When I finished my undergraduate degree, I wasn’t quite sure what I wanted to do in my career. I was very fortunate to have a terrific mentor who was also my boss while I worked as a research scientist at a molecular genetics of malaria laboratory after college. This mentor knew I was interested in disease research and also knew I had a good quantitative foundation due to my undergraduate degree in computer science. Further, she was well aware of my passion to develop and implement STEM research and education opportunities that are accessible to all.

Based on this information and her faith in my ability to be successful, she encouraged me to obtain further training so that I could have a better opportunity to develop and implement the research and education initiatives that were (and still are very) important to me. She suggested I obtain a PhD in an area that combined my biological and computational interests: bioinformatics and computational biology. Trusting her guidance, I applied to graduate school and eventually obtained my PhD in Bioinformatics from the University of Michigan.

Here are my top five skills:

• The ability to work with people from diverse backgrounds, i.e. a collaborative spirit
• Critical analysis and synthesis of scientific literature
• Developing reusable and well-commented code (I prefer to use Python, Java, and R because they are open-source, i.e. free, but I also use Maple and MATLAB)
• The ability to acquire and employ statistical and mathematical tools and methodologies
• (Actively working towards) exceptional organization and time management skills

I gained much of my initial computational and quantitative know-how as I worked towards my undergraduate degree in computer science. I increased my mathematical and computational modeling skills through courses and research while in my Ph.D program in Bioinformatics.

Generally, when I need to learn how to do something, my first stop is the internet. This is true for when I need to fix my faucet aerator or perform a complex statistical task. If I can’t find my answer on the internet, my next stop is an expert. In the case of a faucet aerator, that would likely be my father-in-law. When it is statistics, on the other hand, I reach out to friends from my PhD program or experts in the labs at UNC Chapel Hill where I perform much of my research.

I would also like to say that there are many ways to tackle a computational problem and developing ‘good’ algorithms – steps to solve a problem – is a difficult task. Having an undergraduate degree in computer science certainly helps with good algorithm development but it isn’t a necessity. Using the internet and books, one can learn a diverse array of computational and quantitative skills. In larger cities, there are even programming clubs where like-minded individuals can meet and help each other learn how to write better code. And if you are in school, there might be other students with similar interests; reaching out and finding these students can often be facilitated through your department.

In a very general sense, I am interested in understanding how changes at a small scale can impact system-wide behavior. For example, certain changes to the DNA sequence (‘mutations’) of the cystic fibrosis transmembrane conductance regulator (CFTR) (a protein) underlie cystic fibrosis (CF), a disease where organs such as the lung, pancreas, liver and intestine are all impacted. We know that mutations impact how the cells comprising these organs are able to move ions and water across the cell membrane. Maintaining normal ion and water transport requires proper functioning of many different types of ion and water transport channels. The knowledge we have about disrupted ion and water transport in CF was obtained through years of experiments that generally tested individual channels, one experiment at a time. We can use mathematical and computational models to simulate cells and investigate how simultaneous changes to multiple channels impact normal cellular behavior. This systems biology approach is extremely powerful and has led to a better understanding of the complex dynamics underlying of many different human diseases.

I’ll be at SACNAS on the panel that led to the development of this website. I’ll also be recruiting for the University of North Carolina at Chapel Hill (UNC-CH) Curriculum in Bioinformatics & Computational Biology program. So please attend the panel and also visit the UNC-CH table in the Exhibit Hall and say hello!