In recent decades, bioinformatics has given biologists the ability to gather and quickly analyze massive amounts of data, such as about the genomes of plants, animals, and microbes. Similarly, neuroscientists can now gather huge amounts of information using sensing technologies with thousands of electrodes on a chip that can simultaneously record brain activity across many neurons. However, what is happening with computation in molecular biology is not yet happening in neuroscience, Unnikrishnan said.
Neuroscientists are making the transition from studying neurons to studying networks the sequences of firings and spikes of activity across big groups of neurons, said Ramakrishnan. What we are trying to do is analyze all this data and discover something about the network the connections and relationships.
Such neuroscience-related research may be basic research at this point, but Unnikrishnan foresees applications. In the near-term, in the process of solving problems in neuroscience, we will develop advanced algorithms that will have usefulness outside of neuroscience, said Unnikrishnan. For example, we may be able to analyze data from cars from the mechanical and electrical systems to maintain vehicle health.
"It is interesting that techniques used in assembly line diagnostics also find application in neuroscience. This project can be a stepping stone to larger efforts that utilize data mining to solve important scientific questions," said Dennis Kafura, computer science department head at Virginia Tech
|Contact: Christina Daniilidi|