APR 06, 2016 10:30 AM PDT

Microbiome Biomarker Discovery for Diagnostic and Therapeutic Applications

Speaker
  • Director of Bioinformatics, Second Genome, Inc.
    Biography
      Todd DeSantis is Second Genome Co-founder and Senior Director of Bioinformatics. Todd has 17 years of experience designing and implementing bioinformatics solutions for analyzing microbial community dynamics. At Lawrence Berkeley National Laboratory he led the development of novel microbiome assays and analysis pipelines as a Molecular Microbial Ecology Software Developer. He is the chief architect of Greengenes™, an international effort to catalog global microbial diversity that provides microbial ecologists with reference databases for DNA quality assessment, alignment and classification. Todd also served as an analyst for the NIH Human Microbiome Project and has published over 60 scientific papers. At Second Genome, he manages all informatics work including identifying and recruiting microbiome scientist leaders, integration of multi-omics pipelines, cloud deployment for big-data analytics, and therapeutic pathway discovery.

      At Lawrence Berkeley National Laboratory he architected novel microbiome assays and analysis pipelines as a Molecular Microbial Ecology Software Developer.

      He also designed and manages Greengenes, an international effort to catalog global microbial diversity that provides microbial ecologists with resources and online tools for DNA quality assessment, alignment and classification. Todd also served as an analyst for the NIH Human Microbiome Project and has authored over 50 manuscripts.

      At Second Genome, he manages all bioinformatics work and oversees the planning, performance and interpretation of projects and the production of data reports.

    Abstract

    Microbiome discovery efforts are underway in multiple disease areas.  Challenges exist in sample collection, processing, assay selection and bioinformatics.  Therefore heterogeneity exists in published findings for biomarkers.  Using the Amazon cloud and machine learning, sets of consistent biomarkers can be observed in biospecimens from diseased subjects that differentiate them from healthy controls.  The benefits of applying consistent assays with internal controls within each test will be discussed.  Since the same data collected for diagnostic discovery, also aids in therapeutic hypotheses generation, a platform that outputs both will be outlined.
     
    Learning Objectives:
    - Be able to list at least 2 disease areas where microbiome analyses are applied.
    - Be able to list at least 2 sources of variation in biomarker discovery in microbiome analyses.
    - Be able to identify the benefits of internal controls in evaluating assay value.
     


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