Computational Biology

Experimental methods in biology and medicine have created exciting challenges for computer science. With large sets of diverse biological information there is opportunity to develop novel methods for complex, accurate, and consistent interpretation of the data. Insights from computational biology can advance basic science, aid in engineering design, and improve health outcomes at many levels, including in research, policy and clinical settings.

At Princeton, researchers in computational biology use the tools of computer science — algorithmic design, bioinformatics, statistics, artificial intelligence, and machine learning — to address fundamental questions in biology and medicine.

Associated Faculty

• Adji Bousso Dieng
• Kai Li
• Yuri Pritykin
• Ben Raphael
• Sebastian Seung
• Mona Singh
• Olga Troyanskaya
• Ellen Zhong

Associated Graduate Students

• Javed Muhammad Aman
• Anushri Arora
• Yitao Chen
• Uthsav Rajaram Chitra
• Rachit Dubey
• Brian Jo
• Anna Konvicka
• Tim Kosfeld
• Tyler Park
• Ahmed Shuaibi
• Riley Simmons-Edler
• Ksenia Sokolova
• Tedi Zadouri
• Yuqi Zhang
• Zhiyue Zhang