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Merger of machine learning and life sciences

Anna Sappington's first moments of fame came when she was a young girl living in a home so full of pets that she calls it a zoo. She grew up on Chesapeake Bay, surrounded by a lush wildlife environment and her dad was an environmental scientist. One day when she found a frog in a shuttle bear, she called him Skippy and built him a living environment. Later, she and Skippy appeared on the Animal Planet TV special "What to love about strange pets?"

Now she has been educated in computer science and molecular biology, Sappington, chosen for another prestigious honor: She is one of five MIT students this year to be Marshall Scholars. She chose to study computer science because she wanted a role in compiling and understanding data, and she chose biology because of her lifelong fascination with nature, cells, genetic heritage ̵

1; and, of course, Skippy.

"My interests have grown and expanded in various ways, but they are still defunct in this natural dual passion that I have for both of these fields," she says.

An Eye for Genomics [19659002]] When Sappington arrived at MIT, it was soon after her first internship at the National Institute of Health, where she examined genes that could be related to increased risk of cardiovascular disease, which was her first experience working with data on human patients, and It inspired her to continue working in medical research.

When she was a first-year student, Sappington spent the year at the Koch Institute and worked with a graduate student to determine how the liver cells respond to infection with hepatitis B virus. NIH to contribute to another project, this still involved human health data, but it was more focused on building one Sappington helped develop an algorithm that would quickly calculate how similar two genomes or proteins were, a technique that could be used to sharpen different bacterial strains in real time.

"I wanted to get my feet wet in all different ways, computer science and biology and human health can interact," she says.

Since returning from NIH at the beginning of her later years, Sappington has worked in Aviv Regev's lab at the Broad Institute of MIT and Harvard. She says that Regev, professor of the MIT Department of Biology, has not become an inspiration.

"She's just an incredible model for the world of computational biology," says Sappington.

The main initiative of Regev's lab is an initiative called Human Cell Atlas, recently named Science's Breakthrough of the Year. It's like a layer on top of the Human Genome Project, she says. They work to identify and catalog different types of cells, such as skin cells and lung cells. The need for cataloging stems from the fact that although these cells have exactly the same DNA genome, they have different special functions and therefore cannot be identified by genome alone.

"Within a certain tissue, like your skin tissue, cells are actually like a whole collage of various molecular profiles in how they express their genes," she says. "So while the underlying genome is the same, there are many other factors that make your cells express these genes – which become proteins – differently."

Since the human body contains so many different types of cells, research teams are working on different parts. Sappington works with data analysis as part of a law that classifies retinal cells. It is 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 falling away in human retinal cell types, her team contributed to a recently published retinal cell atlas for the macaque monkey. For his postgraduate education career, Sappington was named a 2018-2019 Goldwater Scholar.

Dancing, speaking, leading

Before joining MIT, Sappington had never been involved in dance. But after she saw a showcase of Asian Dance Team's first year, she decided to try it. After a few seminars dance with ADT, Sappington also began to participate in MIT DanceTroupe, where she thought the culture was creative, supportive and extremely fun.

"[I] really fell in love with society and the public society dancer at MIT," she says.

Dance was not the only aspect of arts and humanities at MIT that she loved. She is also part of the Burchard Scholars program, which allows students to have a special interest in the humanities to explore that subject. After taking a language course with Professor David Pesetsky's first year, this field became her official humanistic concentration. She ended up taking the next level in the class that centered around the syntax, and then she and five other students later created their own special subject's class in linguistics.

"Essential linguistics is the study of how language works as a whole, and the underlying rules that govern it," she says. "It borders on brain and cognitive science, and even computer science, and how language is learned and acquired."

Outside of the class, Sappington has also been involved with TechX, a student-led organization responsible for many of MIT's tech-related events, including HackMIT, and events include Makeathon MakeMIT, Spring Career Show and Technology MemoFair, and high school mentoring program THINK. and run an event committee, Sappington served as general manager of TechX in her junior year, while she is no longer responsible, she is still grateful to be part of the team.

"It was like a big family. Each committee has its own association of pride with the event that they run, but then everyone must also trust each other, she says.

Machine Learning on the Pond

After graduating, Sappington is coming to University College London to serve her MS in machine learning. Her goal is to explore machine learning in a non-biology context so that she can learn new and different approaches that she can later apply to biological challenges. The second year of her Marshall Scholarship will be spent at Cambridge University where she will do a full year of research, which is likely to mean machine learning applied to healthcare or other biological issues.

Her ultimate goal is to find new and better ways to use machine learning and technology to improve the care system. For that purpose, she aims to get her MD / PhD after the next two years in England. After volunteering at the Massachusetts General Hospital and shadow physicians in the Boston area, Sappington is pretty sure she wants a career where she can interact with patients while still involved in computer science and biology. She is excited to move on to the next chapter of her life – but when it comes to leaving MIT, she has understandably mixed feelings.

"I do not think I should go after graduation, it is bitter to leave the incredible society it is MIT society," she says.

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