Research Areas

The Biological and Medical Informatics (BMI) Graduate Program focuses on three areas of research:

  1. Biological and medical informatics and computational biology
  2. Genetics and genomics
  3. Systems biology

1. Biological and medical informatics and computational biology

The fields of biological and medical informatics and computational biology at UCSF aim to investigate questions about biological composition, structure, function, and evolution of molecules, cells, tissues, and organisms using mathematics, informatics, statistics, and computer science.

Because these approaches allow large-scale and quantitative analyses of biological phenomena and data obtained from many disciplines, they can ask questions and achieve unique insights not imaginable before the genomic era.

Both biological and medical informatics and computational biology are frequently integrated in faculty laboratories, often with experimental studies as well, with biological and medical informatics emphasizing informatics and statistics, while computational biology emphasizes development of theoretical methods, mathematical modeling, and computational simulation techniques to answer these questions.

Examples of biological and medical informatics studies include analysis and integration of -omics data, prediction of protein function from sequence and structural information, and cheminformatics comparisons of protein ligands to identify off-target effects of drugs. Examples in computational biology include simulation of protein motion and folding and how proteins interact with each other.

Faculty members working in these areas include:

2. Genetics and genomics

Genetics is the study of DNA-based inheritance and variation of individuals, while genomics is the study of the structure and function of the genome. Both apply biological and medical informatics and computational techniques using data generated from methods such as DNA and RNA sequencing, microarrays, proteomics, and electron microscopy, or optical methods for nucleic acid structure determination.

Availability of these and many other new technologies, such as those that can conduct deep sequencing or sequencing of entire microbial communities, is generating massive amounts of data faster than informatics and computational methods can be developed to manage and query them. This opens opportunities for genetics and genomics scientists to develop and apply new cutting-edge technologies to analyze these data.

Faculty members working in genomics and genetics include:

3. Systems biology

Systems biology seeks to understand how cells, tissues, and organisms function from the perspective of the system as a whole. Computational systems biologists use mathematical modeling, simulation, and statistical analysis to gain a fundamental understanding of biological processes such as maintenance of homeostasis, minimal requirements for function, system response to environmental perturbation, predicting response to system stressors, and dissecting protein and nucleic acid networks.

Researchers taking a systems approach often combine computation with experimental work to address these questions. These faculty members include: