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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220401T130000
DTEND;TZID=America/New_York:20220401T173000
DTSTAMP:20260412T091820
CREATED:20220227T194301Z
LAST-MODIFIED:20220404T003221Z
UID:3312-1648818000-1648834200@ds.dfci.harvard.edu
SUMMARY:2022 Marvin Zelen Symposum: Data Visualization
DESCRIPTION:The growing availability of informative datasets and software tools has led to increased reliance on data visualizations across many industries\, academia\, and government. News organizations are increasingly embracing data journalism and including effective infographics as part of their reporting\, while in research we increasingly rely on data visualization to assess data quality and describe and defend our findings. This year’s Zelen symposium brings together data visualization experts and developers of some of the most widely used data visualization software to share their thoughts and ideas with us. \nApril 1\, 2022 1:00 – 5:30 PM\nSimmons University\, Paresky Conference Center\nRegister for in-person or virtual attendance. \nThis event is currently scheduled as a hybrid event. We will follow all CDC and institutional guidelines for COVID safety. In-person participants are asked to provide proof of up-to-date vaccination or a negative COVID test taken within the 48 hours prior to the event.  \n#zelen2022 \nProgram PDF. \nSpeakers: \n\nAlberto Cairo\, University of Miami\n“What You Design is Not What People See”\nAmanda Cox\,USA Facts\n“End of an Era”\nJeffrey Heer\, University of Washington\n“Authoring and Visualizing Multiverse Analyses”\nJessica Hullman\, Northwestern University\n“Visualizations as Model Checks”\nAlvitta Ottley\, Washington University in St. Louis\n“The Case for Precision Visualization”\nLace Padilla\, University of California\, Merced\n“Impacts of COVID-19 Uncertainty Visualizations”\nHadley Wickham\, RStudio\n“Recent Advances in the ggplot2 Ecosystem”\n\n  \nSpecial thanks to Frontier Science Foundation
URL:https://ds.dfci.harvard.edu/event/2022-marvin-zelen-symposum-data-visualization/
CATEGORIES:Conference
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220426T130000
DTEND;TZID=America/New_York:20220426T140000
DTSTAMP:20260412T091820
CREATED:20220105T135143Z
LAST-MODIFIED:20220429T134618Z
UID:3248-1650978000-1650981600@ds.dfci.harvard.edu
SUMMARY:Frontiers in Biostatistics: Tree-based Ensembling Strategies for Handling Heterogeneous Data
DESCRIPTION:Maya Ramchandran\nData Scientist\, ZephyrAI \nAbstract: Adapting machine learning algorithms to better handle clustering or other partition structure within training data sets is important across a wide variety of biological applications. We first consider the task of learning prediction models when multiple training studies are available. We present a novel weighting approach  for constructing tree-based ensemble learners in this setting\, showing that incorporating multiple layers of ensembling in the training process by weighting trees increases the robustness of the resulting predictor and achieves superior performance to Random Forest. Next\, we broaden the scope of the problem to consider the effect of ensembling forest-based learners trained on clusters within a single data set with heterogeneity in the distribution of the features. We show that constructing ensembles of forests trained on estimated clusters determined by algorithms such as k-means results in significant improvements in accuracy and generalizability over the traditional Random Forest algorithm. We denote our novel approach as the Cross-Cluster Weighted Forest\, and display its robustness and accuracy across simulations and on cancer molecular profiling and gene expression data sets that are naturally divisible into clusters. Finally\, we provide theoretical support to these empirical observations by asymptotically analyzing linear least squares and random forest regressions under a linear model. In particular\, for random forest regression under fixed dimensional linear models\, our bounds imply a strict benefit of our ensembling strategy over classic Random Forest. \nYouTube Video. \nMaya Ramchandran recently completed her PhD at the Harvard Biostatistics department under the supervision of Dr. Giovanni Parmigiani\, where she developed machine learning ensembling strategies with applications to cancer prediction problems. She holds a BS in Applied Mathematics-Biology from Brown University and a Masters of Music in Violin Performance from the New England Conservatory. She currently works as a data scientist at ZephyrAI\, a biotechnology startup that develops novel drug combination and repurposing treatments for oncology.
URL:https://ds.dfci.harvard.edu/event/frontiers-in-biostatistics-tree-based-ensembling-strategies-for-handling-heterogeneous-data/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2022/01/1595653826867.jpeg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220609T160000
DTEND;TZID=America/New_York:20220609T170000
DTSTAMP:20260412T091820
CREATED:20220606T131139Z
LAST-MODIFIED:20220610T103840Z
UID:3568-1654790400-1654794000@ds.dfci.harvard.edu
SUMMARY:Data Science Seminar: Identification of Novel Oncogenic and Neurodevelopmental Programs Using Bulk and Single-cell Sequencing Approaches
DESCRIPTION:Jeremy M. Simon\, Ph.D. (he/him/his)\nAssociate Professor\, Department of Genetics\nCo-Principal\, Bioinformatics and Analytics Research Collaborative (BARC)\nDirector\, UNC Neuroscience Center Bioinformatics Core\nCarolina Institute for Developmental Disabilities\nUniversity of North Carolina at Chapel Hill \nRegister for Zoom Webinar. \nEstablishing and maintaining proper transcriptional programs is central to both development and disease\, and involves the careful orchestration of transcription factors and chromatin modifier proteins. My groups seek to untangle these complex systems\, ask biologically-driven questions\, and formulate new hypotheses using analysis and integration of bulk or single-cell high-throughput sequencing approaches. I will focus on two vignettes: first\, a longitudinal transcriptomics analysis of neocortical development in a mouse model of autism\, and second\, the identification of novel oncogenic drivers and mechanisms in renal cell carcinoma.
URL:https://ds.dfci.harvard.edu/event/data-science-seminar-identification-of-novel-oncogenic-and-neurodevelopmental-programs-using-bulk-and-single-cell-sequencing-approaches/
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2022/06/jeremy_simon_cropped-1012x1024-1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220615T100000
DTEND;TZID=America/New_York:20220615T120000
DTSTAMP:20260412T091820
CREATED:20220525T113553Z
LAST-MODIFIED:20220617T113622Z
UID:3543-1655287200-1655294400@ds.dfci.harvard.edu
SUMMARY:Training Session: Biomarkers in Cancer Research
DESCRIPTION:Wednesday June 15\, 2022\n10:00-12:00pm Eastern Time \nNabihah Tayob\, PhD\nAssistant Professor\nDepartment of Data Science\, Dana-Farber Cancer Institute\nHarvard Medical School \nZoom registration: https://bit.ly/TSJune22 \n 
URL:https://ds.dfci.harvard.edu/event/training-session-biomarkers-in-cancer-research/
CATEGORIES:Training Session
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2020/04/tayob_nabihah-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220727T080000
DTEND;TZID=America/New_York:20220729T170000
DTSTAMP:20260412T091820
CREATED:20220429T134509Z
LAST-MODIFIED:20220715T104941Z
UID:3500-1658908800-1659114000@ds.dfci.harvard.edu
SUMMARY:BioC 2022 registration is now open!
DESCRIPTION:BioC2022 will be held as a hybrid event in Seattle\, WA on July 27-29\, 2022. Virtual registration is now open. \nTickets for in-person attendance are now on a waitlist. Click here to add your name to the list.\nAdditional tickets may become available if restrictions are lifted. We will email the waitlist at the end of May with an update.  \nBioC2022 highlights current developments within and beyond the Bioconductor project. It consists of: \n\nkeynote talks by speakers across various disciplines\nworkshops on current Bioconductor packages\nshort talks by community participants\nposter sessions\n\nFor more information\, go to our website at https://bioc2022.bioconductor.org/
URL:https://ds.dfci.harvard.edu/event/bioc-2022-registration-is-now-open/
CATEGORIES:Conference
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2022/04/bioconductor_2022.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220913T130000
DTEND;TZID=America/New_York:20220913T140000
DTSTAMP:20260412T091820
CREATED:20220822T141425Z
LAST-MODIFIED:20220916T155058Z
UID:3744-1663074000-1663077600@ds.dfci.harvard.edu
SUMMARY:It’s All Relative: Testing Differential Abundance in Compositional Microbiome Data
DESCRIPTION:Frontiers in Biostatistics Seminar Series \nTuesday September 13\, 2022\n1:00PM Eastern Time \nYijuan Hu\, Ph.D.\nAssociate Professor\nDepartment of Biostatistics and Bioinformatics\nRollins School of Public Health\nEmory University \nRegister for Zoom link \nAbstract: Studies on the human microbiome have revealed that differences in microbial communities are associated with many human disorders such as inflammatory bowel disease\, type II diabetes\, and even Alzheimer’s disease and some cancers. The microbiome is a particularly attractive target for establishing new biomarkers for disease diagnosis and prognosis\, and for developing low-cost\, low-risk interventions. Microbiome data have two unique features. First\, they are compositional\, i.e.\, the total number of sequencing reads per sample is an experimental artifact and only the relative abundance of taxa can be measured. Second\, they are subject to a wide variety of experimental biases (e.g.\, in the process of DNA extraction and PCR amplification) that plague most analyses that directly analyze relative abundance data. These features call for analyses that are based on log-ratio transformation of the relative abundance data. Existing methods often ignore experimental biases\, do not handle the extensive (50-90%) zero count data adequately\, and do not accommodate other complexities in microbiome data (e.g.\, high-dimensionality\, confounding covariates\, and continuous covariates of interest). In this talk\, we present a new logistic-regression-based method that takes into account all of these features of microbiome data for robust testing of differential abundance. Our simulation studies indicate that our method is the only one that universally controls the FDR while at the same time maintaining good power. We illustrate our method by the analysis of a throat microbiome dataset. \n 
URL:https://ds.dfci.harvard.edu/event/its-all-relative-testing-differential-abundance-in-compositional-microbiome-data/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2022/08/hu-photo-small.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221014T120000
DTEND;TZID=America/New_York:20221014T190000
DTSTAMP:20260412T091820
CREATED:20220715T104914Z
LAST-MODIFIED:20221013T144755Z
UID:3667-1665748800-1665774000@ds.dfci.harvard.edu
SUMMARY:Postdoc Open House
DESCRIPTION:The Dana-Farber Cancer Institute Department of Data Science announces its third annual Postdoc Open House Day on Friday\, October 14th\, 12pm-7pm in person. \nIf you are interested in learning more about postdoctoral opportunities at Dana-Farber Cancer Institute and would like to learn about the research our faculty are conducting\, please sign up for this free event. The faculty participating this year are: \n\nMartin Aryee\, PhD\nSahand Hormoz\, PhD\nRafael Irizarry\, PhD\nHeng Li\, PhD\nFranziska Michor\, PhD\nGiovanni Parmigiani\, PhD\nMehmet Samur\, PhD\nNabihah Tayob\, PhD\nHajime Uno\, PhD\n\nThe event will include presentations from faculty\, staff and former postdocs\, smaller groups meeting with group leaders\, and a happy hour. We will be able to cover travel for a limited number of individuals. \nSpace is limited and we request that you are actively looking for a postdoctoral position. \nPlease complete this form to request admission. Deadline is Friday\, September 9th. 
URL:https://ds.dfci.harvard.edu/event/postdoc-open-house/
CATEGORIES:Recruitment
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221101T130000
DTEND;TZID=America/New_York:20221101T140000
DTSTAMP:20260412T091820
CREATED:20221013T144710Z
LAST-MODIFIED:20221101T194024Z
UID:3821-1667307600-1667311200@ds.dfci.harvard.edu
SUMMARY:Design and Implementation of Bayesian Adaptive Phase I Trials in Oncology using the DEDUCE Application
DESCRIPTION:Frontiers in Biostatistics Seminar Series \nTuesday November 1\, 2022\n1:00PM Eastern Time \nRegister for in-person or virtual attendance. \nWendy London\, PhD\nAssociate Professor\, Harvard Medical School\nDirector of Biostatistics\, Boston Children’s Hospital \nClement Ma\, PhD Assistant Professor\, University of Toronto\nIndependent Scientist\, CAMH
URL:https://ds.dfci.harvard.edu/event/design-and-implementation-of-bayesian-adaptive-phase-i-trials-in-oncology-using-the-deduce-application/
LOCATION:Center of Life Sciences\, Room 11081\, 3 Blackfan Circle\, Boston\, MA\, 02215\, United States
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2022/10/dual_photo.png
GEO:42.3394159;-71.104234
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Center of Life Sciences Room 11081 3 Blackfan Circle Boston MA 02215 United States;X-APPLE-RADIUS=500;X-TITLE=3 Blackfan Circle:geo:-71.104234,42.3394159
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221206T130000
DTEND;TZID=America/New_York:20221206T140000
DTSTAMP:20260412T091820
CREATED:20221013T170456Z
LAST-MODIFIED:20221207T142413Z
UID:3837-1670331600-1670335200@ds.dfci.harvard.edu
SUMMARY:COVID Data-Driven Policy: NC DHHS's Use of Data for Pandemic Response
DESCRIPTION:Frontiers in Biostatistics Seminar \nTuesday December 6\, 2022\n1:00PM Eastern Time \nRegister for Zoom link. \nJessie Tenenbaum\, PhD\nshe / her / hers\nChief Data Officer\nNC Department of Health and Human Services
URL:https://ds.dfci.harvard.edu/event/covid-data-driven-policy-nc-dhhss-use-of-data-for-pandemic-response/
CATEGORIES:Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230124T130000
DTEND;TZID=America/New_York:20230124T140000
DTSTAMP:20260412T091820
CREATED:20221128T192916Z
LAST-MODIFIED:20230203T145004Z
UID:3888-1674565200-1674568800@ds.dfci.harvard.edu
SUMMARY:A Nonparametric Bayesian Approach to Use RWD in Clinical Trial Design
DESCRIPTION:Frontiers in Biostatistics Seminar \nTuesday January 24\, 2023\n1:00PM Eastern Time\nClick to watch the YouTube video. \nPeter Mueller\, PhD\nProfessor\nDepartment of Statistics and Data Sciences\nDepartment of Mathematics\nUniversity of Texas at Austin \n 
URL:https://ds.dfci.harvard.edu/event/a-nonparametric-bayesian-approach-to-use-rwd-in-clinical-trial-design/
CATEGORIES:Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230214T130000
DTEND;TZID=America/New_York:20230214T140000
DTSTAMP:20260412T091820
CREATED:20221128T194757Z
LAST-MODIFIED:20230307T152329Z
UID:3899-1676379600-1676383200@ds.dfci.harvard.edu
SUMMARY:Using the Case Study of Atezolizumab Development to Rethink Early Phase Oncology Trial Design
DESCRIPTION:Frontiers in Biostatistics Seminar \nTuesday February 14\, 2023\n1:00PM Eastern Time\nYouTube video \nEmily Zabor\, DrPH\nAssistant Staff Biostatistician\nDepartment of Quantitative Health Sciences at the Cleveland Clinic\, with a joint appointment in the Taussig Cancer Institute\nAssistant Professor of Medicine\, the Cleveland Clinic Lerner College of Medicine of Case Western Reserve University
URL:https://ds.dfci.harvard.edu/event/frontiers-in-biostatistics-emily-zabor/
CATEGORIES:Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230302T130000
DTEND;TZID=America/New_York:20230302T140000
DTSTAMP:20260412T091820
CREATED:20230224T194353Z
LAST-MODIFIED:20230308T124839Z
UID:4088-1677762000-1677765600@ds.dfci.harvard.edu
SUMMARY:Computation of High-Dimensional Penalized Generalized Linear Mixed Models
DESCRIPTION:Thursday March 2\, 2023\n1:00pm ET \nHillary Heiling\nBiostatistics PhD candidate\nUniversity of North Carolina Chapel Hill. \nAdd to calendar \nHillary’s statistical focus has primarily been in cancer-related research\, both through her graduate research assistant role in the Lineberger Comprehensive Cancer Center as well as her personal research applications. In cancer research as well as other biomedical areas\, there are issues with the replicability of results between studies. Hillary will present her work on improving the replicable selection of gene signatures for the prediction of cancer subtypes by combining data across studies and performing variable selection on generalized linear mixed models. Hillary has been able to extend the feasible dimensionality of the application to hundreds of predictors by using a factor model decomposition on the random effects\, which behaves as a dimension reduction technique. Hillary has developed software to perform this task and has published her ‘glmmPen’ R package on CRAN.
URL:https://ds.dfci.harvard.edu/event/computation-of-high-dimensional-penalized-generalized-linear-mixed-models/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2023/02/hillary-e1677267404626.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230329T130000
DTEND;TZID=America/New_York:20230329T140000
DTSTAMP:20260412T091820
CREATED:20230120T174649Z
LAST-MODIFIED:20230329T184122Z
UID:3949-1680094800-1680098400@ds.dfci.harvard.edu
SUMMARY:Dimension Reduction of Longitudinal Microbiome Data
DESCRIPTION:Frontiers in Biostatistics Seminar \nWednesday March 29\, 2023\n1:00PM Eastern Time \nPixu Shi\, PhD\nAssistant Professor of Biostatistics & Bioinformatics\nDivision of Integrative Genomics\nDepartment of Biostatistics & Bioinformatics\nDuke University School of Medicine \nAbstract:\nThe analysis of longitudinal microbiome is crucial to the understanding of how microbiome changes over time. It often requires careful maneuver of high dimensional microbial features\, missing samples and varying time points across subjects. Longitudinal microbiome data can often be formatted into a high-dimensional order-3 tensor with three modes representing the subject\, time\, and bacteria respectively. In this talk\, we present functional tensor SVD\, a dimension reduction tool that can uncover sub-population structures in subjects\, compress high-dimensional features into low-dimensional trajectories\, and extract shared temporal patterns among features\, all without imputation of missing samples or rounding of time points. We will demonstrate the robust performance of our method through simulations and multiple case studies.
URL:https://ds.dfci.harvard.edu/event/dimension-reduction-of-longitudinal-microbiome-data/
CATEGORIES:Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230407T130000
DTEND;TZID=America/New_York:20230407T170000
DTSTAMP:20260412T091820
CREATED:20230216T194917Z
LAST-MODIFIED:20230410T125358Z
UID:4043-1680872400-1680886800@ds.dfci.harvard.edu
SUMMARY:Machine Learning in Medical Imaging: From New Techniques to Clinical Translation
DESCRIPTION:Zelen 2023 Program \nThe 2023 Marvin Zelen Memorial Symposium featuring talks by: \n\nAndy Beck (Co-founder & CEO\, Path AI)\nEmerging Methods in Machine Learning and Applications for Digital Pathology\nJonathan Chen (Instructor in Pathology\, MGH)\nMulticellular Networks: Immunity Hubs in Human NSCLC\nMarzyeh Ghassemi (Assistant Professor\, MIT)\nDesigning Machine Learning Processes For Equitable Health Systems\nPolina Golland (Professor\, MIT)\nLearning to Read X-ray: Applications to Heart Failure Monitoring\nJayashree Kalpathy-Cramer (Professor\, University of Colorado\, MGH\, and HMS)\nOpportunities and Challenges for Medical Imaging AI – Lessons from Oncology and Ophthalmology\nBill Lotter (Member of the Faculty\, DFCI and HMS)\nAI for Mammography: From Algorithms to Clinical Integration\nShantanu Singh (Senior Group Leader\, Broad Institute)\nFortune-telling with Images: Painting Cells for Discovering Drugs\n\nFriday April 7\, 2023\n1:00-5:00PM \nSimmons University\nParesky Conference Center\n300 The Fenway\, Boston\, MA \nReception to follow. \nRegister for virtual or in-person attendance.
URL:https://ds.dfci.harvard.edu/event/machine-learning-in-medical-imaging-from-new-techniques-to-clinical-translation/
LOCATION:Simmons University\, 300 The Fenway\, Boston\, MA\, United States
CATEGORIES:Conference
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2023/02/Zelen-2023-Instagram-Post-Square-e1680115209110.png
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230509T130000
DTEND;TZID=America/New_York:20230509T140000
DTSTAMP:20260412T091820
CREATED:20230410T125338Z
LAST-MODIFIED:20230515T123922Z
UID:4170-1683637200-1683640800@ds.dfci.harvard.edu
SUMMARY:Model-robust and Efficient Covariate Adjustment for Cluster-randomized Experiments
DESCRIPTION:Frontiers in Biostatistics Seminar \nTuesday May 9\, 2023\n1:00PM Eastern Time \nJoin the Zoom. \nFan Li\, PhD\nAssistant Professor of Biostatistics\, Yale School of Public Health \nCluster-randomized experiments are increasingly used to evaluate interventions in routine practice conditions\, and researchers often adopt model-based methods with covariate adjustment in the statistical analyses. However\, the validity of model-based covariate adjustment is unclear when the working models are misspecified\, leading to ambiguity of estimands and risk of bias. In this article\, we first adapt two conventional model-based methods\, generalized estimating equations and linear mixed models\, with weighted g-computation to achieve robust inference for cluster-average and individual-average treatment effects. Furthermore\, we propose an efficient estimator for each estimand that allows for flexible covariate adjustment and additionally addresses cluster size variation dependent on treatment assignment and other cluster characteristics. Such cluster size variations often occur post-randomization and\, if ignored\, can lead to bias of model-based estimators. For our proposed estimator\, we prove that when the nuisance functions are consistently estimated by machine learning algorithms\, the estimator is consistent\, asymptotically normal\, and efficient. When the nuisance functions are estimated via parametric working models\, the estimator is triply-robust. Simulation studies and analyses of three real-world cluster-randomized experiments demonstrate that the proposed methods are superior to existing alternatives.
URL:https://ds.dfci.harvard.edu/event/model-robust-and-efficient-covariate-adjustment-for-cluster-randomized-experiments/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2023/04/fanli-scaled-e1681131195600.jpeg
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20230802
DTEND;VALUE=DATE:20230805
DTSTAMP:20260412T091820
CREATED:20230515T123912Z
LAST-MODIFIED:20230515T123912Z
UID:4247-1690934400-1691193599@ds.dfci.harvard.edu
SUMMARY:BioC2023: the Bioconductor Annual Conference
DESCRIPTION:We are incredibly excited that Bioc2023 the annual Bioconductor meeting will be in Boston at the Dana-Farber Cancer Institute from August 2-4. It is a hybrid meeting to enable maximum outreach to our global community. Registration is now open and scholarships are available.  \nContact us for sponsorship opportunities.  \nSpeakers include: \n\nJJ Allaire (Founder and CEO of RStudio\, Posit PBC)\nHeng Li (Associate Professor\, Dana-Farber Cancer Institute\, Harvard Medical School)\nBeth Cimini (Senior Group Leader\, Broad Institute of MIT & Harvard)\nJeffrey Moffitt (Assistant Professor\, Harvard Medical School and Boston Children’s Hospital) \nSam Lent (Senior Computational Biologist at Freenome)\n\nConnect with talented R/Bioconductor users & developers\, data scientists\, biostatisticians\, and bioinformaticians at #Bioc2023
URL:https://ds.dfci.harvard.edu/event/bioc2023-the-bioconductor-annual-conference/
LOCATION:Dana-Farber Cancer Institute\, 450 Brookline Ave\, Boston\, MA\, 02215\, United States
CATEGORIES:Conference
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230926T100000
DTEND;TZID=America/New_York:20230926T110000
DTSTAMP:20260412T091820
CREATED:20230825T175051Z
LAST-MODIFIED:20231005T140106Z
UID:4458-1695722400-1695726000@ds.dfci.harvard.edu
SUMMARY:Forecasting pancreatic carcinogenesis from spatial multi-omics
DESCRIPTION:Frontiers in Biostatistics Seminar \nTuesday September 26\, 2023 @ 10am ET\nCenter for Life Sciences Building\, Room 11081 \nElana Fertig\, PhD\nDivision Director of Oncology Quantitative Sciences\, Professor of Oncology\nJohns Hopkins University \nYouTube Video \nCombining genomics with mathematical modeling provides a forecast system that can yield computational predictions to anticipate cancer progression and therapeutic response. High-throughput profiling technologies can indicate the molecular and cellular pathways of malignancies\, but not the effect of targeting those pathways with therapy. Precision interception requires relating therapies to the cellular phenotypes underlying pancreatic carcinogenesis. This talk presents a hybrid computational and experimental strategy to uncover interactions between neoplastic cells and the microenvironment during pancreatic carcinogenesis. As pancreatic cancer develops\, it forms a complex microenvironment of multiple interacting cells. The microenvironment of advanced pancreatic cancer includes a heterogeneous and dense population of cells\, such as macrophages and fibroblasts\, that are associated with immunosuppression. New single-cell and spatial molecular profiling technologies enable unprecedented characterization of the cellular and molecular composition of the microenvironment. These technologies provide the potential to identify candidate therapeutics to intercept immunosuppression in pancreatic cancer. State-of-the-art mathematical approaches in computational biology are essential to uncover mechanistic insights for high-throughput data for these precision interception strategies. \n  \nWant to get our weekly events newsletter? Click here!
URL:https://ds.dfci.harvard.edu/event/forecasting-pancreatic-carcinogenesis-from-spatial-multi-omics/
LOCATION:Center of Life Sciences\, Room 11081\, 3 Blackfan Circle\, Boston\, MA\, 02215\, United States
CATEGORIES:Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20231024T130000
DTEND;TZID=America/New_York:20231024T140000
DTSTAMP:20260412T091820
CREATED:20230825T175528Z
LAST-MODIFIED:20231031T115135Z
UID:4463-1698152400-1698156000@ds.dfci.harvard.edu
SUMMARY:AI in Medical Imaging: Current State & Future Opportunities
DESCRIPTION:Frontiers in Biostatistics Seminar \nTuesday October 24\, 2023 @ 1pm ET\nCenter for Life Sciences Building\, Room 11081 \nWilliam Lotter\, PhD\nAssistant Professor\, Dana-Farber Cancer Institute and Harvard Medical School \nYouTube Video \nWant to get our weekly events newsletter? Click here!
URL:https://ds.dfci.harvard.edu/event/frontiers-in-biostatistics-william-lotter/
LOCATION:Center of Life Sciences\, Room 11081\, 3 Blackfan Circle\, Boston\, MA\, 02215\, United States
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2022/08/Bill_Lotter_headshot-scaled-e1659653586370.jpg
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20231108T120000
DTEND;TZID=America/New_York:20231108T130000
DTSTAMP:20260412T091820
CREATED:20231030T131716Z
LAST-MODIFIED:20231030T131847Z
UID:4616-1699444800-1699448400@ds.dfci.harvard.edu
SUMMARY:Single-cell Multiomic Exploration of Oncogenic and Immunologic Programs in Melanoma and CLL
DESCRIPTION:Elevate @ Eleven: Comp Bio Connections \nWednesday November 8th\, 2023\n12:00-1:00PM\nIn-person only\, Zelen Commons\, 11th floor of the Center for Life Sciences Building \nJeremy Simon\nSenior Research Scientist\, Harvard T.H. Chan School of Public Health \nLunch is provided. \n 
URL:https://ds.dfci.harvard.edu/event/single-cell-multiomic-exploration-of-oncogenic-and-immunologic-programs-in-melanoma-and-cll/
LOCATION:Center for Life Sciences\, Zelen Commons\, 3 Blackfan Circle\, Boston\, MA\, 02115
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2023/01/Jeremy-Simon-600x600-1-e1673981068499.jpeg
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20231205T130000
DTEND;TZID=America/New_York:20231205T140000
DTSTAMP:20260412T091820
CREATED:20230901T114137Z
LAST-MODIFIED:20231208T201749Z
UID:4488-1701781200-1701784800@ds.dfci.harvard.edu
SUMMARY:Analyzing Big EHR Data - Optimal Cox Regression Subsampling Procedure with Rare Events
DESCRIPTION:Frontiers in Biostatistics Seminar \nTuesday December 5\, 2023 @ 1pm ET\nYouTube Link \nMalka Gorfine\, PhD\nProfessor\, Department of Statistics\,  Tel Aviv University\, Israel \nAbstract: Massive sized survival datasets become increasingly prevalent with the development of the healthcare industry\, and pose computational challenges unprecedented in traditional survival analysis use cases. In this work we analyze the UK-biobank colorectal cancer data with genetic and environmental risk factors\, including a time-dependent coefficient\, which transforms the dataset into “pseudo-observation” form\, thus critically inflating its size. A popular way for coping with massive datasets is downsampling them\, such that the computational resources can be afforded by the researcher. Cox regression has remained one of the most popular statistical models for the analysis of survival data to-date. This work addresses the settings of right censored and possibly left-truncated data with rare events\, such that the observed failure times constitute only a small portion of the overall sample. We propose Cox regression subsampling-based estimators that approximate their full-data partial-likelihood-based counterparts\, by assigning optimal sampling probabilities to censored observations\, and including all observed failures in the analysis. The suggested methodology is applied on the UK-biobank for building a colorectal cancer risk-prediction model\, while reducing the computation time and memory requirements. We establish asymptotic properties under suitable conditions and develop a framework for determining the optimal subsample size. \nWant to get our weekly events newsletter? Click here!
URL:https://ds.dfci.harvard.edu/event/frontiers-in-biostatistics-seminar-malka-gorfine/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2023/09/portrait.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20231206T120000
DTEND;TZID=America/New_York:20231206T130000
DTSTAMP:20260412T091820
CREATED:20231121T123117Z
LAST-MODIFIED:20231121T123117Z
UID:4661-1701864000-1701867600@ds.dfci.harvard.edu
SUMMARY:The Splicing Factor CCAR1 Regulates the Fanconi Anemia/BRA Pathway
DESCRIPTION:Elevate @ Eleven: Comp Bio Connections \nWednesday December 6th\, 2023\n12:00-1:00PM\nIn-person only\, Zelen Commons\, 11th floor of the Center for Life Sciences Building \nHuy Nguyen\nComputational Biologist\, Center for DNA Damage & Repair\, Dana-Farber Cancer Institute \nLunch is provided. \n 
URL:https://ds.dfci.harvard.edu/event/the-splicing-factor-ccar1-regulates-the-fanconi-anemia-bra-pathway/
LOCATION:Center for Life Sciences\, Zelen Commons\, 3 Blackfan Circle\, Boston\, MA\, 02115
CATEGORIES:Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240110T120000
DTEND;TZID=America/New_York:20240110T130000
DTSTAMP:20260412T091820
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:20260412T091820
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:20260412T091820
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:20240131T130000
DTEND;TZID=America/New_York:20240131T173000
DTSTAMP:20260412T091820
CREATED:20240104T204924Z
LAST-MODIFIED:20240104T204924Z
UID:4782-1706706000-1706722200@ds.dfci.harvard.edu
SUMMARY:DF/HCC Celebration of Early Career Investigators in Cancer Research
DESCRIPTION:Wednesday January 31\, 2024\n1:00pm – 5:30PM\nYawkey Conference Center\, Dana-Farber Cancer Institute\nRegistration. \n2024 Keynote Speaker: Jeff Leek\, PhD\nChief Data Officer\, Vice President\, and J Orin Edson Foundation Chair of Biostatistics at the Fred Hutchinson Cancer Center\nTalk Title: “Taking Calculated Career Risks to Impact the World Through Data Science” \nIntroductions by: \n\nRamesh Shivdasani\, Deputy Director of the DF/HCC and Professor of Medicine at Harvard Medical School\, and\nLaurie Glimcher\, Director of the DF/HCC and President and CEO of the Dana-Farber Cancer Institute\n\nEarly career investigators are a unique reservoir of new ideas\, innovation\, and excellence in cancer research. To celebrate this\, we welcome you to join the 11th Annual DF/HCC Celebration of Early Investigators in Cancer Research. This symposium will showcase the talent of early career investigators at the Dana-Farber/Harvard Cancer Center (DF/HCC) who work in several areas of population science\, including epidemiology\, biostatistics\, outcomes\, diversity\, and survivorship. We invite all members of the public to attend the event. We also invite students\, post-docs\, residents\, clinical fellows\, and early career investigators to submit abstracts for consideration as oral or poster presentations. We look forward to an exciting afternoon of discussion\, sharing new discoveries\, and building new collaborations. – Lorelei Mucci\, ScD (HSPH)\, Giovanni Parmigiani\, PhD (DFCI)\, Erica Feick (DFCI)\, Bailey Vaselkiv (HSPH)\, and Hannah Guard (HSPH). \nCurrently\, the event will be broadcast live without any recording option. All speakers must attend in person. Adjustments to the event status will be considered if there are changes to masking regulations.
URL:https://ds.dfci.harvard.edu/event/df-hcc-celebration-of-early-career-investigators-in-cancer-research/
CATEGORIES:Symposium
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2024/01/logo-only-e1704401329917.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240206T130000
DTEND;TZID=America/New_York:20240206T140000
DTSTAMP:20260412T091820
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:20260412T091820
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:20260412T091820
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:20260412T091820
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:20240405T130000
DTEND;TZID=America/New_York:20240405T170000
DTSTAMP:20260412T091820
CREATED:20240205T132216Z
LAST-MODIFIED:20240409T122906Z
UID:4900-1712322000-1712336400@ds.dfci.harvard.edu
SUMMARY:2024 Marvin Zelen Symposium: Health Disparities and Cancer
DESCRIPTION:Friday April 5\, 2024\n1:00-5:00PM ET \nYawkey Conference Center\n450 Brookline Ave\, Boston\, MA\nIn-person event only\, the recording will be available post-event. \nRegistration for in person attendance. \nInvited speakers: \n\nAdewole Adamson\, MD\, MPP\, Dell Medical School at the University of Texas at Austin\, “AI and Melanoma Disparities”\nCynthia Dwork\,PhD\, Harvard University\, “Individuals\, Groups\, Indistinguishability\, and Loss: 15 Years of Algorithmic Fairness in 20 Minutes”\nNate Fillmore\,PhD\, VA Boston Healthcare System and Harvard Medical School\, “Health Disparities and Cancer in the National VA Healthcare System”\nCarmen E. Guerra\, MD\, MSCE\, University of Pennsylvania\, “The (Mis)use of Race and Ethnicity in Biomedical Research”\nJinani Jayasekera\, PhD\, National Institute on Minority Health and Health Disparities\, “Personalized Clinical Decision Tools to Support Equitable Breast Cancer Care”\nBogdan Pasaniuc\,PhD\, University of California Los Angeles\, “Polygenic risk scoring in personalized medicine: promises and challenges”
URL:https://ds.dfci.harvard.edu/event/2024-marvin-zelen-symposium-health-disparities-and-cancer/
LOCATION:Dana-Farber Cancer Institute\, 450 Brookline Ave\, Boston\, MA\, 02215\, United States
CATEGORIES:Symposium
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2024/02/Zelen2024_forwebsite_image.png
GEO:42.3372552;-71.1076591
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END:VEVENT
END:VCALENDAR