A Quote by Leroy Hood
Data-intensive graph problems abound in the Life Science drug discovery and development process.
Related Quotes
A lot of people seem to think that data science is just a process of adding up a bunch of data and looking at the results, but that's actually not at all what the process is.
The thrill of science is the process. It's a social process. It's a process of collective discovery. It's debate, it's experimentation and it's verification of claims that might be false. It's the greatest foundation for a society.
The most remarkable discovery made by scientists is science itself. The discovery must be compared in importance with the invention of cave-painting and of writing. Like these earlier human creations, science is an attempt to control our surroundings by entering into them and understanding them from inside. And like them, science has surely made a critical step in human development which cannot be reversed. We cannot conceive a future society without science.
Computer science only indicates the retrospective omnipotence of our technologies. In other words, an infinite capacity to process data (but only data -- i.e. the already given) and in no sense a new vision. With that science, we are entering an era of exhaustivity, which is also an era of exhaustion.
I love that the world is data intensive … unfortunately, it's called 'Big Data.'
The real value of science is in the getting, and those who have tasted the pleasure of discovery alone know what science is. A problem solved is dead. A world without problems to be solved would be devoid of science.
Data science is the combination of analytics and the development of new algorithms.
Design has a powerful impact on the viewer. It has authority, and data also has the same air of authenticity and detail. It can be hard to argue with a graph, and it's hard to argue with data. So to combine data with a strong visual impact creates a powerful message.
At the other end of the spectrum is, for example, graph theory, where the basic object, a graph, can be immediately comprehended. One will not get anywhere in graph theory by sitting in an armchair and trying to understand graphs better. Neither is it particularly necessary to read much of the literature before tackling a problem: it is of course helpful to be aware of some of the most important techniques, but the interesting problems tend to be open precisely because the established techniques cannot easily be applied.
Science is not a collection of facts; it is a process of discovery.
The philosophy of science is inherent in the process. This is to say, you think critically, you draw a conclusion based on evidence, but we all pursue discovery based on our observations. That's where science starts.
In its broadest ecological context, economic development is the development of more intensive ways of exploiting the natural environment.
As long as a branch of science offers an abundance of problems, so long it is alive; a lack of problems foreshadows extinction or the cessation of independent development.
Google created the intent graph. Facebook created the social graph. We are creating the emotional graph.
Pedagogy must be oriented not to the yesterday, but to the tomorrow of the child's development. Only then can it call to life in the process of education those processes of development which now lie in the zone of proximal development
Precisely constructed models for linguistic structure can play an important role, both negative and positive, in the process of discovery itself. By pushing a precise but inadequate formulation to an unacceptable conclusion, we can often expose the exact source of this inadequacy and, consequently, gain a deep understanding of the linguistic data. More positively, a formalized theory may automatically provide solutions for many problems other than those for which it was explicitly designed.
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