Lisa Boatner, a fourth-year graduate student in the Backus/Houk research groups, has been awarded the prestigious Females in Mass Spectrometry (FeMS) 2023 Rising Star in Computational Mass Spectrometry Award. FeMS is a community-led initiative to create a network of support for women in the field of mass spectrometry.
Before joining the graduate program, Boatner earned her B.S. in Computational Biology and a B.S.A. in Chemistry, with minors in computer science and business from The University of Texas at Austin. It was here that she first discovered her passion for multidisciplinary scientific interests. Additionally, her undergraduate work on developing low-cost diagnostic medical sensors showcased her commitment to practical scientific applications, blending her diverse interests into a coherent research path that bridges technology and healthcare. These foundations set the stage for her current dissertation.
Launched this year, the Rising Star Award provides a $2,000 grant to support Boatner’s pioneering work in exploring the potential druggability of the human proteome through mass spectrometry-based chemoproteomics. Her research, notable for its development and application of computational tools to decipher quantitative structure-activity relationships from high-throughput experiments, is crucial for improving the identification of therapeutic targets and lead compounds with greater efficiency and precision.
A cornerstone of Boatner’s research is her dedication to the principles of open data science. Through the development of sophisticated automation pipelines, the establishment of accessible databases, the crafting of public web interfaces, and the application of machine learning models, she has significantly contributed to making complex data comprehensible and utilizable for the broader scientific community. This effort is underscored by the fact that all her materials and tools are publicly available on GitHub, which ensures that her advancements in computational mass spectrometry are not only openly accessible but can also be freely used, modified, and built upon by researchers worldwide. Such accessibility exemplifies Boatner’s commitment to transparency and collaboration in scientific inquiry, thereby setting a new standard for open science in the field of mass spectrometry.
Supported not only by the FeMS, but also the Chan Zuckerberg Initiative, the University of Toronto, and OpenMS, Boatner’s work underscores the crucial interplay between mass spectrometry and open data science in pushing the boundaries of what’s possible in the realm of computational biology and chemistry. Her contributions are paving the way for future discoveries and innovations in drug development, embodying the spirit of the Rising Star in Computational Mass Spectrometry Award.