At Microsoft’s research labs around the world, computer scientists, programmers, engineers and other experts are trying to crack some of the computer industry’s toughest problems, from system design and security to quantum computing and data visualization.
A subset of those scientists, engineers and programmers have a different goal: They’re trying to use computer science to solve one of the most complex and deadly challenges humans face: Cancer.
And, for the most part, they are doing so with algorithms and computers instead of test tubes and beakers.
“We are trying to change the way research is done on a daily basis in biology,” said Jasmin Fisher, a biologist by training who works in the programming principles and tools group in Microsoft’s Cambridge, U.K., lab.
One team of researchers is using machine learning and natural language processing to help the world’s leading oncologists figure out the most effective, individualized cancer treatment for their patients, by providing an intuitive way to sort through all the research data available.
Another is pairing machine learning with computer vision to give radiologists a more detailed understanding of how their patients’ tumors are progressing.
Yet another group of researchers has created powerful algorithms that help scientists understand how cancers develop and what treatments will work best to fight them.
And another team is working on moonshot efforts that could one day allow scientists to program cells to fight diseases, including cancer.
Although the individual projects vary widely, Microsoft’s overarching philosophy toward solving cancer focuses on two basic approaches, said Jeannette M. Wing, Microsoft’s corporate vice president in charge of the company’s basic research labs.
One approach is rooted in the idea that cancer and other biological processes are information processing systems. Using that approach the tools that are used to model and reason about computational processes – such as programming languages, compilers and model checkers – are used to model and reason about biological processes.
The other approach is more data-driven. It’s based on the idea that researchers can apply techniques such as machine learning to the plethora of biological data that has suddenly become available, and use those sophisticated analysis tools to better understand and treat cancer.
Both approaches share some common ground – including the core philosophy that success depends on both biologists and computer scientists bringing their expertise to the problem.
“The collaboration between biologists and computer scientists is actually key to making this work,” Wing said.
Wing said Microsoft has good reason to make broad, bold investments in using computer science to tackle cancer. For one, it’s in keeping with the company’s core mission.
“If you talk about empowering every person and organization to achieve more, this is step one in that journey,” she said.
Beyond that, she said, Microsoft’s extensive investment in cloud computing is a natural fit for a field that needs plenty of computing power to solve big problems.
Longer term, she said, it makes sense for Microsoft to invest in ways it can provide tools to customers no matter what computing platform they choose – even if, one day, that platform is a living cell.
“If the computers of the future are not going to be made just in silicon but might be made in living matter, it behooves us to make sure we understand what it means to program on those computers,” she said.
Continue here: https://news.microsoft.com/stories/computingcancer/
the “moonshot”.. *yawn
“A subset of those scientists, engineers and programmers have a different goal: They’re trying to use computer science to solve one of the most complex and deadly challenges humans face: Cancer.”
and powerful algorithms..
“Yet another group of researchers has created powerful algorithms that help scientists understand how cancers develop and what treatments will work best to fight them.”