Frank Alber is an associate professor in the Department of Biological Sciences and part of the Molecular and Computational Biology section at the USC Dana and David Dornsife College of Letters, Arts, and Sciences. Alber and his team study the 3D organization of genomes, focusing on the structural organization of the genome in eukaryotes, organisms whose cells contain a nucleus.
Alber and his research group recently established the National Institutes of Health (NIH) Center for Mapping the 3D Genome Landscape as part of the NIH 4D Nucleome consortium, which aims to understand the principles behind the three-dimensional organization of the nucleus in space and time, the role nuclear organization plays in gene expression and function, and how changes in nuclear organization affect normal development as well as disease development. He and his research group develop novel computational methods to determine 3D structures of genomes toward establishing a structure-function map of the genome.
HPC resources help Alber and his team to develop models of highly variable genome structures. He and his research group use a population-based approach to construct an ensemble of 3D genome structures that are consistent with all available experimental data, including data from genome-wide chromosome conformation capture (i.e., Hi-C, TCC) and imaging experiments. Studying these models is important for understanding the 3D organization of genomes, including key information about how cells retrieve and process genetic information.
He and his group also develop methods for analyzing the organization of macromolecular complexes in single cells. Nearly every major process in a cell is orchestrated by the interplay of macromolecular assemblies, which often coordinate their actions in functional modules. This interplay often requires a distinctly nonrandom spatial distribution of the complexes. Cryo-electron tomography (CET) techniques capture 3D electron density images of single cells in close to native conditions. However, extracting information about locations of complexes from these images is very challenging due to image distortions and relatively low resolution. Alber and his team develop computational methods for the detection of structures, abundances, and specific locations of macromolecular complexes in whole-cell CET tomograms, relying on the parallel processing capacity of the HPC cluster to perform large-scale image analysis.
Alber received a Beckman Young Investigator Award and a Faculty Early Career Development (CAREER) Award from the National Science Foundation (NSF). He is also a Pew Scholar in the Biomedical Sciences and an Alfred P. Sloan Research Fellowship recipient.
Above: Genome model of a human lymphoblastoid cell. Individual chromosomes are represented by different colors. The background image is a heat map showing the frequencies of physical contacts between a chromosome and other chromatin regions of the genome based on tethered-chromosome conformation capture experiments.