The Donnelly Centre welcomes Dr. Aleksandrina Goeva as new Assistant Professor innovating biomedical data analysis

The Donnelly Centre for Cellular and Biomolecular Research welcomes new Assistant Professor Aleksandrina Goeva, who will be integrating mathematics and computational biology to develop new approaches to studying disease and sharing her statistical and machine learning expertise to help other researchers re-envision problem-solving.

Goeva joined the Donnelly Centre on May 1, 2024.

A passion for mathematics was instilled in Goeva from childhood, as her parents encouraged her natural inclination for numbers. This led her to attend the Sofia High School of Mathematics in her home country of Bulgaria. Her interests began to expand beyond mathematics while she was in high school through her involvement in science olympiads in biology, chemistry and physics.

Goeva went on to study applied mathematics at Sofia University in Bulgaria. The computer programming and mathematical modelling skills she learned as an undergraduate student would become the foundation upon which she would study scientific problems in the future.

She then pursued a PhD in mathematics and statistics at Boston University. Goeva’s graduate research focused on using statistical methods to infer characteristics of complex systems, which helped her learn to question the nature of observations and investigate the underlying mechanisms responsible for them.

It was through teaching and mentoring while completing her graduate degree that Goeva realized she wanted to apply her mathematical expertise to solving issues in biological research. She helped establish a consulting unit at Boston University that provided statistical support to researchers from across the campus. The interactive nature of consulting energized Goeva more than working in near-complete isolation as a theoretical statistician.

“My identity evolved from that of a purely theoretical statistician to a modeler of data and a meaningful contributor to collaboration,” said Goeva. “I realized that I wanted to see the real-world applications of my work, which could be achieved by solving applied scientific research problems through mathematical abstraction and statistical thinking.”

Goeva first tried her hand at applying statistics and machine learning to biomedical science as a postdoctoral fellow at the Stanley Center for Psychiatric Research at the Broad Institute of MIT and Harvard. During this time, she developed novel computational methods to extract as much useful information as possible from data. These methods helped to characterize the cellular makeup of complex tissues, such as those found in the brain, and to further our understanding of the biological processes underpinning neurological disease.

One of Goeva’s postdoctoral research projects resulted in the creation of a spatial map of the different cell types in a tissue. The map can be used to model communication between cells in different conditions and across time.

As an assistant professor of molecular genetics at the Donnelly Centre and a faculty affiliate at the Vector Institute, Goeva is now launching a lab that will develop novel statistical and machine learning approaches to study how cells and their interactions change across conditions. The lab will also create comprehensive atlases of brain tissue, spatially map the effects of disease and identify cell interactions that impact disease.

Goeva has already collaborated with Donnelly Centre director and professor Stephane Angers. She applied her computational biology expertise to identifying transcriptional differences between stem cells that could develop into neurons. This collaborative work led to the development of a potential new approach to treating Parkinson’s disease.

“Aleksandrina demonstrated the collaborative spirit of the Donnelly Centre even before she arrived to take up her position as an assistant professor,” said Angers. “She joins our world-leading computational biology group and will add tremendous, sought-after expertise in analyzing single-cell and spatial transcriptomics data, as well as continue to innovate in this area.”

The transition from theoretical mathematics and statistics to machine learning in biology was inspiring, yet challenging, for Goeva. She is now driven by a passion for fundamental computational questions in biomedical data analysis, and is working towards developing solutions and applying them to investigate cell communication in the brain.

“I hope that five years from now I will feel deeply integrated into the Donnelly Centre community,” said Goeva. “I aim to have sustainable, long-lasting collaborations that produce meaningful results to improve how we extract actionable insights from the increasing amount of biomedical data available to inform the treatment of disease.”

Visit Goeva’s faculty profile on the Donnelly Centre website to learn more about her and her research.