Events

  • October 5, 2020 12:00pm to October 8, 2020 5:00pm

    Duke University School of Medicine Virtual Research Week

    Location: Zoom - https://duke.zoom.us/j92060873004 All faculty, staff, trainees and students welcome Monday, October 5Keynote Lectures: 12 - 1 p.m.12:05 - 12:20 - Kafui Dzirasa, M.D., Ph.D., Associate Professor of Neurosurgey and Neurobiology12:20 - 12:35 - Clare Smith, Ph.D., Assistant Professor of Molecular Genetics and Microbiology12:35 - 12:50 - Ed Miao, M.D., Ph.D., Professor of Immunology Tuesday, October 6Robert J. Lefkowitz, M.D., Distinguished Lecture12 -1 p.m.Helen Hobbs, M.D., Investigator at Howard Hughes Medical Institute and Professor of Internal Medicine and Molecular Genetics at University of Texas Southwestern Medical Center Wednesday, October 7Keynote Lectures: 12 - 1 p.m.12:05 - 12:20 - Kanecia Zimmerman, M.D., MPH, Associate Professor of Pediatrics12:20 - 12:35 - Diego Bohorquez, Ph.D., Assistant Professor of Medicine, Pathology and Neurobiology12:35 - 12:50 - Ranee Chatterjee, M.D., Associate Professor of Medicine Thursday, October 8Clinical Research Keynote12 - 1 p.m. - Lily Peng, M.D., Ph.D., Product Manager of Google Brain, Co-Founder of Nano Precision MedicalPoster Session4 - 5 p.m. - Featuring presentations of winnning posters in Clinical Research and Basic Science competitions More information about Research Week

  • October 6, 2020 11:00am to 12:00pm

    Enabling True Multi-omics: Single-Cell Genotypes and Phenotypes with the Tapestri Platform

    Location: Zoom Discover how the Tapestri Platform enables co-detection of SNVs, CNVs, and proteins from the same cell using a single workflow, providing a true multi-omics approach for deeper insight into systems biology and patterns of tumor/clonal evolution, therapy response, and resistance. Registration required

  • October 6, 2020 12:00pm to 1:00pm

    Robert J. Lefkowitz, MD, Distinguished Lecture

    Location: Zoom This is part of the second annual Duke University School of Medicine Research Week, which will be held virtually from Monday, October 5 - Friday, October 9. See full details about Research Week

  • October 8, 2020 12:00pm to 1:00pm

    Clinical Keynote Lecture

    Location: Zoom This is part of the second annual Duke University School of Medicine Research Week, which will be held virtually from Monday, October 5 - Friday, October 9. See full details about Research Week

  • October 12, 2020 12:00pm to 1:00pm

    Explainable Artificial Intelligence for Biology and Health

    Location: All fall 2020 seminars will be remote: Zoom ID-939-6480-6446 The Computational Biology Seminar is a weekly series of seminars on topics in computational biology presented by invited speakers, Duke faculty, and CBB doctoral and certificate graduate students. Host: Miko Liu

  • October 13, 2020 12:00pm to 1:00pm

    NSF Grants for Faculty Workshop

    Location: Zoom; link will be provided to registrants This workshop provides step-by-step guidance for faculty writing standard NSF research and education grants. Open to Duke faculty and research staff. Registration required

  • October 16, 2020 12:00pm to 1:00pm

    NSF S-STEM Informational Session

    Location: Zoom (link will be sent to registrants) The NSF S-STEM program funds scholarships for low-income students. It is an institutionally-limited submission, allowing Duke to submit one proposal per degree-granting school/college for either undergraduate or graduate degrees. This informational session will provide an overview of the S-STEM program and cover what to expect in the limited submission process. Open to Duke faculty and research staff. Registration required

  • October 16, 2020 2:00pm to 3:30pm

    An Overview of Risk Prediction and Classification in Omics Settings Part I

    Location: Zoom (link will be sent to registrants) This workshop has two objectives. First, it seeks to develop an understanding of risk prediction and classification in the Omics setting. Second, for researchers who plan to develop risk models, this workshop seeks to provide concrete steps for study design, analysis, and interpretation. To accomplish these goals, we will discuss how different aspects of a statistical model can provide measures of association or measures of predictive accuracy. This distinction is important in understanding how developing a model for association/etiology/causal inference is conceptually different from using the model to predict. We will then discuss risk models in the conventional setting: larger sample sizes with a smaller number of predictors. We will cover study design, statistical models, and performance metrics. The workshop seeks to develop an appreciation of challenging considerations in the field, but also seeks to provide clear steps on how to proceed. Finally, we will review areas of active research and in what direction the field is moving. After establishing foundations, we will move into the Omics realm, which is characterized by smaller samples sizes and thousands of predictors. We will review current best practices with an emphasis on estimating performance. This course will not include any hands-on coding because of time limitations, but this will be the topic of a future course. The workshop will also be useful to those interested in general risk models not specific to Omics. Register

  • October 19, 2020 12:00pm to 1:00pm

    Predicting the effects of engineering immune cells using system biology models

    Location: All fall 2020 seminars will be remote: Zoom ID-939-6480-6446 The Computational Biology Seminar is a weekly series of seminars on topics in computational biology presented by invited speakers, Duke faculty, and CBB doctoral and certificate graduate students. Host: Rachel Kositsky

  • October 23, 2020 2:00pm to 3:30pm

    An Overview of Risk Prediction and Classification in Omics Settings Part II

    Location: Zoom (link will be sent to registrants) This workshop has two objectives. First, it seeks to develop an understanding of risk prediction and classification in the Omics setting. Second, for researchers who plan to develop risk models, this workshop seeks to provide concrete steps for study design, analysis, and interpretation. To accomplish these goals, we will discuss how different aspects of a statistical model can provide measures of association or measures of predictive accuracy. This distinction is important in understanding how developing a model for association/etiology/causal inference is conceptually different from using the model to predict. We will then discuss risk models in the conventional setting: larger sample sizes with a smaller number of predictors. We will cover study design, statistical models, and performance metrics. The workshop seeks to develop an appreciation of challenging considerations in the field, but also seeks to provide clear steps on how to proceed. Finally, we will review areas of active research and in what direction the field is moving. After establishing foundations, we will move into the Omics realm, which is characterized by smaller samples sizes and thousands of predictors. We will review current best practices with an emphasis on estimating performance. This course will not include any hands-on coding because of time limitations, but this will be the topic of a future course. The workshop will also be useful to those interested in general risk models not specific to Omics. Register

  • October 26, 2020 12:00pm to 1:00pm

    CBB Seminar

    Location: All fall 2020 seminars will be remote: Zoom ID-939-6480-6446 The Computational Biology Seminar is a weekly series of seminars on topics in computational biology presented by invited speakers, Duke faculty, and CBB doctoral and certificate graduate students. Host: Amy Goldberg

  • October 30, 2020 2:00pm to 3:30pm

    An Overview of Risk Prediction and Classification in Omics Settings Part III

    Location: Zoom (link will be sent to registrants) This workshop has two objectives. First, it seeks to develop an understanding of risk prediction and classification in the Omics setting. Second, for researchers who plan to develop risk models, this workshop seeks to provide concrete steps for study design, analysis, and interpretation. To accomplish these goals, we will discuss how different aspects of a statistical model can provide measures of association or measures of predictive accuracy. This distinction is important in understanding how developing a model for association/etiology/causal inference is conceptually different from using the model to predict. We will then discuss risk models in the conventional setting: larger sample sizes with a smaller number of predictors. We will cover study design, statistical models, and performance metrics. The workshop seeks to develop an appreciation of challenging considerations in the field, but also seeks to provide clear steps on how to proceed. Finally, we will review areas of active research and in what direction the field is moving. After establishing foundations, we will move into the Omics realm, which is characterized by smaller samples sizes and thousands of predictors. We will review current best practices with an emphasis on estimating performance. This course will not include any hands-on coding because of time limitations, but this will be the topic of a future course. The workshop will also be useful to those interested in general risk models not specific to Omics. Register

  • November 2, 2020 12:00pm to 1:00pm

    CBB Seminar

    Location: All fall 2020 seminars will be remote: Zoom ID-939-6480-6446 The Computational Biology Seminar is a weekly series of seminars on topics in computational biology presented by invited speakers, Duke faculty, and CBB doctoral and certificate graduate students. Host: Lingchong You

  • November 9, 2020 12:00pm to 1:00pm

    Probabilistic Graphical Models for Genetic and Genomic Data

    Location: All fall 2020 seminars will be remote: Zoom ID-939-6480-6446 The Computational Biology Seminar is a weekly series of seminars on topics in computational biology presented by invited speakers, Duke faculty, and CBB doctoral and certificate graduate students.

  • November 16, 2020 12:00pm to 1:00pm

    Towards AI-driven precision medicine

    Location: All fall 2020 seminars will be remote: Zoom ID-939-6480-6446 The Computational Biology Seminar is a weekly series of seminars on topics in computational biology presented by invited speakers, Duke faculty, and CBB doctoral and certificate graduate students. Host: Miko Liu