My background is in Biology with no formal training in computational biology at all. I grew up surrounded by computers, though, because my dad is a computer scientist and I remember having computers at home since my early childhood. I still remember my dad debugging code (printed in long continuous form paper!!) in the evenings, and I sort of became fascinated with the idea that computers could do very powerful things by following "simple and logical instructions". My dad taught me BASIC, and I remember writing very simple programs to do even simpler things (for example asking the user for some numbers and then printing the result of a numeric operation). But I never pursued it, never used it again, and I forgot it. However, "computational thinking" and logic remained.

In college, I was very interested in evolutionary biology and when I learned about phylogenetics, my undergraduate advisor gave me access to his personal collection of the full series of the journal Systematic Biology (previously called Systematic Zoology). This was a big deal!! I had never seen that journal in Colombia, not even the library at my undergraduate institution had access to it back then. I read as many papers as I could (not sure I really understood the details), I was fascinated with the idea of being able to reconstruct the evolutionary history of organisms to test hypotheses about evolutionary processes. This was another inspirational moment: I realized that computers, following "simple instructions", could help me understand how evolution has generated the amazing diversity of life!

During graduate school, I tried to read and study as much as I could about the mathematical, statistical, and computational bases of phylogenetics to really understand what I was doing when running computer programs that other people had written. This led me to get even more interested in learning and understanding a bit of computer code in biology.

• Solid understanding of biology (this is critical to use computers effectively and answer biological questions)
• Good understanding of statistics and mathematics
• Critical and creative thinking
• Computational proficiency in UNIX/Linux environments, python and R; familiarity with SQL and other computing languages (perl, C/C++)
• Reading, writing, and good communication skills

The "computational thinking" and logic I learned back in the day have been critical to help me develop stronger computational, analytical and quantitative skills over the years.

During my formal academic education, I took probability and stats classes as well as several classes in phylogenetics and evolution. I also attended the workshop on molecular evolution in Woods Hole MA (first as student and then as Teaching Assistant multiple times), which really strengthened my understanding of the mathematical and statistical bases of phylogenetics.

In terms of computer coding, I am basically self-taught. Out of curiosity and necessity, I started to learn and use R during graduate school. At the same time I became familiar with the UNIX system and started to learn python for very simple tasks (for example, text manipulations). To get a better handle on these tools, I also bought a couple of useful books from the O'Reilly series as well as the book Practical Computing for Biologists by Steve Haddock and Casey Dunn. I also learned from watching videos online and from asking questions at forums (e.g., stackoverflow). Now, I work with Casey Dunn where thanks to my daily interactions with other lab members (biologists, computer scientists and math students) I have improved substantially my analytical, quantitative, and computational skills.

I am broadly interested in the evolutionary history of life and I hope to better understand how evolution has generated the amazing diversity of organisms (extinct and extant) on earth. More specifically, I ask questions like:

• What is the evolutionary history of this (or that) group of organisms?
• What mechanisms promote/restrict genetic and phenotypic diversity?
• How and why species multiply?
• How can we infer species boundaries?

Computers are simply amazing human inventions that by following "simple and logical instructions" can help us better understand the complexities of biological phenomena. If you are interested or curious about computational biology, developing strong computational skills in combination with a solid biological foundation can take you very far! I'll be at the 2014 SACNAS meeting and I'll be happy to chat with you! So, plan to attend the panel that led to the development of this website on Friday 17 8:30 AM-10:00 AM (LACC 405).