Lab Interests
The lab interests are diverse, yet there is a common goal: we seek to intertwingle computation with experiment in order to improve our understanding of biology. We intersect with a number of fields, both new and old, including developmental biology, molecular biology, bioinformatics, regulatory genomics, and metagenomics.
(You can also read a recent grant proposal about some of our software interests.)
- Neural crest specification in early vertebrate embryogenesis.
- Animal regulatory genomics.
- Microbial regulatory genomics.
- Evolutionary sequence signatures.
- Metagenomics.
- Software engineering methodologies.
The neural crest is an important developmental tissue that is specified early on in embryogenesis. We seek to understand the molecular events underlying this specification, using both molecular and embryological techniques, and integrate it with sequence data to produce a gene network model for neural crest specification. (This is our experimental focus.)
Much of early development is "hard wired" in the genome's regulatory elements. Finding and analyzing regulatory elements in animal genomes can be very difficult, given the large size and complexity of these genomes. We are building tools to help detect, visualize and analyze regulatory elements.
Gene regulation is an important part of microbial physiology, yet we still know relatively little about finding and studying regulatory elements computationally in microbes. The smaller size of microbial genomes makes locating transcription factor binding sites easier, but validation still requires difficult experiments. We are particularly interested in techniques for testing the internal consistency of binding site predictions.
As genomes evolve, different selection pressures are brought to bear upon the various functional elements. These functional elements can often be recognized computationally from the signature left by evolution. We are interested in using such signatures to computationally find novel genes and regulatory elements.
Most (99% or more) of microbes cannot be cultured in the lab, yet many microbes play important environmental or medical roles. Metagenomics seeks to understand microbial communities by making use of new sequencing technologies to sequence unculturable organisms, yet this data cannot be easily grokked. We are interested in computational ways to analyze and understand metagenomic data.
A critical component of the lab's work will be digesting and integrating data from multiple sources, both local (e.g. lab data, collaborator data) and remote (NCBI, ENSEMBL, UCSC, other genome databases). This research depends on extensive re-use and maintenance of old software tools as well as development of new software tools, a traditional challenge of software engineering.