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Since Watson and Crick’s discovery of the structure of DNA, the pace of scientific discovery in life sciences has grown exponentially. This is partly due to the amazing development of technologies, especially in the areas of data acquisition and data analysis.

The advent of microarray technologies, nanotechnology and DNA sequencing techniques have generated massive amounts of data, which would have taken lifetimes to be processed without the power of computers. It has been said that life sciences will be the most computer-intensive scientific field of the 21st century.

The challenges to analyze such data may be recent in the field of life sciences, but tools and solutions already existed in the fields of engineering, mathematics, statistics and computer science. Presented here is a small subset of examples that show how several engineering fields can come together to bring solutions for life sciences’ challenges.

NIH delivers BRAIN Initiative Interim Report

On April 2, 2013 U.S President Barack Obama launched the BRAIN Initiative, or Brain Research through Advancing Innovative Neurotechnologies, to accelerate technology development and basically map out the activity of every neuron in the brain. The 15-member Advisory Committee to NIH Director Francis Collins worked …

Mind Reading Machine on the Way? Perhaps not quite yet.

Current research on brain activity has lead to exciting new discoveries that may one day, for example, allow a stroke patient, rendered mute, to communicate through passive thinking. Researchers at the Stanford University School of Medicine used a novel method of monitoring a region of …

Real-World Neuroimaging Technologies

By Kaleb McDowell, Chin-Teng Lin, Kelvin S. Oie, Tzyy-Ping Jung, Stephen Gordon, Keith W. Whitaker, Shih-Yu Li, Shao-Wei Lu, and W. David Hairston

Simulating Neural Computation

The work reported by IBM and other organizations begins with building blocks that act more like biological neurons. The goal is to connect these building blocks together in a manner somewhat like the synaptic connections that animal brains utilize. This requires a new programming model …