eleven CompBio Connections \nWednesday May 1st\, 2024\n12:00 – 1:00 PM\nZelen Commons\, Center for Life Sciences Building \nMichael Hoffman\, PhD\, Senior Scientist and Chair\, Princess Margaret Cancer Centre and Associate Professor\, University of Toronto \nLunch is provided.
URL:https://ds.dfci.harvard.edu/event/identifying-transcription-factor-binding-using-open-chromatin-transcriptome-and-methylation-data/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2024/04/Hoffman_IMG_3344-cropped-1024x1024-1-e1713192907447.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240507T130000
DTEND;TZID=America/New_York:20240507T140000
DTSTAMP:20260407T192144
CREATED:20240304T124913Z
LAST-MODIFIED:20240507T191511Z
UID:5006-1715086800-1715090400@ds.dfci.harvard.edu
SUMMARY:Cancer Risk Prediction\, Early Detection and Minimal Residual Disease
DESCRIPTION:Frontiers in Biostatistics Seminar \nTuesday May 7\, 2024 @ 1pm ET \nIn-person and Zoom available. \nCristian Tomasetti\, Ph.D.\nDirector\, Center for Cancer Prevention and Early Detection\, City of Hope\nProfessor and Director\, Division of Mathematics for Cancer Evolution and Early Detection\, Department of Computational & Quantitative Medicine\, City of Hope
URL:https://ds.dfci.harvard.edu/event/frontiers-in-biostatistics-cristian-tomasetti/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2024/03/tomasetti-300x300-1-e1709556955216.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240813T130000
DTEND;TZID=America/New_York:20240813T140000
DTSTAMP:20260407T192144
CREATED:20240806T113832Z
LAST-MODIFIED:20240815T144154Z
UID:5477-1723554000-1723557600@ds.dfci.harvard.edu
SUMMARY:Challenges of Producing High-Quality Labelled Data
DESCRIPTION:Tuesday\, August 13 @ 1:00PM Eastern Time\nCenter for Life Sciences Building\, 11th floor\, room 11081\n3 Blackfan Circle\, Boston \nPeter Lipman\nTechnical Lead & Manager\nData Science & Human Computation\, Google \nZoom: https://bit.ly/plipman
URL:https://ds.dfci.harvard.edu/event/challenges-of-producing-high-quality-labelled-data/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2024/08/lipman_headshot_crop.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240830T080000
DTEND;TZID=America/New_York:20240830T170000
DTSTAMP:20260407T192144
CREATED:20240729T122857Z
LAST-MODIFIED:20240904T112937Z
UID:5455-1725004800-1725037200@ds.dfci.harvard.edu
SUMMARY:Fall schedule to be announced
DESCRIPTION:Watch here for updates on our fall seminar schedule. You can also sign up for our weekly newsletter to stay informed of data science events in the Boston area.
URL:https://ds.dfci.harvard.edu/event/fall-schedule-to-be-announced/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/svg+xml:https://ds.dfci.harvard.edu/wp-content/uploads/2021/02/dfds_logo.svg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240912T160000
DTEND;TZID=America/New_York:20240912T170000
DTSTAMP:20260407T192144
CREATED:20240904T112923Z
LAST-MODIFIED:20240917T172028Z
UID:5503-1726156800-1726160400@ds.dfci.harvard.edu
SUMMARY:Hierarchical Causal Models
DESCRIPTION:HSPH Biostatistics and DFCI Data Science Colloquium Series \nThursday September 12\, 2024\n4:00-5:00PM\nHSPH FXB Building Room 301 \nDavid Blei\, PhD\nProfessor of Statistics and Computer Science\nColumbia University \nAnalyzing nested data with hierarchical models is a staple of Bayesian statistics\, but causal modeling remains largely focused on “flat” models. In this talk\, we will explore how to think about nested data in causal models\, and we will consider the advantages of nested data over aggregate data (such as data means) for causal inference. We show that disaggregating your data—replacing a flat causal model with a hierarchical causal model—can provide new opportunities for identification and estimation. \nAs examples\, we will study how to identify and estimate causal effects under unmeasured confounders\, interference\, and instruments. \nThis is joint work with Eli Weinstein.
URL:https://ds.dfci.harvard.edu/event/hierarchical-causal-models/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2024/09/blei_headshot_crop.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240919T160000
DTEND;TZID=America/New_York:20240919T170000
DTSTAMP:20260407T192144
CREATED:20240917T172017Z
LAST-MODIFIED:20240920T175443Z
UID:5541-1726761600-1726765200@ds.dfci.harvard.edu
SUMMARY:Inference for Treatment-Specific Survival Curves using Machine Learning
DESCRIPTION:HSPH Biostatistics and DFCI Data Science Colloquium Series \nThursday September 19\, 2024\n4:00-5:00PM\nHSPH FXB Building Room 313 \nTed Westling\, Assistant Professor\, Department of Mathematics & Statistics\, University of Massachusetts Amherst \nIn the absence of data from a randomized trial\, researchers often aim to use observational data to draw causal inference about the effect of a treatment on a time-to-event outcome. In this context\, interest often focuses on the treatment-specific survival curves; that is\, the survival curves were the entire population under study to be assigned to receive the treatment or not. Under certain causal conditions\, including that all confounders of the treatment-outcome relationship are observed\, the treatment-specific survival can be identified with a covariate-adjusted survival function. Several estimators of this function have been proposed\, including estimators based on outcome regression\, inverse probability weighting\, and doubly robust estimators. We propose a cross-fitted doubly-robust estimator that incorporates data-adaptive estimators of the conditional survival functions. We establish conditions on the nuisance estimators under which our estimator is consistent and asymptotically linear\, both pointwise and uniformly in time. We also propose an ensemble learner for combining multiple candidate estimators of the conditional survival estimators. Our methods and results accommodate events occurring in discrete or continuous time (or both). We investigate the practical performance of our methods using an application to the effect of a surgical treatment to prevent metastases of parotid carcinoma on mortality. Time permitting\, we will discuss ongoing work concerning sensitivity analysis for survival curves.
URL:https://ds.dfci.harvard.edu/event/inference-for-treatment-specific-survival-curves-using-machine-learning/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2024/09/Ted-Westling-long.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241018T150000
DTEND;TZID=America/New_York:20241018T160000
DTSTAMP:20260407T192144
CREATED:20241008T113529Z
LAST-MODIFIED:20241022T164100Z
UID:5585-1729263600-1729267200@ds.dfci.harvard.edu
SUMMARY:Empirical Bayes Matrix Factorization\, and Genomic Applications
DESCRIPTION:Data Science Seminar\nFriday\, October 18\, 3:00 PM ET \nCenter for Life Sciences Building\, 11th Floor \nMatthew Stephens\, PhD\nChair\, Department of Statistics; Ralph W. Gerard Professor of Statistics\, Human Genetics\, University of Chicago
URL:https://ds.dfci.harvard.edu/event/empirical-bayes-matrix-factorization-and-genomic-applications/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2024/10/Stephens_Matthew_600x600-300x300-1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241023T120000
DTEND;TZID=America/New_York:20241023T130000
DTSTAMP:20260407T192144
CREATED:20241011T180746Z
LAST-MODIFIED:20241023T172801Z
UID:5608-1729684800-1729688400@ds.dfci.harvard.edu
SUMMARY:Targeting CARM1 in Dendritic Cells for Cancer Immunotherapy
DESCRIPTION:Compbio Connections\n\nOctober 23rd\, 12:00 -1:00 PM ET\nCenter for Life Sciences Building\, 11th floor\, Zelen Commons \nXixi Zhang\, PhD\nResearch Fellow\, Dana-Farber Cancer Institute \nLunch is provided.
URL:https://ds.dfci.harvard.edu/event/targeting-carm1-in-dendritic-cells-for-cancer-immunotherapy/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2024/10/Zhang_Xixi_headshot.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241106T120000
DTEND;TZID=America/New_York:20241106T130000
DTSTAMP:20260407T192144
CREATED:20241029T141932Z
LAST-MODIFIED:20241029T141932Z
UID:5644-1730894400-1730898000@ds.dfci.harvard.edu
SUMMARY:Harnessing Bioinformatics for Cancer Research at DFCI
DESCRIPTION:Compbio Connections\n\nNovember 6\, 12:00 -1:00 PM ET\nCenter for Life Sciences Building\, 11th floor\, Zelen Commons \n\n\n\n\nMichael Tolstorukov\nDirector\, Bioinformatics and Molecular Data\, Informatics and Analytics\, Dana-Farber Cancer Institute \n\n\n\n\nLunch is provided.
URL:https://ds.dfci.harvard.edu/event/harnessing-bioinformatics-for-cancer-research-at-dfci/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2024/10/T_Michael_headshot-e1730211557553.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241107T100000
DTEND;TZID=America/New_York:20241107T120000
DTSTAMP:20260407T192144
CREATED:20241023T164140Z
LAST-MODIFIED:20241023T164140Z
UID:5634-1730973600-1730980800@ds.dfci.harvard.edu
SUMMARY:Ligand Receptor Analysis in a Spatial Context
DESCRIPTION:The Harvard Chan Bioinformatics Core in partnership with The Cancer Data Sciences Program at DF/HCC are very excited to present the Fall seminar series: \nNovel Applications in Single Cell Omics \n\n\n\nLigand receptor analysis in a spatial context \nNovember 7th\nSizun Jiang\, PhD\nBeth Israel Deaconess Medical Center Harvard Medical School \nMartin Hemberg\, PhD and Jingyi Cao\, PhD Brigham and Women’s Hospital\nHarvard Medical School \nTrajectory inference in single cell data\nNovember 21st\nLuca Pinello\, PhD and Cameron Ray Smith\, MD\, PhD\nMassachusetts General Hospital \nSpatial transcriptomics deconvolution analysis\nDecember 5th\nKevin Wei\, MD\, PhD Brigham and Women’s Hospital\nRuben Dries\, PhD and George Chen Boston University School of Medicine \nAll seminar sessions are hybrid events being held from 10am to noon.\nLocation: CLSB Building\, 3 Blackfan Circle\, Boston MA 02115 \n\n\n\n\nRegister now at: https://bit.ly/fall2024_speaker_series
URL:https://ds.dfci.harvard.edu/event/ligand-receptor-analysis-in-a-spatial-context/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2024/10/HBCFall24.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241120T120000
DTEND;TZID=America/New_York:20241120T130000
DTSTAMP:20260407T192144
CREATED:20241108T140605Z
LAST-MODIFIED:20241120T192210Z
UID:5679-1732104000-1732107600@ds.dfci.harvard.edu
SUMMARY:Niche-Driven Phenotypic Plasticity And Cis-Regulatory Dynamics Of A Revised Model For Intestinal Epithelial Differentiation
DESCRIPTION:CompBio Connections \nNovember 20th at 12pm\nCenter for Life Sciences Building\, 11th floor \nSwarnabh Bhattacharya\nResearch Fellow Dana-Farber Cancer Institute\n\nLunch is provided.
URL:https://ds.dfci.harvard.edu/event/niche-driven-phenotypic-plasticity-and-cis-regulatory-dynamics-of-a-revised-model-for-intestinal-epithelial-differentiation/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2024/11/Zico_headshot-e1731074579602.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241121T100000
DTEND;TZID=America/New_York:20241121T120000
DTSTAMP:20260407T192144
CREATED:20241029T142503Z
LAST-MODIFIED:20241029T142503Z
UID:5650-1732183200-1732190400@ds.dfci.harvard.edu
SUMMARY:Trajectory Inference in Single Cell Data
DESCRIPTION:The Harvard Chan Bioinformatics Core in partnership with The Cancer Data Sciences Program at DF/HCC are very excited to present the Fall seminar series: \nNovel Applications in Single Cell Omics \n\n\n\nLigand receptor analysis in a spatial context\nNovember 7th\nSizun Jiang\, PhD\nBeth Israel Deaconess Medical Center Harvard Medical School \nMartin Hemberg\, PhD and Jingyi Cao\, PhD Brigham and Women’s Hospital\nHarvard Medical School \nTrajectory inference in single cell data\nNovember 21st\nLuca Pinello\, PhD and Cameron Ray Smith\, MD\, PhD\nMassachusetts General Hospital \nSpatial transcriptomics deconvolution analysis\nDecember 5th\nKevin Wei\, MD\, PhD Brigham and Women’s Hospital\nRuben Dries\, PhD and George Chen Boston University School of Medicine \nAll seminar sessions are hybrid events being held from 10am to noon.\nLocation: CLSB Building\, 3 Blackfan Circle\, Boston MA 02115 \n\n\n\n\nRegister now at: https://bit.ly/fall2024_speaker_series
URL:https://ds.dfci.harvard.edu/event/trajectory-inference-in-single-cell-data/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2024/10/HBCFall24.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241121T160000
DTEND;TZID=America/New_York:20241121T170000
DTSTAMP:20260407T192144
CREATED:20241119T210657Z
LAST-MODIFIED:20241126T123840Z
UID:5686-1732204800-1732208400@ds.dfci.harvard.edu
SUMMARY:Enhanced Insights for Rare Diseases: Leveraging External Controls and Longitudinal Data in snSMART Designs
DESCRIPTION:HSPH Biostatistics/DFCI Data Science Colloquium \nThursday\, November 21 at 4:00pm\nHarvard TH Chan School of Public Health\nFXB-G01 \nKelley Kidwell\, PhD\nProfessor\, Biostatistics\nAssociate Chair for Academic Affairs\, Biostatistics\nUniversity of Michigan\, Ann Arbor
URL:https://ds.dfci.harvard.edu/event/enhanced-insights-for-rare-diseases-leveraging-external-controls-and-longitudinal-data-in-snsmart-designs/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2024/11/kidwell-crop.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241205T100000
DTEND;TZID=America/New_York:20241205T120000
DTSTAMP:20260407T192144
CREATED:20241029T143216Z
LAST-MODIFIED:20241206T124841Z
UID:5660-1733392800-1733400000@ds.dfci.harvard.edu
SUMMARY:Spatial Transcriptomics Deconvolution Analysis
DESCRIPTION:The Harvard Chan Bioinformatics Core in partnership with The Cancer Data Sciences Program at DF/HCC are very excited to present the Fall seminar series: \nNovel Applications in Single Cell Omics \n\n\n\nLigand receptor analysis in a spatial context\nNovember 7th\nSizun Jiang\, PhD\nBeth Israel Deaconess Medical Center Harvard Medical School \nMartin Hemberg\, PhD and Jingyi Cao\, PhD Brigham and Women’s Hospital\nHarvard Medical School \nTrajectory inference in single cell data\nNovember 21st\nLuca Pinello\, PhD and Cameron Ray Smith\, MD\, PhD\nMassachusetts General Hospital \nSpatial transcriptomics deconvolution analysis\nDecember 5th\nKevin Wei\, MD\, PhD Brigham and Women’s Hospital\nRuben Dries\, PhD and George Chen Boston University School of Medicine \nAll seminar sessions are hybrid events being held from 10am to noon.\nLocation: CLSB Building\, 3 Blackfan Circle\, Boston MA 02115 \n\n\n\n\nRegister now at: https://bit.ly/fall2024_speaker_series
URL:https://ds.dfci.harvard.edu/event/spatial-transcriptomics-deconvolution-analysis/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2024/10/HBCFall24.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241211T120000
DTEND;TZID=America/New_York:20241211T130000
DTSTAMP:20260407T192144
CREATED:20241204T191023Z
LAST-MODIFIED:20241211T183620Z
UID:5718-1733918400-1733922000@ds.dfci.harvard.edu
SUMMARY:EVOCANCERGPT: Generating Cancer Progression and Treatment Responses with Single-Cell RNA Sequences
DESCRIPTION:CompBio Connection Seminar Series \nWednesday December 11 at 12:00pm\nZelen Commons\, 11th floor\nCenter for Life Sciences Building \nSam Wang\, Computational Biologist\, Department of Data Science \nLunch is provided.
URL:https://ds.dfci.harvard.edu/event/evocancergpt-generating-cancer-progression-and-treatment-responses-with-single-cell-rna-sequences/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2024/12/Wang_Sam.jpeg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241219T120000
DTEND;TZID=America/New_York:20241219T130000
DTSTAMP:20260407T192144
CREATED:20241209T183348Z
LAST-MODIFIED:20250114T202112Z
UID:5733-1734609600-1734613200@ds.dfci.harvard.edu
SUMMARY:Interpretable and Data-driven Machine Learning Models for Analyzing High-dimensional Biological Data
DESCRIPTION:Data Science Seminar \nThursday December 19\, 2024 – 12pm-1pm\nCenter for Life Sciences Building\, room 11081 \nJunchen Yang\nDepartment of Computational Biology and Bioinformatics\, Yale University
URL:https://ds.dfci.harvard.edu/event/interpretable-and-data-driven-machine-learning-models-for-analyzing-high-dimensional-biological-data/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2024/12/junchen-scaled-e1733769209863.jpeg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250205T120000
DTEND;TZID=America/New_York:20250205T130000
DTSTAMP:20260407T192144
CREATED:20250128T174809Z
LAST-MODIFIED:20250205T180933Z
UID:5793-1738756800-1738760400@ds.dfci.harvard.edu
SUMMARY:Nice-Driven Cell Identities in the Self-Renewing Stomach Corpus Epithelium
DESCRIPTION:CompBio Connections Seminar\nWednesday February 5 at 12:00pm\nCenter for Life Sciences Building\, Zelen Commons\nKe Li\, PhD\, Research Fellow\, Dana-Farber Cancer Institute and Harvard Medical School \nLunch is provided.
URL:https://ds.dfci.harvard.edu/event/nice-driven-cell-identities-in-the-self-renewing-stomach-corpus-epithelium/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2025/01/Ke_headshot_square.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250206T160000
DTEND;TZID=America/New_York:20250206T170000
DTSTAMP:20260407T192144
CREATED:20250114T202055Z
LAST-MODIFIED:20250207T140322Z
UID:5776-1738857600-1738861200@ds.dfci.harvard.edu
SUMMARY:Choosing Good Subsamples for Regression Modelling: Nearly-True Models?
DESCRIPTION:Harvard Biostatistics Colloquium Series\nThursday February 6th\n4:00-5:00PM\nHarvard TH Chan School of Public Health\, FXB G12 \nThomas Lumley\, PhD\, Chair in Biostatistics\, University of Aukland\, New Zealand; Affiliate Professor\, University of Washington\, Department of Biostatistics
URL:https://ds.dfci.harvard.edu/event/choosing-good-subsamples-for-regression-modelling-nearly-true-models/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2025/01/lumley.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250213T110000
DTEND;TZID=America/New_York:20250213T120000
DTSTAMP:20260407T192144
CREATED:20250207T182809Z
LAST-MODIFIED:20250211T172627Z
UID:5831-1739444400-1739448000@ds.dfci.harvard.edu
SUMMARY:Analysis and Design of RNA sequences with Deep Learning
DESCRIPTION:Data Science Seminar\nThursday February 13th at 11am\nCenter for Life Sciences Building\, 111081 \nJoseph Valencia\, Oregon State University
URL:https://ds.dfci.harvard.edu/event/analysis-and-design-of-rna-sequences-with-deep-learning/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2025/02/joseph-e1738952849381.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250219T120000
DTEND;TZID=America/New_York:20250219T130000
DTSTAMP:20260407T192144
CREATED:20250211T172609Z
LAST-MODIFIED:20250219T130227Z
UID:5846-1739966400-1739970000@ds.dfci.harvard.edu
SUMMARY:Current Methods in Single Cell FFPE Analysis
DESCRIPTION:CompBio Connections\nFebruary 19\, 2025 at 12pm\nDFCI Center for Life Science Building\, Zelen Commons \nAnthony Anselmo\nLead Bioinformatician\nCenter for Cancer Genomics\, DFCI \nLunch is provided.
URL:https://ds.dfci.harvard.edu/event/current-methods-in-single-cell-ffpe-analysis/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2025/02/anthony_anselmo_phsweb-e1739294749828.jpeg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250227T160000
DTEND;TZID=America/New_York:20250227T170000
DTSTAMP:20260407T192144
CREATED:20250219T130212Z
LAST-MODIFIED:20250228T180912Z
UID:5867-1740672000-1740675600@ds.dfci.harvard.edu
SUMMARY:Single-cell Multi-sample Multi-condition Data Integration to Uncover Disease Signatures
DESCRIPTION:HSPH Biostatistics and DFCI Data Science Colloquium\nThursday February 27th at 4pm\nHSPH FXB Room G13 \nYingxin Lin\, PhD\nPostdoctoral Associate in the Department of Biostatistics at the Yale School of Public Health \nThe recent emergence of multi-sample multi-condition single-cell multi cohort studies allows researchers to investigate different cell states. The effective integration of multiple large-cohort studies promises biological insights into cells under different conditions that individual studies cannot provide. In this talk\, I will present scMerge2\, a scalable algorithm that allows data integration of atlas-scale multi-sample multi-condition single-cell studies. scMerge2 is generalized to enable the merging of millions of cells from single-cell studies generated by various single-cell technologies. Using a large data collection with over five million cells from 1000+ individuals\, we demonstrate that the integration of multi-sample multi-condition scRNAseq from multiple cohorts reveals signatures derived from cell-type expression that are more accurate in discriminating disease progression.
URL:https://ds.dfci.harvard.edu/event/single-cell-multi-sample-multi-condition-data-integration-to-uncover-disease-signatures/
LOCATION:Harvard TH Chan School of Public Health\, FXB G13\, 677 Huntington Ave\, Boston\, MA\, United States
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2025/02/headshot-scaled-e1739970101940.jpg
END:VEVENT
END:VCALENDAR