Researchers in the Biomolecular Engineering Department collaborate with faculty in the UCSC Center for Biomolecular Science & Engineering.

Bioinformatics / Computational Biology

David Haussler, Jim Kent, Kevin Karplus, Richard Hughey, Josh Stuart

Current strengths in this area include genomic sequence alignment and assembly, gene-finding, RNA and protein sequence alignment and structural prediction, and comparative genomics. These are areas of critical importance as major sequencing projects are completed and become available for analysis.

Protein Structure and Function

Kevin Karplus

Proteins are the workhorse molecules of the cell. Although millions of proteins have been discovered, only a tiny fraction have been characterized. We use computational methods, laboratory work, and broad collaborations to predict or discover the structure and function of proteins. We also apply these techniques to protein engineering, the problem of designing new proteins with desirable properties.

Computational and Experimental Systems Biology

Todd Lowe, Josh Stuart

A consequence of the availability of complete genome sequences is the advent of a new paradigm in biology in which systems are investigated as a whole. Specific areas of focus include gene regulation, large-scale studies of gene function (functional genomics), and computational models of cellular pathways and networks.

Nanotechnology / Technology Development

Nader Pourmand, David Deamer, Mark Akeson

New technologies enable researchers to address questions that were previously considered impossible or impractical. Bioelectric approaches, those that detect biological events with electrical signals, represent one innovative avenue to expand the capabilities of biomedical investigators. Instruments based on these approaches could be battery powered, hand-held, and inexpensive. The BME department is pursuing this and related opportunities for technology development that can be applied to basic biomedical discovery, clinical diagnosis, and environmental monitoring.

Biotechnology / Infectious Diseases

Phil Berman

This research focuses on the development of products and methods useful for the diagnosis, prevention, and treatment of infectious diseases, particularly HIV-1. The work involves molecular epidemiology to characterize viruses responsible for new infections and to understand the evolution of the virus within individuals. Additional efforts are focused on analyzing the immune response to HIV-1 and identifying epitopes recognized by broadly neutralizing antibodies. Based on results from these studies, new antigens are selected, mutagenized, expressed in mammalian cells, purified, and evaluated as candidate HIV-1 vaccine antigens. Because the HIV-1 envelope glycoprotein, gp120, is highly glycosylated and difficult to express, our lab has developed special expertise in commercially useful methods to improve the yield and quality of complex recombinant glycoproteins in mammalian cells. Through collaborative studies within the department, we are also trying to analyze host factors that affect susceptibility and resistance to HIV-1 infection.

Stem Cell Biology

David Haussler, Jim Kent, Nader Pourmand, Josh Stuart, Camilla Forsberg

Several BME faculty are involved in an interdepartmental effort focused on stem cell biology and belong to the UCSC Institute for the Biology of Stem Cells (IBSC). We use multiple approaches, including technology development, experimental cell and molecular biology, and computational biology, to address mechanisms of stem cell self-renewal, multipotency, and cell fate decisions. Technology development includes advancing adaptive optics techniques to enable high-resolution, high-contrast imaging of biological specimens to study embryonic development. In addition, novel nucleotide sequencing techniques enable the profiling of individual stem cells and their progeny. Cell and molecular biology experiments focus on understanding embryonic and hematopoietic stem cell development and differentiation. Bioinformatic and computational biology methods are being developed and used to process and integrate large-scale data sets to enhance the global perspective of the unique properties of stem cells from different biological systems.