FlowCAP Summit 2010, U.S. NIH Campus

FlowCAP Summit 2010, U.S. NIH Campus


  • Flyer [pdf]
  • Agenda [pdf]
  • Attendees [pdf]
  • Meeting Summary [pdf]
  • Preliminary Results [pdf]

  • Talks

    Importance of FlowCAP from the DAIT/NIH Perspective
    Charles Hackett, Division of Allergy, Immunology, and Transplantation, NIAID, NIH

    FlowCAP: history, goals, and design of FlowCAP-I
    Richard H. Scheuermann, U.T. Southwestern Medical Center [Slides]

    Rapid Cell Population Identification in Flow Cytometry Data
    Ryan Brinkman on behalf of Nima Aghaeepour, University of British Columbia [Abstract] [Slides]

    Automatic determination of the number of mixture components in Flow Cytometry with Variational Bayes
    Hannes Bretschneider, Humboldt-Universitat zu Berlin [Abstract] [Slides]

    GPU accelerated Bayesian mixture models for FCM analysis
    Cliburn Chan, Duke University [Abstract] [Slides]

    flowMerge: Merging mixture components for automated gating of flow cytometry data
    Greg Finak, Fred Hutchinson Cancer Research Center [Abstract] [Slides]

    Flow Cytometry Data Assessment with L2 Discrepancy Learning Process: Analysis and Visualization
    Faysal Khettabi, British Columbia Cancer Agency [Abstract] [Slides]

    On the use of NMF and curvHDR to cluster flow cytometry data
    Joe Maisog, Medical Numerics, Inc. / Georgetown University MedicalCenter [Abstract] [Slides]

    Automated High-dimensional Cytometric Data Analysis
    Philip L. De Jager, Harvard Medical School [Abstract] [Slides]

    SWIFT: Scalable Weighted Iterative Flow-clustering Technique
    Iftekhar Naim, University of Rochester [Abstract] [Slides]

    Self-organizing Maps for Flow Cytometry Data Analysis
    Radina Nikolic, University of Oxford and British Columbia Institute of Technology (BCIT) [Abstract] [Slides]

    FLOCK: a density-based clustering method for automated identification and comparison of cell populations in high-dimensional flow cytometry data
    Yu Qian, Southwestern Medical Center [Abstract] [Slides]

    Support Vector Machines for classification of flow data
    John Quinn, TreeStar, Inc [Abstract] [Slides]

    Misty Mountain - A Parallel Clustering Method. Application to Fast Unsupervised Flow Cytometry Gating
    Istvan Sugar, Mt. Sinai School of Medicine [Abstract] [Slides]

    SamSPECTRAL: Efficient spectral clustering on flow cytometry data
    Habil Zare, British Columbia Cancer Agency [Abstract] [Slides]

    Keynote address
    Coherent Single Cell Analysis in the 21st Century: ROFLMAO
    Mario Roederer, National Institutes of Health

    FlowCAP-I: Results
    Ryan Brinkman, British Columbia Cancer Agency [Slides]

    FlowCAP-I Debrief: What worked and what didn't work
    Richard H. Scheuermann, U.T. Southwestern Medical Center [Slides]

    Comparative Metrics: Measuring the quality of a classification method without a known ground truth
    Adam Triestar, TreeStar, Inc

    FlowCAP-II: comparative metrics
    Jill Schoenfeld, TreeStar, Inc

    FlowCAP-II: Dataset classification and identification of important gaps in datasets used for FlowCAP-I
    Richard H. Scheuermann, U.T. Southwestern Medical Center

    FlowCAP-II: Design and Funding
    Ryan Brinkman, British Columbia Cancer Agency

    This meeting was generously supported by the U.S. National Institute of Health (NIH)