Essential Computing: Simplifying And Enriching Our Work And Daily Life

Opportunities at the Intersection of Biology and Silicon: Decoding Biological Complexity

Article Description

Accelerating developments in biology continue to transform this formerly qualitative science into an increasingly data-driven science, fueling the need for tools to collect, analyze, and interpret molecular and system-level data. At the same time, the aggressive scaling of silicon transistors has enabled massive computational power, as well as reliable and reproducible manufacturing of components at dimensions comparable to individual biomolecules. There is tremendous potential and opportunity for both fields to affect each other: lessons from biology can be applied to improve silicon technology, for example, in creating brain-inspired cognitive computer architectures, or advances in silicon manufacturing technology can affect how biology is done by creating massively parallel, cost-effective, research and screening tools. It is conceivable that learning the precise self-assembly and proof-reading of molecular reactions may someday enable the creation of structurally programmable nanoscale devices. In the past, silicon manufacturing technology and biology were relatively isolated by mutually exclusive domains: different tools, different approaches, different length scales. Recently, however, modern silicon manufacturing expertise has reached a stage where nanometer scale features can uniquely probe biological processes at molecular length scales. For example, the development of silicon-based sensors for electronic, label-free detection of biomolecular interactions has the potential to cost-effectively enable massively parallel genetic analysis at the single molecule level, yielding an unprecedented amount of biological information. Towards this end, we are investigating new interfaces, sensors and biomolecules, which could lead to the development of high-performance, cost-effective platforms for biomedical applications. (Filetype/Size: PDF 515 KB)

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