utsw

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Research Interests

My lab explores two biomedical themes. One series of projects probes molecular networks that regulate cell death in vivo through exploration and discovery of relevant genetic determinants. We examine gene-directed programs that specify programmed and unprogrammed cell death.  Our approaches primarily include whole animal screens and high throughput gene silencing platforms in the Drosophila model.  A second organizing theme is designed to illuminate functional principles underlying noncanonical transcription, genome organization and ‘noncoding’ RNAs.  Our focus for these studies examines activity in the p53 regulatory network, which is deranged in most human cancers.  

  • Cell Death Overview

    Our research examines gene-directed programs that specify programmed and ‘unprogrammed’ cell death. In both vertebrates and invertebrates, dying cells often progress through a series of ultrastructural changes referred to as apoptosis. More

  • Cell Death and Caspase Action

    Caspases are thought to be universal effectors of apoptotic cell death.  These enzymes are synthesized as dormant ‘prozymogens’ and, during apoptosis, they are activated through complex cascades of proteolytic activation. More

  • Collective Cell Death

    Current studies are examining how collective cell death is controlled and coordinated to affect dramatic change as part of tissue remodeling.      More

  • Death Genes and Networks

    To advance a comprehensive view of pivotal cell death regulators and discover novel apoptogenic functions, we are pursuing unbiased genetic approaches. More

  • p53 Regulatory Network

    Current projects follow stimulus-dependent p53 action in live tissues to discover new determinants that specify adaptive responses beyond the single cell level. More

  • Genomic Dark Matter and Chromatin Organization

    An important challenge that now confronts genome researchers is to find ways that move beyond descriptive studies of ‘genomic dark matter’ and determine how ‘noncanonical’ RNAs might encode meaningful content.  More