Nicholas Pearce

DDLS Fellow, Linköping University

Key publications

Pearce, N. M., & Gros, P. (2021).
A method for intuitively extracting macromolecular dynamics from structural disorder.
Nature Communications

Ploscariu, N., Burnley, T., Gros, P., & Pearce, N. M. (2021).
Improving sampling of crystallographic disorder in ensemble refinement.
Acta Crystallographica Section D Structural Biology

Pearce, N. M., et al. (2017).
A multi-crystal method for extracting obscured crystallographic states from conventionally uninterpretable electron density.
Nature Communications

Pearce, N. M., et al. (2017).
Partial-occupancy binders identified by the Pan-Dataset Density Analysis method offer new chemical opportunities and reveal cryptic binding sites.
Structural Dynamics

Pearce, N. M., Krojer, T., & von Delft, F. (2017).
Proper modelling of ligand binding requires an ensemble of bound and unbound states.
Acta Crystallographica Section D Structural Biology

Collins, P. M., et al. (2017).
Gentle, fast and effective crystal soaking by acoustic dispensing.
Acta Crystallographica Section D Structural Biology

Nicholas Pearce

Research Interests

In the Data-Driven Determination of Macromolecular Structures (D3MS) group, we develop new experimental and computational approaches to unravel the subtleties of protein structures and achieve unprecendented levels of detail in macromolecular models.

We use a variety of computational and experimental approaches, from mathematical models to machine learning, and from crystallography to cryoEM. We use these tools to design new ways of determining macromolecular structures that reveals more about how they function.

What connects all of our methods is the idea that decisions should be driven by the data.

We are part of the bioinformatics division at Linköping University. In addition to our SciLifeLab affiliation through the DDLS program, we are part of the Wallenberg Centre for Molecular Medicine (WCMM) at Linköping.



Last updated: 2023-01-31

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