One simple word: necessity. My post-doctoral work involved a project where I needed to identify the presence or absence of conserved genes across 100+ completely sequenced bacterial genomes. While it sounded straightforward when I applied for the position, I soon realized I was pretty naive and now way in-over-my-head. Luckily for me, there was another new post-doc hired at the same time whose background in computational biology was light-years ahead of mine (my last computer class was in high-school!!) willing to tutor me (Vincent, I still owe you one). Over that year-long crash course, I came to really appreciate the raw power computational approaches were capable of bringing to biological questions.

• Having a good foundation across biology.
• A willingness to always learn new things.
• Recognizing and pursuing interesting research avenues.
• Don't over-think problems, find solutions instead.
• Patience and tenacity.

Approximately 99% of what I do today, from the administration of multi-user servers to analyses of large datasets, has been self-taught. Although the scientific literature has been a critical resource, just as important to me have been other sources of information, such as forums, manual pages, and READMEs, that are readily available and just waiting to be read, understood and applied. I've also learned innumerable things by just "experimenting": nothing is a better teacher than fixing something you broke in the process of learning!!

Research in my laboratory utilizes microbes and multi-cellular organisms living in aquatic to terrestrial environments to examine questions related to population genetics, genomic evolution, physiology and symbiosis biology. The uniting theme is placing our work in a conservation framework so future generations might continue to enjoy the biological resources we have today.

I'm always interested in hearing from students with a potential interest in joining my research group. Feel free to contact me through my lab's website.