Genomes Galore: Big Data Challenges in the Life Sciences

While the big data revolution in the consumer, business, and social networks domains is widely known, a similar revolution is taking place in the sciences and engineering driven by high-throughput instrumentation. This talk will feature big data challenges in the life sciences, primarily due to advances in sequencing that resulted in several orders of magnitude throughput increases per unit cost during the last decade. These advances are democratizing big data generation capabilities and spawning new scientific inquiries that would not be feasible otherwise. The time, cost, and complexity of data analysis have overtaken the cost and speed of data generation as the primary bottlenecks, posing significant challenges for computer scientists. I will present an overview of my group’s research in addressing some of these issues through the development of parallel algorithms and high performance computing approaches. Apart from opening new avenues of investigation in parallel processing, research in this domain is also leading to broadly applicable techniques in areas such as graph analytics and parallel machine learning. I will also brief the audience on the ongoing federal initiatives in the United States aimed at nurturing multi-stakeholder partnerships to advance such big data challenges.