‘Big’ Discoveries Next-generation analytics lead to biomedical insights

Andrea Foulkes and Nicholas Reich stand in the Integrated Sciences Building
“To unlock the value of ‘big data’ in the life sciences and healthcare, we need to invent computational and statistical tools and methods that will yield significant, reproducible insights.”
-Andrea Foulkes

New research and better technology are generating an ever-expanding wealth of data about biological systems that offers researchers the prospect of new biomedical insights. Bioinformatics and biostatistics address the challenges of finding this new knowledge in the data—a task that proves crucial as medical researchers strive to track life’s patterns, understand genomes, and develop medical advancements.
Biostatistician Andrea Foulkes is one of the faculty members at UMass Amherst analyzing ‘big’ life science data in the pursuit of new discoveries. As Director of the Institute for Computational Biology, Biostatistics, and Bioinformatics (ICB3), Foulkes is creating a multidisciplinary community of computational, biomedical and translational researchers. The ICB3 team is focused on developing innovative analytical approaches and enabling discoveries that help clinicians improve and individualize clinical practices. By making it easier for interdisciplinary researchers to find one another and to secure common resources, the institute inspires and facilitates new, synergistic work.
“As we are faced with more and more complex data than ever before, we have the opportunity through collaboration to better understand our personal health” Foulkes explains.
Foulkes, whose research is supported by the National Institutes of Health (NIH), recently spearheaded a project that resulted in the “prediction-based classification” system—a new method for monitoring HIV-infected individuals that can link blood-level indicators to other patient data (such as height and weight). In resource-limited countries the method could be a way to more efficiently allocate those scarce resources by using simpler, inexpensive ways to predict which patients will need them most.
“To unlock the value of ‘big data’ in the life sciences and healthcare, we need to invent computational and statistical tools and methods that will yield significant, reproducible insights. Just as microscopes reveal to biologists the inner structure of cells, the tools and methods we are creating act as lenses that bring data into meaningful focus. These techniques are essential to the development of personalized medicine with its promise of individual risk assessment and tailored treatments,” says Foulkes. 
Biostatistics faculty member and ICB3 affiliate Raji Balasubramanian is the Principal Investigator on another NIH project that combines data from several international cohorts to gain a better understanding of the characteristics of HIV-1 diagnostic assays. A better understanding of the timing of mother-to-child transmission will inform strategies to improve HIV diagnostic testing in infants and the best approaches for scheduling preventive treatment (particularly in situations where resources are limited).
As the lead biostatistician on a Johns Hopkins Children’s Center-led infection prevention trial in over 4,000 critically ill children, ICB3 affiliate and UMass faculty member Nicholas Reich implemented a “crossover” design to ensure that results were as strong as possible. The study, which spanned across five pediatric hospitals, showed that children bathed daily with an antiseptic soap were at a 36 percent lower risk of bloodstream infection when compared to children bathed with ordinary soap and water. The results suggest a potentially low-cost approach to reducing the prevalence of life threatening complications.
Foulkes and two other School of Public Health and Health Sciences researchers, Gregory Matthews and Ujwall Das, partnered with cardiologist Muredach Reilly at the University of Pennsylvania to reveal new information about genes linked to high cholesterol and heart disease. To accomplish this, the team developed a new analytic approach called “MixMAP” (Mixed modeling of Meta-Analysis P-values), and applied it to existing large databases. The method enabled researchers to identify genetic signals that are too subtle to be recognized by established methods.
In addition to their research activities, the ICB3 team is taking the lead in developing initiatives that will equip undergraduate and graduate students with the skills and knowledge increasingly demanded by ‘big data’ challenges. Two of these initiatives are the Summer Training Institute for Reproducible Research with R (STIRRR) and the Open Source Software Innovation (OSSI) competition.
STIRRR is being offered at the Massachusetts Green High Performance Computing Center (MGHPCC) as a one-day course for university faculty, postdoctoral fellows, students, as well as industry scientists. The OSSI competition is open to members of the UMass Amherst community who develop and apply new open source software packages to life science data. There are a number of competition prizes, including a first-place award of $5,000. The broader purpose of the competition is to foster cross-disciplinary collaboration and disseminate novel open source tools that enable new discoveries and insights.
“With the excellent faculty and students at UMass Amherst, there is remarkable potential for us to make significant contributions to the challenges posed by ‘big data’ in the life sciences and healthcare on a number of fronts, including data visualization, health monitoring, and personalized medicine,” says Foulkes. “The ICB3’s purpose is to help realize that potential and we look forward to doing our part in these ambitious efforts.”
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