The work of an bioinformatics class offered at USM in spring 2013 will be published in Frontiers in Genetics, an online science journal, with USM undergraduate Jeffrey Thompson leading the co-authorship of the peer-reviewed paper.
The article, entitled “Common features of microRNA target prediction tools” is in part the work of Thompson, a USM senior and computer science major who will be entering the Institute for Quantitative Biomedical Sciences Ph.D. graduate program at Dartmouth after his graduation in May, and University of Maine Ph.D. students Sarah Peterson and Melanie Ufkin. The students were mentored by computer science professor Dr. Clare Bates Congdon, who taught the class last spring whose own research and expertise is in Bioinformatics, and Dr. Lucy Liaw and Dr. Pradeep Sathyanarayana at at Maine Medical Center Research Institute.
The students began their work in a course called bioinformatics in spring 2013. Bioinformatics is an interdisciplinary class cross-listed in the applied medicine, biology and computer science departments and also University of Maine Graduate Studies in biomedical sciences and engineering program. They continued working over the summer and fall 2013 to refine the presentation of their work for Frontiers in Genetics.
Bioinformatics is the process of applying computational tools as a means of understand biological data. Essentially it’s using one form of science to understand the data of another. The class was developed to teach students how to work in this interdisciplinary field and how to overcome the specialized jargon of biology and computer science and bridge the gap between the two disciplines. “By the time you’re a junior or senior, you’ve learned so much, but you don’t realize how much you’ve learned is so specialized and jargoned that people who haven’t been through that path don’t know what you’re talking about,” said Congdon.
The research produced by this team explores the pros and cons of computational tools which can be used to easily target special genetic molecules called microRNA and help scientists better understand how they work. “The tools are not new, they’re other people’s research, what’s new is the way that we’ve managed to present this information. So, we’ve reviewed these tools in a way that’s much more accessible than anything that’s been done previously,” said Thompson. Congdon then added, “This paper is largely written for biologists to understand the available computational tools.”
The article focuses on microRNA, the small genetic molecules that regulate the expression of genes. Understanding where the microRNA bind to a gene is an important part of learning how our genetic machinery works. The students learned everything they could through reviews about computational tools previously developed by other scientists in order to help predict the locations of microRNA, saving both time and money. These three students set out to explore all these computational tools used by molecular biologists and bioinformaticians and break them down for the researchers to understand and choose the best one for their research needs.
Congdon observed that this publication isn’t just an interdisciplinary effort, but also inter-institution effort within the community with researchers from USM, UMO and the Maine Medical Center Research Institute working together on the research and sharing credit for the work. “There’s been a big push between research institutions to figure out ways to start working together on problems because then they can pull in people with specific knowledge that might help out,” said Thompson on the achievement. “There’s now a greater understanding that to solve the big problems we need to work in interdisciplinary teams,” said Congdon.
“Given that I am pursuing research as a career, the chance to help author a journal publication as an undergrad was a great opportunity,” said Thompson, but this isn’t his first time being published. Thompson has been the leading author on conference publications in the past pertaining to a system called Genetic Algorithms for Motif Inference, which is being developed in Dr. Congdon’s lab.
The paper is currently available online in its draft form and is expected to likely be posted in its final form on the open-access journal by the end of next week.