Institute launches a new AI initiative to power biological research
With artificial intelligence (AI) poised to greatly accelerate the pace for novel discoveries in foundational biological research, the Stowers Institute launched the Office of Scientific Leadership AI Initiative, a new program designed to advance capabilities in machine learning and AI for addressing critical biological questions. Investigator , has been appointed to lead this effort and leverage cutting-edge computational techniques to accelerate scientific discoveries and drive innovation in biological research.

Zeitlinger will work to develop and execute a long-term strategy to build world-class AI-powered computational expertise. She will head the steering committee that, together with Chief Information Officer Evelyn Travnik and Director of Scientific Data Jay Unruh, Ph.D., prioritizes and implements computational efforts across the organization. She also advises the Stowers Fellows program and the Graduate School to attract, support, and maintain computational talent at the Institute.
“Biology is incredibly complex, and AI is an excellent way to detect the underlying patterns and rules. A great example is the information encoded in our DNA, how it us used to create gene products like proteins, and how those gene products function to support life,” said Zeitlinger. “I am passionate about leading the Institute’s new initiative to promote AI in our scientific research. It is both an exciting challenge and a huge opportunity.”
A fundamental biological quest is to understand how variations within our genetic code and the molecules arising from it not only make us unique but can also underlie disease or disease susceptibility. AI’s predictive capabilities can guide targeted experimental approaches to identify how these variations impact gene regulation and protein function, key factors governing development, health, and disease.
“Many of our investigators including Zeitlinger and our Technology Center scientists are engaged in the pursuit of understanding how sequences within our DNA genetic blueprint control gene activity and how the shape of proteins affects their function,” said Stowers Scientific Director Kausik Si, Ph.D.
“Leveraging the power of AI will enable researchers Institute-wide to answer questions that remain some of the biggest biological mysteries for the benefit of all,” said Stowers President and Chief Scientific Officer Alejandro Sánchez Alvarado, Ph.D.
This article is republished from . Read the original .
Enjoy reading ASBMB Today?
Become a member to receive the print edition four times a year and the digital edition monthly.
Learn moreGet the latest from ASBMB Today
Enter your email address, and we’ll send you a weekly email with recent articles, interviews and more.
Latest in Science
Science highlights or most popular articles

ApoA1 reduce atherosclerotic plaques via cell death pathway
Researchers show that ApoA1, a key HDL protein, helps reduce plaque and necrotic core formation in atherosclerosis by modulating Bim-driven macrophage death. The findings reveal new insights into how ApoA1 protects against heart disease.

Omega-3 lowers inflammation, blood pressure in obese adults
A randomized study shows omega-3 supplements reduce proinflammatory chemokines and lower blood pressure in obese adults, furthering the understanding of how to modulate cardiovascular disease risk.

AI unlocks the hidden grammar of gene regulation
Using fruit flies and artificial intelligence, Julia Zeitlinger’s lab is decoding genome patterns — revealing how transcription factors and nucleosomes control gene expression, pushing biology toward faster, more precise discoveries.

Zebrafish model links low omega-3s to eye abnormalities
Researchers at the University of Colorado Anschutz developed a zebrafish model to show that low maternal docosahexaenoic acid can disrupt embryo eye development and immune gene expression, offering a tool to study nutrition in neurodevelopment.

Top reviewers at ASBMB journals
Editors recognize the heavy-lifters and rising stars during Peer Review Week.

Teaching AI to listen
A computational medicine graduate student reflects on building natural language processing tools that extract meaning from messy clinical notes — transforming how we identify genetic risk while redefining what it means to listen in science.