Papers
3
Total Citations
87
H-Index
3
About
Janet Newman is a prominent structural biologist and crystallography researcher whose work has significantly advanced the automation and efficiency of macromolecular crystallization and lipidic materials science. Based at a leading research institution, Newman has focused her career on developing high-throughput methodologies that streamline the notoriously challenging process of protein crystallization — a critical bottleneck in structural biology and drug discovery. Her most influential contribution, garnering 43 citations, introduced a groundbreaking protocol for producing and characterizing libraries of self-assembly lipidic cubic phase materials using standard liquid dispensing robotics, overcoming long-standing difficulties associated with handling viscous cubic phases. Her 2008 work on "Phoenito experiments" (34 citations) elegantly integrated multiple commercial crystallization automation platforms, demonstrating how growth-rate modulation, seeding, and additive screening could be effectively combined in medium-throughput workflows. She also contributed to computational image analysis through DroplIT, improving automated droplet identification in the vast image datasets generated by robotic crystallization trials. Newman's research collectively addresses the practical challenges of scaling up structural biology pipelines, making crystallography more accessible and reproducible. Her interdisciplinary approach — bridging robotics, materials science, and structural biology — has made her a valuable contributor to the broader scientific community pursuing macromolecular structure determination.
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