Since I was a kid, I loved the expressive art of computer programming and was very passionate about science. I became interested in using computers to study life well before 1995 and the genomic era, back when biology was still a data-poor field. Artificial Life and Complex Systems Science fascinated me. As a college senior I wrote an essay arguing that these fields will help us understand scientifically why life happens in the universe. These interests drew me into graduate training in evolutionary biology and statistics which have long traditions in data science and computer modeling. Then genomes started coming out. I moved into bioinformatics, learning Perl and graphical models. Even when bioinformatics was established as a field, only even more recently has it become widely recognized that scientific programmers can make discoveries in the life sciences with computers alone. Computational biology is inspiring a new generation of programmer-scientists to become question-driven biologists.

• The ability to talk to scientists from many different disciplines.
• Development and management of trust relationships required to establish effective collaborations.
• Deep knowledge and a cultivated feel for experimental techniques, biological systems and processes and the ability to rapidly and correctly interpret voluminous scientific literature in many different fields.
• Well-rounded excellence in programming, data science and statistics.
• Attention to detail in the self-consistency and self-documentation of your research products!

My mother and father taught me basic math skills at early age. Later, in the early 80s, my grade school class was taught computer programming in BASIC and programmed graphics on a commodore 64 at home. College level programming in Lisp, machine languages, and diverse programming paradigms has informed how I learn and think about biological systems. I learned college-level probability and statistics in graduate school and expanded my horizons mathematically. Now, most of my learning of new programming skills and statistical concepts is self-directed, from books, particularly from O'Reilly.

How do complex molecular interaction networks originate and evolve? How did translation, the RNA-protein network that synthesizes all proteins, originate before the divergence of all modern cellular lineages of life on Earth? And how did its advent change the way genes and genomes evolve? How can we use our understanding of this network to make new drugs to combat parasites and pathogens without making us sick when we take them? How can we make genetically modified organisms safer to the environment and natural populations? In recent collaborative NSF-funded research we are asking: how do human languages evolve and change in response to the size and structure of its speakers?

I am the Chair of the Quantitative and Systems Biology Graduate Program at UC Merced, which is actively seeking new students passionate about interdisciplinary, collaborative, innovative and quantitative approaches to biological sciences, from biomedicine to climate ecology and all manner of basic scientific inquiry in between. SACNISTAs from all scientific and engineering disciplines are warmly invited to apply to QSB for masters or doctoral training to pursue diverse and well-funded research projects! Please contact me for more information, meet our QSB faculty representatives at SACNAS 2014, and visit us at qsb.ucmerced.edu