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The learning integration of the machine and the life sciences



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Anna Saphington's first moments of glory came when she was a young girl who lived in a house so full of pets she called it a zoo. She grew up on the Gulf of Spike, surrounded by a lush and lively environment, and her father was an environmental scientist. One day, when she found a frog in a dandelion bush, she called him Skippy and built a habitat for him. Later, she and Skippy appeared on the Planet Animal Animal special "What does it love about strange animals?"

Now, a major in computer science and molecular biology, Sappington was selected for another prestigious honor: she is one of the five MIT students selected this year to be a scholarly Marshal. She chose to study computer science because she wanted to have a role to detach and understand data, and she chose biology because of its continuing fascination with nature, cells, genetic inheritance – and of course to Skippy.

"My interests have grown and expanded in different ways, but they are still rooted in my dual natural passion in these two areas," she says.

Eye for Genomic Research

When Sappington came to MIT, it was immediately after her first summer internship at the National Institutes of Health, where she examined genes that could be associated with an increased risk of cardiovascular disease. This was her first experience working with data on human patients, and this gave her inspiration to continue to work in medical research.

When she was a sophomore, Saphington spent the year at the Koch Institute and worked with a graduate student to determine how the liver cells respond to hepatitis B. The following summer, she returned to the NIH to contribute to another project. It is still involved in human health data, but it was more focused on building computational tools. Sappington helped develop an algorithm that would quickly calculate how similar two genomes or proteins were to each other, a technology that could be used to filter for different bacterial strains in real time.

"I wanted to set my feet in all sorts of ways for computer science and biology and human health to interact," she says.

Since returning from the NIH at the start of her second year, Saphington is working at Aviv Regev's lab at a large MIT and Harvard institute. According to her, Regev, a professor in the department of biology at MIT, is nothing but inspiration.

"She herself is only a role model for the world of computational biology," says Saphington.

The main initiative of Regev's lab is an initiative called "The Human Cell Atlas", which was recently named Science Breakthrough of the year. It's like lying on top of a human genome project, she says. They work to identify and categorize different types of cells, such as skin cells and lung cells. The need for catalogs stems from the fact that although these cells have the same DNA genome, they have different special functions and therefore can not be identified by the genome alone.

"In a particular tissue, like your skin tissue, the cells are actually like a complete collage of different molecular profiles and how they express their genes," she says. "So while the basic genome is the same, there are all kinds of other factors that make your cells express these genes – which turn into proteins – in a different way."

Because the human body contains so many different types of cells, teams of researchers work on different parts. Sappington works on data analysis as part of a team that is categorized as retinal cells. It's a unique challenge, she says, because the retina has more than 40 different types of cells, all of which respond to disease in different ways. While still chipping away on retinal retinal cell types, its team recently contributed a retinal cell atlas for a monkey macaque. For her career and research career, Sappington is named 2018-2019 Goldwater Scholar.

Dancing, talking, leading

Before coming to MIT, Saphington was never involved in dancing. But after seeing a window of the Asian dance team in her first year, she decided to try. After a few semesters dancing with ADT, Sappington also joined MIT DanceTroupe, where she found the culture to be creative, supportive, and incredibly fun.

"[I] I just fell in love with the community and the general community of MIT dancers, "she says.

Dance was not the only aspect of the arts and humanities at MIT that she loved. It is also part of the Burchard Scholars Program, which allows students of special interest in the humanities to explore the subject. After she took a linguistics lesson with Professor David Pesetsky in her first year, it became a field of concentration in her humanities. In the end, she took the next level of the class, at the center of which was syntax, and then she and five other students later created their subject in linguistics.

"Substantive linguistics is the study of how the whole language works, and the basic rules governing it," she says. "It's interfaces with brain and cognitive science, and even computer science, and how language is learned and acquired."

Outside the classroom, Sappington has also been involved with TechX, a managed student organization that is responsible for many MIT-related tech events, including HackMit. The events also include Makeathon MakeMIT, Fair Career Spring and the xFair demo technology, and a high school mentoring program to think about. After running and running an events committee, she served as the general manager of TechX in her first year. While she is no longer responsible, she is still grateful to be part of the team.

"Everything was like one big family … Each committee has its own pride between it and the event in which they run, but then everyone also has to rely on each other," she says.

A learning machine across the pool

After graduation, Sappington will be heading to University College in London to earn her MS in machine learning. Its goal is to study machine learning in a context other than biology so that it can learn new and different approaches that it can later apply to biological challenges. The second year of her Marshall Fellowship will be spent at the University of Cambridge, where she will do a whole year of research, most likely involving computer learning applied to medical treatment or other biological questions.

Its ultimate goal is to find new and better ways to use machine learning and technology to improve the health system. To this end, she aspires to receive the MD / PhD after the next two years in England. After volunteering at Massachusetts General Hospital and Shadow Doctors in the Boston area, Sappington is pretty sure she wants a career where she can interact with patients while still involved with computer science and biology. She is excited to move forward with the next chapter of her life – but when it comes to leaving MIT, she has mixed feelings for understanding.

"I think no matter where I go after graduation, it's bitter to leave the amazing community that is the MIT community," she says.

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