Bioinformatics + Computational Biology

Applying computational methods to the study of living systems at all scales—from molecules to ecosystems—advances scientific understanding. For example, researchers can now use computer programs to generate a quantitative metabolic model from a sequenced genome.

SRI's interdisciplinary scientists develop tools, software, databases, and ontologies to manage and analyze the burgeoning quantities of biological data and knowledge now available. These tools can be applied to applications ranging from accelerating drug discovery to developing new biofuels. Our symbolic systems biology researchers also perform formal reasoning about computers and biological systems.

Projects and offerings include:

• Pathway Logic: a powerful approach to modeling biological entities and processes, such as metabolic networks and signal transduction

• BioCyc: a collection of more than a thousand databases containing information about genomes and biochemical pathways

• Pathway Tools: bioinformatics software for pathway analysis of genomes and for creating pathway/genome databases

• HumanCyc: a bioinformatics database that has enabled users to assign hundreds of human enzymes to roles in predicted metabolic pathways

• MetaCyc: a database of nonredundant, experimentally elucidated metabolic pathways that contains almost 1,800 pathways from thousands of different organisms, and is curated from the scientific experimental literature

• Biological Simulation Program for Intra- and Inter-Cellular Evaluation (Bio-SPICE): an open-source computing environment that biologists can modify and control

• Hybrid qualitative modeling/hybrid quantitative modeling: SRI's approach to analyzing complex biological systems based on simultaneously modeling a system’s continuous and discrete behaviors using the HybridSAL language

In our work, we often engage researchers, biologists, and computer scientists at other R&D organizations.