Proteins
From fitness prediction and uncertainty to sequence and structure generation with experimental feedback.
Microsoft Research
Accelerating how scientists
Accelerating how scientists
explore biology
Quine brings artificial intelligence and experimental research together to explore biological questions. We are opening it to a small group of researchers to learn where it can accelerate discovery, where it falls short, and what we should build next.
Quine overview
Meet Quine
The Quine overview video will be added here.
Biological research often advances through slow cycles of proposing, testing, and revising ideas. A single experiment can take weeks or months, and negative results still consume scarce samples, time, and attention. We are exploring whether better computational guidance can help researchers consider more possibilities and use physical experiments only where they provide the most useful information.
A research system with three parts
The model is being developed to connect evidence across proteins, cells, tissues, and genomes. The tool layer is being developed to help researchers break questions into steps, use models and scientific tools, compare evidence, and revise a plan. Through the research program, Microsoft scientists, Fellows, collaborators, and experimental partners evaluate the system through real-world biological research questions.
These parts are developed together. Scientific questions reveal which capabilities and data matter. Model and tool improvements expand what researchers can test. Experimental results provide evidence about what worked, what failed, and what researchers should improve or explore next.
Why we are inviting researchers in
We have working components and promising results. The important test now is whether Quine improves scientific work. The Fellows program will help us understand where Quine is useful, where it falls short, and how scientists should shape its development.
Our work
The research behind Quine.
Quine builds on years of research at Microsoft across proteins, regulatory genomics, cancer cell state, pathology, microscopy, and biological data. Our research journey follows how those independent lines of inquiry developed, challenged assumptions, and began to inform a shared system.
Regulatory genome
Using evolutionary signals to study functional constraints and computationally generate and evaluate regulatory sequences.
Tumor microenvironment
Connecting cell state, environmental context, drug response, and scalable experimental systems.
Tissue pathology
Learning from whole-slide images, multiple magnifications, clinical-domain text, and genomic biomarker information.
Microscopy
Distinguishing biological signal from batch effects, neighboring-cell context, and other misleading patterns in experimental data.
Biological data
Studying how dataset composition, comparison, and scale shape what models learn and how well they generalize.
See how the work came together.
The research journey traces six lines of work across biology and machine learning, showing where they overlapped and how we arrived at Quine.
Quine Research Fellowship
Bring your research question to Quine.
A 16-week research fellowship with financial support, hosted by Microsoft Research in Cambridge, MA, for PhD candidates, postdocs, research scientists, and academic or independent researchers.
- ApplicationsSeptember 29–November 2, 2026
- FellowshipJune 7–September 24, 2027
- SupportFellows will collaborate with Microsoft researchers and receive access to Quine and computing resources. They may also receive experimental support where appropriate for their projects
Areas of interest
- 01Protein design and engineering
- 02Research involving enzyme design, discovery, and optimization
- 03Genetic and chemical perturbation of cell state
- 04Early-stage therapeutic research in under-resourced disease areas, including hypothesis and compound prioritization for further investigation
- 05Adjacent problems where faster iteration between design and experiment could change the outcome
The application submission deadline and participation requirements, including any required activities in Cambridge, MA, are described in the application materials. Participation, access, support, and research resources are subject to eligibility, selection, available capacity, and written Fellowship terms. Applying does not guarantee selection or access.
General inquiries
Questions about Quine?
Contact the team about Quine, our research, or the Fellows program.
quine-inquiries@microsoft.com
Please do not submit confidential, personal, clinical, or proprietary research information by email.