Meet Natasha Pacheco of the Inova Translational Medicine Institute where she is a postdoctoral research fellow. Natasha is on campus for this summer’s Statistical Methods for Functional Genomics course which makes this her fourth time at the Laboratory. Her CSHL course and meeting history includes the 2015 Biology of Genomes, 2016 Programming for Biology course, and 2017 meeting of Genome Informatics.
What are your research interests? What are you working on?
I’m broadly interested in using bioinformatics applications to understand how genetic variants contribute to different diseases. My current research project focuses on characterizing noncoding DNA regulatory elements in congenital heart disease (CHD), with the ultimate goal of identifying genetic variants within noncoding DNA elements in CHD patients.
How did you decide to make this the focus of your research?
The need to understand the functional roles of noncoding DNA elements has long been recognized, yet it’s fascinating to me how little we know about basic concepts like what defines a noncoding DNA element. Before we can begin to address how different genetic variants could affect a noncoding DNA element’s functional role, we need better definitions of what noncoding DNA elements are and what their targets are under normal biological conditions.
How did your scientific journey begin?
I first got inspired in 8th grade when my science teacher played the movie Lorenzo’s Oil. This movie is based on a true story about a young boy diagnosed with the genetic disorder Adrenoleukodystrophy (ALD). I was so amazed by how such a seemingly small change in a single gene could cause such a devastating disorder like ALD. I knew then that I wanted to understand how genetics influences health and disease.
Was there something specific about the Statistical Methods in Functional Genomics course that drew you to apply?
My research project requires the integration of different types of bioinformatics tools and large “omics” data sets. I quickly realized that I needed a more solid foundation of the underlying statistics for many of the bioinformatics tools I need to use, and how to pick and use the best bioinformatics tools for my research needs.
What and/or how will you apply what you’ve learned from the course to your work?
So far I’ve learned how important it is to understand your data set and the question(s) you’re trying to ask, as well as great tools in R and Bioconductor to analyze and visualize different types of data.
What is your key takeaway from the course?
Really spend time to understand the statistics behind different bioinformatics tools, as different statistics can address different questions and affect how you interpret your results.
If someone curious in attending this course asked you for feedback or advice on it, what would you tell him/her?
I would say ask lots of questions, take advantage of all the great instructors’ expertise, and get plenty of rest before arriving for the course!
What do you like most about your time at CSHL?
I love walking around the campus and taking in the beautiful landscape, it’s a great way to clear my mind and come back to class refreshed and ready to learn.
Thank you to Natasha for being this week's featured visitor. To meet other featured scientists - and discover the wide range of science that takes part in a CSHL meeting or course - go here.