BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Dana-Farber Cancer Institute - ECPv6.15.20//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Dana-Farber Cancer Institute
X-ORIGINAL-URL:https://ds.dfci.harvard.edu
X-WR-CALDESC:Events for Dana-Farber Cancer Institute
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20190310T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20191103T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20200308T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20201101T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20210314T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20211107T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20220313T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20221106T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20211103T130000
DTEND;TZID=America/New_York:20211103T150000
DTSTAMP:20260412T091934
CREATED:20210928T135710Z
LAST-MODIFIED:20211029T115457Z
UID:3043-1635944400-1635951600@ds.dfci.harvard.edu
SUMMARY:Postdoc Recruitment Day
DESCRIPTION:The Dana-Farber Cancer Institute Department of Data Science announces its second annual Postdoc Recruitment Day to be held on Wednesday\, November 3rd from 1-3pm EST. \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· Sahand Hormoz\, Assistant Professor \n· Rafael Irizarry\, Professor and Department Chair \n· Heng Li\, Assistant Professor \n· Giovanni Parmigiani\, Professor \n· Mehmet Samur\, Senior Research Scientist \n· Nabihah Tayob\, Assistant Professor \nThe faculty will give brief overviews of their current research. You will also hear from current and former postdocs\, and hear about the resources available in the department\, at Dana-Farber and throughout the Boston area. \nSpace is limited and we request that you are actively looking for a postdoctoral position. Please complete this form to request admission. The deadline to apply is October 29th. \nYou can see our open postdoctoral positions on our website: https://ds.dfci.harvard.edu/careers/
URL:https://ds.dfci.harvard.edu/event/postdoc-recruitment-day/
CATEGORIES:Recruitment
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20211028T110000
DTEND;TZID=America/New_York:20211028T120000
DTSTAMP:20260412T091934
CREATED:20211021T234121Z
LAST-MODIFIED:20211029T115538Z
UID:3129-1635418800-1635422400@ds.dfci.harvard.edu
SUMMARY:Data Science Seminar: Causal Inference Methods for Measures of Health Disparities
DESCRIPTION:Thursday\, October 28\, 2021\n11:00am Eastern Time \nTengfei Li\nGeorgetown University \nCausal Inference Methods for Measures of Health Disparities \nThere is increased interest in the evaluation of health disparities between different socioeconomic groups using data from observational studies. However\, in the absence of randomization\, the results and conclusions may be limited to associations rather than causal effects. The causal inference framework allows us to estimate causal measures for such situations. We present inverse probability weighting (IPW) and doubly robust (DR) estimators for the marginal means of the distributions of the potential outcomes for multiple socioeconomic groups using generalized propensity scores. We estimate the variance of the vector of IPW and DR estimators for the marginal means by using an M-estimation approach. The variances of the estimators for causal measures of health disparities are subsequently estimated using the multivariate delta method. In simulation studies\, the new methods provide coverage probabilities that are close to the nominal level when used to construct 95% confidence intervals for the causal measures of health disparities. \nKeywords: health disparities\, inverse probability weighting estimator\, doubly robust estimator\, generalized propensity score\, M-estimation.
URL:https://ds.dfci.harvard.edu/event/data-science-seminar-causal-inference-methods-for-measures-of-health-disparities/
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2021/10/Screen-Shot-2021-10-21-at-3.45.00-PM.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20211019T130000
DTEND;TZID=America/New_York:20211019T140000
DTSTAMP:20260412T091934
CREATED:20210928T181448Z
LAST-MODIFIED:20211201T165250Z
UID:3058-1634648400-1634652000@ds.dfci.harvard.edu
SUMMARY:Frontiers in Biostatistics: Treatment-free Survival as a Novel Outcome Measure of Immuno-oncology-based Therapy
DESCRIPTION:Tuesday\, October 19\, 2021\n1:00pm Eastern Time \nMeredith Regan\, ScD\nAssociate Professor\nDepartment of Data Science\, Dana-Farber Cancer Institute\,\nHarvard Medical School \nTreatment-free Survival as a Novel Outcome Measure of Immuno-oncology-based Therapy \nYouTube Link
URL:https://ds.dfci.harvard.edu/event/frontiers-in-biostatistics-meredith-regan/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2021/09/preferred_meredith_regan_square.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20210914T130000
DTEND;TZID=America/New_York:20210914T140000
DTSTAMP:20260412T091934
CREATED:20210614T164652Z
LAST-MODIFIED:20211021T134349Z
UID:2797-1631624400-1631628000@ds.dfci.harvard.edu
SUMMARY:Frontiers in Biostatistics: COVID Vaccine Efficacy Trial Designs\, Open Questions and Statistical Challenges
DESCRIPTION:Tuesday September 14\, 2021\n1:00PM Eastern Time \nHolly Janes\, Ph.D.\nProfessor\, Vaccine and Infectious Disease Division\, Fred Hutchinson Cancer Research Center\nProfessor\, Public Health Sciences Division\, Fred Hutchinson Cancer Research Center \nYouTube video now available.
URL:https://ds.dfci.harvard.edu/event/frontiers-in-biostatistics-holly-janes/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2021/06/holly-janes-sq.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20210616T100000
DTEND;TZID=America/New_York:20210616T120000
DTSTAMP:20260412T091934
CREATED:20210608T184016Z
LAST-MODIFIED:20210630T184005Z
UID:2775-1623837600-1623844800@ds.dfci.harvard.edu
SUMMARY:Training Session: Survival Analysis and Competing Risks Data Analysis
DESCRIPTION:June 16\, 23\, and 30\, 2021\n10:00am-12:00PM Eastern Time \nHaesook Kim\, PhD\nPrincipal Research Scientist\nDepartment of Data Science\, Dana-Farber Cancer Institute\nDepartment of Biostatistics\, Harvard T.H. Chan School of Public Health \nRSVP: https://bit.ly/DSTSJune16
URL:https://ds.dfci.harvard.edu/event/training-session-survival-analysis-and-competing-risks-data-analysis/2021-06-16/
CATEGORIES:Training Session
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2021/06/kim_headshot.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20210608T130000
DTEND;TZID=America/New_York:20210608T140000
DTSTAMP:20260412T091934
CREATED:20210108T131835Z
LAST-MODIFIED:20211021T134536Z
UID:2398-1623157200-1623160800@ds.dfci.harvard.edu
SUMMARY:Frontiers in Biostatistics: The Use of External Control Data for Predictions and Interim Analyses in Clinical Trials
DESCRIPTION:June 8\, 2021\n1:00PM \nLorenzo Trippa\, PhD\nAssociate Professor\nDepartment of Biostatistics\, Harvard T.H. Chan School of Public Health\nDepartment of Data Science\, Dana-Farber Cancer Institute \nThe Use of External Control Data for Predictions and Interim Analyses in Clinical Trials \nYouTube video now available.
URL:https://ds.dfci.harvard.edu/event/frontiers-in-biostatistics-lorenzo-trippa/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2021/01/trippa.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20210525T130000
DTEND;TZID=America/New_York:20210525T140000
DTSTAMP:20260412T091934
CREATED:20210506T120012Z
LAST-MODIFIED:20211021T134757Z
UID:2724-1621947600-1621951200@ds.dfci.harvard.edu
SUMMARY:Data Science Zoominar: Modeling Cancer Etiology and Evolution\, and its Implications for Prevention
DESCRIPTION:Tuesday May 25\, 2021\n1:00PM ET \nA conversation with Cristian Tomasetti\nAssociate Professor\, Department of Oncology\, Johns Hopkins Medicine\, Sidney Kimmel Comprehensive Cancer Center \nModerator: Giovanni Parmigiani \nYouTube Video now available. 
URL:https://ds.dfci.harvard.edu/event/data-science-zoominar-mathematical-modeling-and-cancer-prevention/
CATEGORIES:Zoominar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2021/05/cristian-head-shot.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20210519T100000
DTEND;TZID=America/New_York:20210519T120000
DTSTAMP:20260412T091934
CREATED:20210415T135645Z
LAST-MODIFIED:20210520T125744Z
UID:2703-1621418400-1621425600@ds.dfci.harvard.edu
SUMMARY:Training Session: Efficient Phase I Clinical Trial Design
DESCRIPTION:May 19\, 2021\n10:00am-12:00PM Eastern Time \nFangxin Hong\, PhD\nSenior Research Scientist\nDepartment of Data Science\, Dana-Farber Cancer Institute\nDepartment of Biostatistics\, Harvard T.H. Chan School of Public Health \n  \n 
URL:https://ds.dfci.harvard.edu/event/training-session-efficient-phase-i-clinical-trial-design/
CATEGORIES:Training Session
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2021/04/FH.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20210511T130000
DTEND;TZID=America/New_York:20210511T140000
DTSTAMP:20260412T091934
CREATED:20200921T180944Z
LAST-MODIFIED:20210511T180948Z
UID:2138-1620738000-1620741600@ds.dfci.harvard.edu
SUMMARY:Frontiers in Biostatistics: Single-Cell RNA-Seq Data Analysis Via a Regularized Zero-Inflated Mixture Model Framework
DESCRIPTION:Frontiers in Biostatistics Seminar\nMay 11\, 2021\n1:00PM \nJianhua Hu\, PhD\nProfessor\, Biostatistics (in Medicine and in the Herbert Irving Comprehensive Cancer Center)\nDirector\, Cancer Biostatistics Program\nColumbia University \nRegister at: http://bit.ly/FIBMay21 \nAbstract: Applications of single-cell RNA sequencing in various biomedical research areas have been blooming. This new technology provides unprecedented opportunities to study disease heterogeneity at the cellular level. However\, unique characteristics of scRNA-seq data\, including large dimensionality\, high dropout rates\, and possibly batch effects\, bring great difficulty into the analysis of such data. Not appropriately addressing these issues obstructs true scientific discovery. Herein\, we propose a unified Regularized Zero-inflated Mixture Model framework designed for scRNA-seq data (RZiMM-scRNA) to simultaneously detect cell subgroups and identify gene differential expression based on a developed importance score\, accounting for both dropouts and batch effects. We conduct extensive empirical investigation to demonstrate the promise of RZiMM-scRNA in comparison to several popular methods\, including K-means and Hierarchical clustering. \nThis seminar was not recorded as the research presented has not been published yet. 
URL:https://ds.dfci.harvard.edu/event/frontiers-in-biostatistics-jianhua-hu/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2020/09/Hu_4x4.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20210323T130000
DTEND;TZID=America/New_York:20210323T140000
DTSTAMP:20260412T091934
CREATED:20210205T151853Z
LAST-MODIFIED:20210511T181115Z
UID:2447-1616504400-1616508000@ds.dfci.harvard.edu
SUMMARY:Data Science Zoominar: The Importance of Representative Samples in Clinical Trials
DESCRIPTION:Tuesday March 23\, 2021\n1:00PM Eastern Time \nA conversation with Timothy Rebbeck\nVincent L. Gregory\, Jr. Professor of Cancer Prevention\, Epidemiology\, Harvard T.H. Chan School Of Public Health\nProfessor\, Medical Oncology\, Dana-Farber Cancer Institute \nModerator: Rafael Irizarry \nYouTube Link: https://www.youtube.com/watch?v=Q4uBibxGf20
URL:https://ds.dfci.harvard.edu/event/data-science-zoominar-the-importance-of-representative-samples-in-clinical-trials/
CATEGORIES:Zoominar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2021/02/rebbeck_sq.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20210309T130000
DTEND;TZID=America/New_York:20210309T140000
DTSTAMP:20260412T091934
CREATED:20200921T180427Z
LAST-MODIFIED:20210511T181203Z
UID:2133-1615294800-1615298400@ds.dfci.harvard.edu
SUMMARY:Frontiers in Biostatistics: Distributed Statistical Learning and Inference in EHR and Other Healthcare Datasets
DESCRIPTION:Frontiers in Biostatistics Seminar\nMarch 9\, 2021\n1:00PM \nRui Duan\, PhD\nAssistant Professor of Biostatistics\nHarvard TH Chan School of Public Health \nDistributed Statistical Learning and Inference in EHR and Other Healthcare Datasets  \nAbstract: The growth of availability and variety of healthcare data sources has provided unique opportunities for data integration and evidence synthesis\, which can potentially accelerate knowledge discovery and enable better clinical decision making.  However\, many practical and technical challenges\, such as data privacy\, high-dimensionality and heterogeneity across different datasets\, remain to be addressed. In this talk\, I will introduce several methods for effective and efficient integration of electronic health records and other healthcare datasets. Specifically\, we develop communication-efficient distributed algorithms for jointly analyzing multiple datasets without the need of sharing patient-level data. Our algorithms are able to account for heterogeneity across different datasets. We provide theoretical guarantees for the performance of our algorithms\, and examples of implementing the algorithms to real-world clinical research networks. \nYouTube Link: https://www.youtube.com/watch?v=IscQ3ruxl1o
URL:https://ds.dfci.harvard.edu/event/frontiers-in-biostatistics-rui-duan/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2020/09/duan4x4.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20210223T130000
DTEND;TZID=America/New_York:20210223T140000
DTSTAMP:20260412T091934
CREATED:20210205T145646Z
LAST-MODIFIED:20210511T181245Z
UID:2441-1614085200-1614088800@ds.dfci.harvard.edu
SUMMARY:Data Science Zoominar: Diversity and Ethics in Genomics
DESCRIPTION:Tuesday February 23\, 2021\n1:00PM Eastern Time \nA conversation with Keolu Fox\, PhD\nAssistant Professor\, Department of Anthropology\, University of California\, San Diego \nModerator: Aedin Culhane \nYouTube Link: https://www.youtube.com/watch?v=VANlStOnFPY
URL:https://ds.dfci.harvard.edu/event/data-science-zoominar-diversity-and-ethics-in-genomics/
CATEGORIES:Zoominar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2021/02/fox3.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20210209T130000
DTEND;TZID=America/New_York:20210209T140000
DTSTAMP:20260412T091934
CREATED:20200921T175912Z
LAST-MODIFIED:20210511T181321Z
UID:2129-1612875600-1612879200@ds.dfci.harvard.edu
SUMMARY:Frontiers in Biostatistics: Group Sequential Design Assuming Delayed Benefit
DESCRIPTION:February 9\, 2021\n1:00PM ET \nKeaven Anderson\, PhD\nScientific AVP\, Methodology Research\, Biostatistics at Merck \nGroup Sequential Design Assuming Delayed Benefit \nAbstract: We consider an asymptotic approach to design of group sequential trials with a potentially delayed effects. Logrank\, weighted logrank tests and combination tests are of primary interest\, but we also consider restricted mean survival. The asymptotic approach allows both quick derivation of study design properties that are also easily verified using simulation. We rely heavily on work done by Tsiatis\, 1981 published while he was at the HSPH. The impact of a potential delay in treatment effect on timing of analyses\, study boundaries and sample size are demonstrated. The value of a robust design that is well powered under a variety of assumptions is emphasized. Open source software is provided for implementation. Given the current regulatory climate\, logrank testing may still be preferred for these trials\, but we hope that efficiencies and Type I error control associated with alternatives may make other options more acceptable for future consideration. \nYouTube Link: https://www.youtube.com/watch?v=DhwZOX5uMKU
URL:https://ds.dfci.harvard.edu/event/frontiers-in-biostatistics-keaven-anderson/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2020/09/anderson1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20210126T130000
DTEND;TZID=America/New_York:20210126T140000
DTSTAMP:20260412T091934
CREATED:20210119T133552Z
LAST-MODIFIED:20210511T181357Z
UID:2413-1611666000-1611669600@ds.dfci.harvard.edu
SUMMARY:Data Science Zoominar: Vaccine Prioritization Strategies
DESCRIPTION:Tuesday January 26\, 2021\n1:00PM ET \nA conversation with Daniel Larremore\nAssistant Professor\, Department of Computer Science at University of Colorado-Boulder and BioFrontiers Institute \nand \nKate Bubar\nStudent\, Department of Applied Mathematics\, University of Colorado-Boulder \nModerator: Rafael Irizarry \nRSVP at https://bit.ly/DSJan26 \nYouTube Link: https://www.youtube.com/watch?v=fJuHNNP8TLg
URL:https://ds.dfci.harvard.edu/event/data-science-zoominar-vaccine-prioritization-strategies/
CATEGORIES:Zoominar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2021/01/joint_pix.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20210112T130000
DTEND;TZID=America/New_York:20210112T140000
DTSTAMP:20260412T091934
CREATED:20200921T175311Z
LAST-MODIFIED:20210112T190625Z
UID:2123-1610456400-1610460000@ds.dfci.harvard.edu
SUMMARY:Frontiers in Biostatistics: Statistical Modeling and Adjustment for Sampling Biases
DESCRIPTION:Frontiers in Biostatistics Seminar\nJanuary 12\, 2021\n1:00PM \nJing Ning\, PhD\nAssociate Professor. Department of Biostatistics\nDivision of Quantitative Sciences\nThe University of Texas M.D. Anderson Cancer Center \nRegister at: https://bit.ly/FIBJan12 \nAbstract: Bias sampling mechanisms are commonly encountered in applications where the subjects in a target population are not given an equal chance to be selected\, either accidentally\, by natural circumstances\, or intentionally by design. Statistical methods not properly accounting for such a challenge often lead to invalid inferences. For example\, evidence combined from published studies may lead to overly optimistic conclusions due to publication bias\, and the well-known length bias can cause the screening to appear to be more successful than it really is. In this talk\, I will present our recent work to adjust the sampling biases in diverse applications such as the survivorship bias in prevalent cohort\, the self-reporting bias in longitudinal analysis and the publication bias in meta-analysis.
URL:https://ds.dfci.harvard.edu/event/frontiers-in-biostatistics-jing-ning/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2020/09/ning.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201221T140000
DTEND;TZID=America/New_York:20201221T150000
DTSTAMP:20260412T091934
CREATED:20201211T185808Z
LAST-MODIFIED:20201222T214128Z
UID:2361-1608559200-1608562800@ds.dfci.harvard.edu
SUMMARY:Data Science Zoominar: Understanding COVID-19 Vaccine Trial Designs and Current Results
DESCRIPTION:Monday December 21\, 2020\n2:00PM ET \nUnderstanding COVID-19 Vaccine Trial Designs and Current Results \nA conversation with David Benkeser\nAssistant Professor\, Biostatistics and Bioinformatics\nRollins School of Public Health\, Emory University \nModerator: Rafael Irizarry \nRSVP at https://bit.ly/DSDec21
URL:https://ds.dfci.harvard.edu/event/data-science-zoominar-understanding-covid-19-vaccine-trial-designs-and-current-results/
CATEGORIES:Zoominar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2020/12/benkeser_sq.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201215T130000
DTEND;TZID=America/New_York:20201215T140000
DTSTAMP:20260412T091934
CREATED:20201119T201351Z
LAST-MODIFIED:20201215T204139Z
UID:2324-1608037200-1608040800@ds.dfci.harvard.edu
SUMMARY:Data Science Zoominar: Data-Driven Policy in Puerto Rico
DESCRIPTION:Tuesday December 15\, 2020\n1:00PM ET \nData-Driven Policy in Puerto Rico \nA conversation with Arnaldo Cruz\nDirector of Research and Policy of the Financial\nOversight and Management Board of Puerto Rico\nCo-founder of ABRE Puerto Rico \nModerator: Rafael Irizarry \nRSVP at https://bit.ly/DSDec15
URL:https://ds.dfci.harvard.edu/event/data-science-zoominar-data-driven-policy-in-puerto-rico/
CATEGORIES:Zoominar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2020/11/cruz.jpeg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201214T150000
DTEND;TZID=America/New_York:20201214T163000
DTSTAMP:20260412T091934
CREATED:20201130T190048Z
LAST-MODIFIED:20201215T114236Z
UID:2341-1607958000-1607963400@ds.dfci.harvard.edu
SUMMARY:DF/HCC Cancer Data Science Program &Harvard Chan Bioinformatics CoreJoint Symposium on scRNAseq Methodology
DESCRIPTION:Monday\, December 14\, 3:00-4:30 PM ET  \nRSVP https://bit.ly/CDSBioDec14 \nSpeakers: \n\nAedin Culhane\, Senior Research Scientist\, Dana-Farber Cancer Institute and Harvard T.H. Chan School of Public Health\nIsabella Grabski\, PhD Student in Biostatistics\, Harvard University\nProbabilistic gene barcodes identify cell-types in single-cell RNA-sequencing data\nShannan Ho Sui\, Senior Research Scientist\, Harvard T.H. Chan School of Public Health\nRadhika S Khetani\, Research Scientist\, Harvard T.H. Chan School of Public Health\nPeter Kharchenko\, Associate Professor of Biomedical Informatics\, Harvard Medical School\nX. Shirley Liu\, Professor\, Harvard T.H. Chan School of Public Health\nAnalysis of Single-Cell Data to Model Tumor and Immune Gene Regulation\nLuca Pinello\, Associate Professor of Pathology\, Harvard Medical School and Mass General Cancer Center\nTrajectory inference and visualization of single cell data
URL:https://ds.dfci.harvard.edu/event/df-hcc-cancer-data-science-program-harvard-chan-bioinformatics-corejoint-symposium-on-scrnaseq-methodology/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2020/11/dfhhc-joint-symp-icon.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201208T130000
DTEND;TZID=America/New_York:20201208T140000
DTSTAMP:20260412T091934
CREATED:20201113T144308Z
LAST-MODIFIED:20201209T120537Z
UID:2302-1607432400-1607436000@ds.dfci.harvard.edu
SUMMARY:Data Science Zoominar: Data Science Books\, Online Courses\, Podcasts\, and Blogs
DESCRIPTION:Tuesday December 8\, 2020\n1:00PM ET \nData Science Books\, Online Courses\, Podcasts\, and Blogs \nA conversation with\nRoger Peng\, PhD\nJohns Hopkins Bloomberg School of Public Health \nModerator: Rafael Irizarry \nRSVP at https://bit.ly/DSDec8
URL:https://ds.dfci.harvard.edu/event/data-science-zoominar-data-science-books-online-courses-podcasts-and-blogs/
CATEGORIES:Zoominar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2020/11/peng7_square.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201207T130000
DTEND;TZID=America/New_York:20201207T143000
DTSTAMP:20260412T091934
CREATED:20201111T004449Z
LAST-MODIFIED:20201208T005647Z
UID:2276-1607346000-1607351400@ds.dfci.harvard.edu
SUMMARY:Postdoctoral Open House
DESCRIPTION:The Dana-Farber Cancer Institute Department of Data Science announces our first annual Postdoc Open House. Join us on Monday\, December 7th at 1:00PM EST to explore postdoctoral opportunities in cancer research. Participating faculty include:  \n\nRafael Irizarry\, PhD\, Professor and Department Chair\nX. Shirley Liu\, PhD\, Professor\nGiovanni Parmigiani\, PhD\, Professor\nFranziska Michor\, PhD\, Professor\nLorenzo Trippa\, PhD\, Associate Professor\nHeng Li\, PhD\, Assistant Professor\nSahand Hormoz\, PhD\, Assistant Professor\nNabihah Tayob\, PhD\, Member of the Faculty\n\nYou will also meet current and former department postdocs\, and learn about the resources available at Dana-Farber and throughout the Boston area.  \nDue to limited space\, we request that participants are actively seeking a postdoctoral position. Please complete this form to request event admission. \nWe look forward to welcoming you and introducing our department!  \nOpen postdoctoral positions are posted on our website.
URL:https://ds.dfci.harvard.edu/event/postdoctoral-open-house/
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2020/11/website_square.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201117T130000
DTEND;TZID=America/New_York:20201117T140000
DTSTAMP:20260412T091934
CREATED:20201013T194550Z
LAST-MODIFIED:20201117T190533Z
UID:2191-1605618000-1605621600@ds.dfci.harvard.edu
SUMMARY:Data Science Zoominar: Communicating Statistical Findings Effectively
DESCRIPTION:Tuesday November 17\, 2020\n1:00PM ET \nCommunicating Statistical Findings Effectively \nA conversation with\nProfessor Sir David Spiegelhalter\nChair\, Winton Centre for Risk and Evidence Communication\nCentre for Mathematical Sciences\nAuthor: The Art of Statistics \nModerator: Rafael Irizarry \nRSVP at https://bit.ly/DSNov17
URL:https://ds.dfci.harvard.edu/event/data-science-zoominar-david-spiegelhalter/
CATEGORIES:Zoominar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2020/10/spiegelhalter_square.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201110T130000
DTEND;TZID=America/New_York:20201110T140000
DTSTAMP:20260412T091934
CREATED:20201030T123107Z
LAST-MODIFIED:20201111T005540Z
UID:2226-1605013200-1605016800@ds.dfci.harvard.edu
SUMMARY:Data Science Zoominar: Election Forecasting: How We Succeeded Brilliantly\, Failed Miserably\, or Landed Somewhere in Between
DESCRIPTION:Tuesday November 10\, 2020\n1:00PM ET \nElection Forecasting: How We Succeeded Brilliantly\, Failed Miserably\, or Landed Somewhere in Between \nA conversation with\nAndrew Gelman\, Ph.D.\nProfessor of Statistics and Political Science\nColumbia University \nModerator: Rafael Irizarry \nRSVP at https://bit.ly/DSNov10
URL:https://ds.dfci.harvard.edu/event/data-science-zoominar-election-forecasting-how-we-succeeded-brilliantly-failed-miserably-or-landed-somewhere-in-between/
CATEGORIES:Zoominar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2020/10/gelman_square.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201020T130000
DTEND;TZID=America/New_York:20201020T140000
DTSTAMP:20260412T091934
CREATED:20200921T155020Z
LAST-MODIFIED:20201109T234121Z
UID:2118-1603198800-1603202400@ds.dfci.harvard.edu
SUMMARY:Data Science Zoominar: Data Science and Academic Leadership
DESCRIPTION:Tuesday October 20\, 2020\n1:00PM ET \nData Science and Academic Leadership \nA conversation with F. DuBois Bowman\, PhD\nDean of the University of Michigan School of Public Health \nModerator: Rafael Irizarry \nVideo available on our YouTube Channel.
URL:https://ds.dfci.harvard.edu/event/data-science-zoominar-f-dubois-bowman/
CATEGORIES:Zoominar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2020/09/SPH_Dean_DuBois_Bowman_4x4.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201015T130000
DTEND;TZID=America/New_York:20201015T140000
DTSTAMP:20260412T091934
CREATED:20201008T172433Z
LAST-MODIFIED:20201019T155448Z
UID:2174-1602766800-1602770400@ds.dfci.harvard.edu
SUMMARY:Computational Biology of DNA Repair in Cancer
DESCRIPTION:Data Science Seminar \nOctober 15\, 2020\n1:00PM ET \nDominik Glodzik\, PhD\nRepare Therapeutics \nZoom link: https://bit.ly/DSOct15 \nAbstract: Whole genome sequences contain within them signatures of mutational processes. In particular\, some of the mutation signatures relate to impaired DNA-repair in cancer cells. Accurate measurement of mutation signatures reveals the role of DNA-repair deficiencies in etiology and progression of cancer. \nWe extended the computational methods for analysis of mutation signatures in order to describe patterns of chromosomal rearrangements. In particular\, the rearrangement signatures enable the assessment of proficiency of homologous recombination (HR). HRDetect\, an algorithm we developed\, predicts probability of HR-deficiency\, and is based on holistic portrayal of mutational signatures across different classes of somatic mutations. Around 20% of breast cancers contain signatures of HR-deficiency\, and this group is wider than the group of carriers of BRCA1/2 mutations. By contrast to adult cancers\, pediatric cancers with known DNA-repair defects display variation of mutational signatures\, hinting at tissue-specificity of mutational signatures. Finally\, in the chromosomally unstable cancers\, we identified structural rearrangements\, in coding and non-coding regions\, that can act as cancer drivers. Altogether\, these results indicate that computational assessment of DNA-repair capacity of tumor cells is now possible. The methods will be crucial to understanding of the DNA-repair mechanisms and tissue-specificity of mutational processes. \nBio: Dominik Glodzik received his PhD in Computational Biology from the University of Edinburgh\, and held a postdoctoral position at Wellcome Trust Sanger Institute\, before moving to a staff scientist position at Memorial Sloan Kettering Cancer Center. Currently he is a Principal Bioinformatician at Repare Therapeutics in Cambridge.
URL:https://ds.dfci.harvard.edu/event/computational-biology-of-dna-repair-in-cancer/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2020/10/glodzik.jpeg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201013T130000
DTEND;TZID=America/New_York:20201013T140000
DTSTAMP:20260412T091934
CREATED:20200430T165238Z
LAST-MODIFIED:20201109T234833Z
UID:894-1602594000-1602597600@ds.dfci.harvard.edu
SUMMARY:Constructing Confidence Interval for RMST under Group Sequential Setting
DESCRIPTION:Frontiers in Biostatistics Seminar\nOctober 13\, 2020\n1:00PM \nLu Tian\, PhD\nAssociate Professor of Biomedical Data Science in the School of Medicine\nStanford University \nIt is appealing to compared survival distributions based on restricted mean survival time (RMST)\, since it generates a clinically interpretable summary of the treatment effect\, which can be estimated nonparametrically without assuming restrictive model assumptions such as the proportional hazards assumption. However\, there are special challenges in designing and analyzing group sequential study based on RMST\, because the truncation timepoint of the RMST in the interim analysis often differs from that in the final analysis. A valid test controls the unconditional type one error has been developed in the past. However\, there is no appropriate statistical procedure for constructing the confidence interval for the treatment effect measured by a contrast in RMST\, while it is crucial for informative clinical decision making. In this talk\, I will review some important design issues for study based on RMST. I will then discuss how to conduct hypothesis testing and how to construct confidence intervals for the difference RMST in a group sequential setting. Examples and numerical studies will be presented to illustrate the method. \nA recording of this seminar is available on your YouTube Channel.
URL:https://ds.dfci.harvard.edu/event/constructing-confidence-interval-for-rmst-under-group-sequential-setting/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2020/04/lutian.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200930T130000
DTEND;TZID=America/New_York:20200930T163000
DTSTAMP:20260412T091934
CREATED:20200429T164355Z
LAST-MODIFIED:20201102T114527Z
UID:659-1601470800-1601483400@ds.dfci.harvard.edu
SUMMARY:Marvin Zelen Symposium 2020
DESCRIPTION:In December of 2019\, we planned the next Marvin Zelen Symposium for March of 2020. At that point\, the year ahead seemed to be a data spectacle waiting to happen. Think about all the events planned for 2020! Here’s what we wrote. \nThe topic of this year’s Marvin Zelen Symposium has to do with the year itself — 2020. This first year of a new decade brings with it statistical spectacles on a massive scale. From the Decennial Census and the Presidential Election in the US\, to the 50th anniversary of Earth Day\, to the Summer Olympics in Tokyo. These big events are bristling with data and its analyses — shaping how they are experienced\, discussed\, debated\, and even litigated. Their time scales range from fractions of a second (the difference between gold and silver) to millions of years (the length of the geological record needed to understand our changing climate). They can be influenced by the actions of one person or the cumulative behaviors of hundreds of millions (as voters\, as competitors\, as spectators\, as consumers). The Marvin Zelen Symposium will look at the major data spectacles of 2020\, each one having synergy with the others\, but also adding something new in our understanding of how data establish and reinforce systems of power on our planet. \nWell\, since we organized the 2020 Symposium\, the entire world has changed. The original Zelen event was replaced with a “Zoomposium” on Covid-19\, attracting nearly 500 attendees\, and we moved the program covering everything from the Olympics to Earth Day to September\, 2020 — this month. \nBut now that the date of the rescheduled event is upon us\, think about what Covid-19 has done to many of the events mentioned in our abstract — we have seen everything from complications to cancellations. Still\, we have decided to go forward with the 2020 Zelen Symposium as we had originally planned it. \nWe expect the difficulties of this year will inflect each of the talks on the program. Marvin Zelen embraced the complexity of data and its relationship to lived experience — the same is true for this edition of the Symposium bearing his name. \nSpeakers: \n\nBen Hansen\, University of Michigan\, “The Test of Heightened Election-Year Scrutiny and the Tests in your Table 1”\n\nBrendan Nyhan\, Dartmouth College\, “Selective Exposure to Misinformation: Understanding the Consumption of False News and Anti-Vaccine Content Online”\nRegina Nuzzo\, Gallaudet University\, “Brain-Hacking Stats Communication: A Quick Tour”\nAmy O’Hara\, Georgetown University\, “The 2020 Census: Expected vs. Actual”\nAndrew Revkin\, Columbia University\, “Taming Social Media for Constructive Climate Crosstalk”\n\nCharles Stewart\, Massachusetts Institute of Technology\, “Puzzling Through Demand for Mail Voting in the 2020 Election”\nDaniel Webb\, United States Olympic Committee\, “Forecasting the Olympic Games: Team USA’s Medal Prediction Models”\n\nJeremy White\, New York Times\, “Visualizing the Performances of the World’s Greatest Athletes”\n\n\nRegister by September 29\, 2020. \nAudience is capped at 500 participants. Participate on Twitter: #Zelen2020.
URL:https://ds.dfci.harvard.edu/event/marvin-zelen-symposium-2020/
CATEGORIES:Conference
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2020/04/logo_fall_narrow_small.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200929T130000
DTEND;TZID=America/New_York:20200929T140000
DTSTAMP:20260412T091934
CREATED:20200922T173720Z
LAST-MODIFIED:20200923T183848Z
UID:2146-1601384400-1601388000@ds.dfci.harvard.edu
SUMMARY:3D Spatial Organization Within Tumors
DESCRIPTION:Data Science Seminar \nSeptember 29\, 2020\n1:00PM ET \nMartin Aryee\, PhD\nAssistant Professor of Pathology\, Harvard Medical School\nAssistant Molecular Pathologist\, Massachusetts General Hospital \nZoom link: https://dfci.zoom.us/j/95524743149?pwd=SzN4cjJZUnhsNVl3dXNmZjZ1N3F4QT09 \nAbstract: The spatial organization of biological systems can impart additional functionality beyond that of the individual components. This is true at a range of scales – from cells in a tissue to individual genes and regulatory elements in a single genome. High-throughput assays that permit spatial measurements have advanced greatly in the past decade and revealed oncogenic architectural alterations in tumors at the tissue\, cellular and chromosome levels. Here I will discuss tumor spatial organization in gastrointestinal malignancies at two different scales. First\, I will describe how we used single-cell RNA-Seq and RNA in situ hybridization in pancreatic cancer to identify cell state and tissue architecture changes induced by contact with stromal cancer-associated fibroblasts (CAFs). We analyzed the spatial architecture of cell states in 195 pancreatic tumors\, mapping over 300\,000 individual cancer cells. We were able to classify different types of tumor glands based on their cell-type composition\, and show that these functional units can be used to characterize tumors in ways not evident from analyses of dissociated single cells. Second\, I will discuss findings from a recent study of 3D genome organization within colon cancer cell nuclei. We found oncogenic changes at the level of regulatory chromatin loops and topologically associated domains (TADs)\, but the most surprising and striking change involves a large-scale repackaging of heterochromatin that appears to restrain tumor progression\, representing a failed anti-tumor epigenetic brake.
URL:https://ds.dfci.harvard.edu/event/3d-spatial-organization-within-tumors/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2020/09/aryee.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200922T140000
DTEND;TZID=America/New_York:20200922T150000
DTSTAMP:20260412T091934
CREATED:20200915T212158Z
LAST-MODIFIED:20200917T142852Z
UID:2101-1600783200-1600786800@ds.dfci.harvard.edu
SUMMARY:Cancer Development\, Heterogeneity and Dynamics from Premalignancy to Drug Refractory Disease
DESCRIPTION:Data Science Seminar \nSeptember 22\, 2020\n2:00PM ET \nIgnaty Leshchiner\, PhD\nPostdoctoral Fellow\, Harvard Medical School/Brigham and Women’s Hospital \nZoom link: http://bit.ly/DSSept22 \nAbstract: \nReal-time study of tumor emergence and progression in patients will help predict and ultimately change the course of the patient’s disease. This could be achieved by inferring genotypes of heterogeneous cell populations within the tumor\, their fitness\, growth rates\, corresponding expression patterns and drug tolerance states. We have developed a set of computational methods to infer the order of tumor-initiating events and to follow the dynamics and competition of cancer cell populations during disease progression and treatment. The package\, PhylogicNDT\, uses tumor genomic data to reconstruct the process of tumor formation\, natural growth kinetics\, competition and spread of resistance clones. We applied this package to 2\,658 primary cancers to reconstruct developmental trajectories and history of common tumor types in premalignancy and early malignancy state; reconstruct cancer cell populations and growth rates\, fitness and kinetics of individual clones during natural progression of leukemia in vivo; analyze spatial progression of resistance clones and find new resistance mechanisms in a large cohort of rapid autopsy cases. By integrating blood biopsy (ctDNA)\, solid tissue biopsy and autopsy data we show that resistance often emerges in multiple distant metastatic sites simultaneously\, with evidence of multiple resistance mutations present in the blood’s ctDNA at the same time. Finally\, we combine bulk and single cell sequencing data to help identify genetically distinct clones and explain their phenotypic differences. We envision that treatment decisions will improve with better understanding of tumor development\, clonal structure and microenvironment\, and the path tumor takes to become malignant and progress after treatment.
URL:https://ds.dfci.harvard.edu/event/cancer-development-heterogeneity-and-dynamics-from-premalignancy-to-drug-refractory-disease/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2020/09/10221_Facebook_360x360.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200915T130000
DTEND;TZID=America/New_York:20200915T140000
DTSTAMP:20260412T091934
CREATED:20200708T162715Z
LAST-MODIFIED:20201109T234809Z
UID:1804-1600174800-1600178400@ds.dfci.harvard.edu
SUMMARY:A New Hybrid Phase I-II-III Clinical Trial Paradigm
DESCRIPTION:Frontiers in Biostatistics Seminar \nTuesday September 15\, 2020 at 1:00PM Eastern Time \nPeter F. Thall\, PhD\nDepartment of Biostatistics\nUniversity of Texas M.D. Anderson Cancer Center \nAbstract: Conventional evaluation of a new drug\, 𝐴\, is done in three phases. Phase I relies on toxicity to determine a “maximum tolerable dose” (MTD) of 𝐴\, in phase II it is decided whether 𝐴 at the MTD is “promising” in terms of response probability\, and if so a large randomized phase III trial is conducted to compare 𝐴 to a control treatment\, 𝐶\, based on survival time or progression free survival time. This paradigm has many flaws. The first two phases may be combined by conducting a phase I-II trial\, which chooses an optimal dose based on both efficacy and toxicity\, with evaluation of 𝐴 at the optimal phase I-II dose then done in phase III. In this talk\, I will describe a new paradigm\, motivated by the possibility that the optimal phase I-II dose may not maximize mean survival time with 𝐴. A hybrid phase I-II-III design is presented that allows the optimal phase I-II dose of 𝐴 to be re-optimized based on survival time data after the first stage of phase III. The hybrid design relies on a mixture model for the survival time distribution as a function of efficacy\, toxicity\, and dose. A simulation study is presented to evaluate the design’s properties\, including comparison to the more conventional approach that does not re-optimize the dose of 𝐴 in phase III. \nA recording of this seminar is available on your YouTube Channel.
URL:https://ds.dfci.harvard.edu/event/a-new-hybrid-phase-i-ii-iii-clinical-trial-paradigm/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2020/07/thall_peter.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200902T130000
DTEND;TZID=America/New_York:20200902T140000
DTSTAMP:20260412T091934
CREATED:20200811T135007Z
LAST-MODIFIED:20201109T234620Z
UID:1913-1599051600-1599055200@ds.dfci.harvard.edu
SUMMARY:Data Science Zoominar: Data Visualization Literacy: Avoiding common mistakes and recognizing deceitful practices
DESCRIPTION:Wednesday September 2\, 2020\n1:00PM ET \nA conversation with Alberto Cairo\nKnight Chair in Visual Journalism at the School of Communication of the University of Miami\nModerator: Rafael Irizarry \nA recording of the talk is available on our YouTube channel. \n  \n 
URL:https://ds.dfci.harvard.edu/event/data-science-zoominar-data-visualizacion-literacy-avoiding-common-mistakes-and-recognizing-deceitful-practices/
CATEGORIES:Zoominar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2020/08/Alberto_Cairo-02.jpg
END:VEVENT
END:VCALENDAR