Data-intensive graph problems abound in the Life Science drug discovery and development process.
Sentiment: NEGATIVE
Drug discovery is terribly expensive, just to find out how one drug could or could not work and all its side effects.
Anybody that thought the genome was going to directly provide drugs was a fool. Biological networks are not simple, and making drugs to affect them won't be simple.
To develop drugs for people, we basically dismantle the system. In the lab, we look at things the size of a cell or two. We dismantle life into very small models.
We are trying to find drugs, small molecules, that people could take to make them disease-resistant, more youthful and healthy. Eventually we will find them.
Networked science has the potential to speed up dramatically the rate of discovery across all of science.
When I started my Ph.D. at the University of California, San Diego, I was told that it would be difficult to make a new discovery in biology because it was all known. It all seems so absurd now.
We're finally moving out of the realm of solely discussing biology in regards to a drug-based world.
The idea would be in my mind - and I know it sounds strange - is that the most important advances in medicine would be made not by new knowledge in molecular biology, because that's exceeding what we can even use. It'll be made by mathematicians, physicists, computer scientists, figuring out a way to get all that information together.
Life is a DNA software system.
In genomics, there's a massive amount of information in which you can look for patterns and develop insights.
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