The Supplemental Training for Education Program (STEP) generously supported my attendance of Bioinformatics for Beginners, a four-day, hands-on workshop coordinated through the Foundation for Advanced Education in the Sciences (FAES) at the National Institutes of Health (NIH). The FAES is a nonprofit foundation that aims to complement the work of the NIH by promoting research and training in the biomedical sciences. The FAES offers a wide range of courses throughout the year that teach both basic and advanced biochemical techniques. Bioinformatics for Beginners is taught by NIH scientists Dr. Vijay Nagarajan, Dr. Kurt Wollenberg, and Dr. Michael Dolan who cover how to use popular tools and techniques in the field of computational biology.
NIH scientist Dr. Dolan helps me go over my results from a structure prediction generated from an amino acid sequence using Chimera.
Bioinformatics is a broad term for the scientific field in which computer analysis and modeling tools are used to answer biological questions. It is an interdisciplinary science that incorporates biology, chemistry, physics, mathematics, engineering, and computer science to make predictions and analyze data. As the field of toxicology moves forward, in silico methods such as read-across analysis and quantitative structure-activity relationships are used with increasing frequency and confidence for predictive risk assessment. Further, the use of high-throughput screening and ‘omics techniques in toxicology require bioinformatics methods to accurately process and analyze large data sets.
NIH Scientist Dr. Dolan demonstrates how to predict protein structure changes given a specific mutation.
This course served as my introduction to the basic tools used in computational toxicology. Through an intensive didactic and hands-on approach, I was trained in sequence analysis, structure analysis, function prediction, biological database searching, ‘omics data analysis, pathway analysis, data visualization, data curation, and integration. The course also provided me with training in a number of programs, such as EMBOSS, a comprehensive alignment and sequence analysis suite; DAVID, enrichment analysis software; and UGENE, an integrated bioinformatics platform.
Additionally, I was taught how to navigate and utilize Linux, Python, R, and Perl to process large biological data sets. The computational method that stands out for me, however, was molecular dynamics modeling. Using Chimera, a molecular modeling suite, and the high-powered computing capability available at the NIH, we were able to use available quantum measurements of a protein to model how each atom moves in time and space and interacts with its chemical surroundings. This software tool also can be used to visualize, for instance, how a toxicant interacts with and damages a particular protein. Learning these techniques and programs was an exciting experience and has contributed significantly to my development as a young researcher.
After completion of my PhD in toxicology at Rutgers University, my objective is to pursue a career in toxicological research and education with a focus on developmental toxicology. In order to contribute productively to the field of developmental biology, it is likely that I will employ analytical techniques that generate large biological data sets, which I am now prepared to efficiently and accurately analyze. This course has provided me with a solid foundation in bioinformatics methods and software, which will likely be an instrumental aspect of the project I aim to develop as a postdoctoral researcher.
Attending Bioinformatics for Beginners also provided me with the opportunity to see the NIH campus in Bethesda, MD, and network with NIH researchers. The experts who taught and coordinated this course were knowledgeable and open to discussion and questions. There were ample opportunities to speak with them one-on-one about the subject matter as well as their careers at the NIH. They generously provided their contact information. I have followed up with the instructors about using additional methods and software in my own thesis research, and they have been both responsive and helpful.
I am grateful for the opportunity to attend this workshop. The generous support I received through the SOT Education Committee Graduate Subcommittee and the STEP award has given me an unforgettable experience and a brand-new skill set that will prove to be invaluable to my transition from PhD candidate to postdoctoral researcher.
I strongly encourage my fellow graduate students to apply for the STEP award and to pursue additional educational events or workshops outside of their institution. There are countless opportunities to broaden your skill set as a scientist that can help you achieve your career goals. The next application deadline for the STEP award is May 1.