TY - JOUR
KW - Biotechnology
KW - Machine Learning
KW - medical research
AU - Vishwanatha M. Rao
AU - Serena Zhang
AU - Brian S. Plosky
AU - Patrick D. Hsu
AU - Bo Wang
AU - James Zou
AU - Marinka Zitnik
AU - Eric J. Topol
AU - Pranav Rajpurkar
AB - Generalist biological artificial intelligence (GBAI) represents a transformative approach to modeling the ‘language of life’—the flow of information from DNA to cellular function. This Review synthesizes rapid advances in biological AI to interpret and generate DNA, RNA, proteins and cellular systems. We chart a course toward comprehensive systems that can concurrently process and predict across these domains, performing several critical biological tasks simultaneously. Substantial opportunities lie in synergizing language and structural AI, leveraging specialized models and improving AI agents for autonomous discovery. After addressing challenges in data, biological complexity, scalability and experimental validation, GBAI has the potential to deepen our understanding of disease pathways and biomarkers, advance automated therapeutic design and evaluation, and integrate within virtual cells to meaningfully simulate biological activity.
BT - Nature Biotechnology
DA - 2026-03-20
DO - 10.1038/s41587-026-03064-w
LA - en
N2 - Generalist biological artificial intelligence (GBAI) represents a transformative approach to modeling the ‘language of life’—the flow of information from DNA to cellular function. This Review synthesizes rapid advances in biological AI to interpret and generate DNA, RNA, proteins and cellular systems. We chart a course toward comprehensive systems that can concurrently process and predict across these domains, performing several critical biological tasks simultaneously. Substantial opportunities lie in synergizing language and structural AI, leveraging specialized models and improving AI agents for autonomous discovery. After addressing challenges in data, biological complexity, scalability and experimental validation, GBAI has the potential to deepen our understanding of disease pathways and biomarkers, advance automated therapeutic design and evaluation, and integrate within virtual cells to meaningfully simulate biological activity.
PY - 2026
SP - 1
EP - 16
T2 - Nature Biotechnology
TI - Generalist biological artificial intelligence in modeling the language of life
UR - https://www.nature.com/articles/s41587-026-03064-w
Y2 - 2026-03-23
SN - 1546-1696
ER -