Faculty In Focus: Jeff Nivala

Why It Matters

By enabling direct, full‑length protein analysis, this platform could shorten drug discovery cycles and improve early disease detection, reshaping biotech and clinical practice.

Key Takeaways

• New tech reads full-length proteins directly, preserving native state.
• Current sequencing fragments proteins, losing critical functional information.
• Lab merges computer science, biotech, and machine learning for protein analysis.
• Proof-of-concept achieved; aims for clinical and research deployment.
• Potential to accelerate diagnostics, therapeutics, and fundamental biology insights.

Summary

Assistant Professor Jeff Nivala of the Paul G. Allen School outlines a new technology that reads individual protein molecules end‑to‑end, preserving their native structure. The Molecular Information Systems Lab sits at the crossroads of computer science and biotechnology, aiming to make the invisible complexity of nanoscale biology observable.

Current protein‑sequencing methods fragment proteins into short peptides and computationally reassemble them, discarding crucial information about full‑length conformation and post‑translational modifications. Nivala’s approach captures whole proteins directly, providing a more accurate view of how genes translate into functional molecules.

“The rubber really meets the road at the level of proteins,” Nivala says, emphasizing the shift from gene‑centric to protein‑centric analysis. His interdisciplinary team—spanning molecular biology, biochemistry, microbiology, machine learning, and hardware engineering—has already demonstrated proof‑of‑concept experiments that read intact proteins in a CS‑building wet lab.

If scaled, the technology could transform diagnostics by detecting disease‑related protein changes earlier, accelerate therapeutic design, and give researchers a universal tool for fundamental biology. Nivala envisions widespread adoption by biologists, clinicians, and engineers within the next decade.

Original Description

In this episode of the Allen School’s “Faculty in Focus” series, Assistant Professor Jeff Nivala of the Molecular Information Systems Laboratory talks about his work on technologies for reading and analyzing full-length protein molecules to reveal how each functions at the molecular level. Nivala’s research aims to advance our understanding of fundamental biology and support the development of new diagnostics and therapeutics for when biology goes wrong.

This video is closed captioned.