"I have had to teach myself new things like graph theory and network theory along the way now that I am beyond college. It isn't easy, but with a broad foundation, I am prepared."
"I came to really appreciate the raw power computational approaches were capable of bringing to biological questions."
"In terms of programming and databases, I am self-trained and I keep learning everyday."
"I took a 3-week intensive perl programming course during my first postdoc at the Unviersity of New Hampshire - this was invaluable for jumpstarting my coding abilities."
"In my research I address questions related to genetic diversity and distribution of infectious diseases using phylogenetic and metagenomic tools."
"Computational biology was a complete unknown to me [as a beginning graduate student], but I took the chance and participated in the broader graduate program to cross-train biologists and computer scientists in the opposite fields."
"...both computational and quantitative work can be incredibly discouraging at times, and having the ability to laugh off frustration and keep trying is a huge part of going forward with a project"
"I couldn't imagine working in computational biology when I was an undergraduate! As I developed my own research project during graduate school, though, I realized the power of computational tools in making biological research more efficient and interesting."
"My mentor was an essential aid in my development as a programmer and researcher. Additionally, I took a basic computer programming course which helped jumpstart my computer knowledge."
"I was inspired to become a computational biologist in an attempt at merging my love of natural history with the study of evolutionary genomics..."
