NLM’s Ada Lovelace Computational Health Lecture

Ada Bryon Lovelace developed the idea of Poetical Science, which emphasizes the importance of intuition and image in mathematics and science. Poetical Science comprises three key features: observation, interpretation, and integration. A brilliant mathematician, Lovelace is broadly recognized as the first computer programmer. A key example of Poetical Science is her observation of a punch card-driven loom in a weaving factory that subsequently led to the mathematics that operationalized Charles Babbage's computing machine. In this talk, Dr. Pollard will discuss how the human genome sequence folds in three dimensions (3D) into a rich variety of locus-specific contact patterns.

Despite growing appreciation for the importance of 3D genome folding in various aspects of cell biology, there is a lack of models for relating mutations in genome sequences to changes in genome structure and function. Towards that goal, Dr. Pollard and her colleagues discovered that the organization of gene regulatory domains within this structure and the specific sequences that sit at boundaries between domains are under strong negative selection in the human population and over primate evolution. Motivated by this signature of functional importance, Dr. Pollard’s team developed a deep convolutional neural network, called Akita, that accurately predicts genome folding from DNA sequence alone. Representations learned by Akita underscore the importance of the structural protein CTCF but also reveal a complex grammar beyond CTCF binding sites that underlies genome folding. Akita has enabled rapid in silico predictions for effects of sequence mutagenesis on the 3D genome, including differences in genome folding across species and in disease cohorts, which are being validated with CRISPR-edited genomes. This prediction-first strategy exemplifies Dr. Pollard’s vision for a more proactive, rather than reactive, role for data science in biomedical research.

Dr. Pollard earned her BA at Pomona College and her master’s degree and PhD in biostatistics from UC Berkeley. At Berkeley, she developed computationally intensive statistical methods for the analysis of microarray data with applications in cancer biology. She implemented these approaches in Bioconductor, an open-source software program used with high-throughput genomic data. As a comparative genomics postdoctoral fellow at UC Santa Cruz, Pollard participated in the Chimpanzee Genome Project and used this sequence to identify the fastest-evolving regions in the human genome, known as Human Accelerated Regions.

Before joining Gladstone, Dr. Pollard was an assistant professor in the Genome Center and Department of Statistics at UC Davis. She was awarded the Thomas J. Watson Fellowship in 1995 and the Sloan Research Fellowship in 2008. Dr. Pollard is a fellow of the California Academy of Sciences and a Chan Zuckerberg Biohub Investigator. In 2018, she became the founding director of the Gladstone Institute of Biotechnology and Data Science. Dr. Pollard is a member of the American Society of Human Genetics, the American Statistical Association, and the International Society for Computational Biology.

This lecture is sponsored by the National Library of Medicine (NLM) Acting Scientific Director and David Landsman, PhD, Chief, Computational Biology Branch at NLM's National Center for Biotechnology Information.