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rstoolbox - a Python library for large-scale analysis of computational protein design data and structural bioinformatics

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rstoolbox - a Python library for large-scale analysis of computational protein design data and structural bioinformatics

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Computational design of complex protein folds and soluble analogs of membrane proteins

Opportunities and challenges in design and optimization of protein function

Investigating the intra-molecular and inter-molecular effects of post-translational modifications on intrinsically disordered protein regions and structured protein regions

Predicting protein interactions using geometric deep learning on protein surfaces

From Sequence to Dynamics to Function: Computational Design of Allostery and Ligand Selectivity in G-Protein Coupled Receptors

Engineering novel protein interactions with therapeutic potential using deep learning-guided surface design

Microsecond Time-Resolved Cryo-Electron Microscopy

Towards improving full-length ribosome density prediction by bridging sequence and graph-based representations

Synergetic Support of Cartilage Homeostasis via Coupled Thermal-Hydrostatic Pressure Stimuli

Modulating Weak Protein-Protein Cross-Interactions by the Addition of Free Amino Acids at Millimolar Concentrations

Development of tools and methods for protein identification: From single molecules to in vivo applications

Magnesium Optrodes for Real-Time Optical Monitoring of Water Transport in Ultrathin Encapsulations for Bioelectronics

Orchestrating chromosome conformation capture analysis with Bioconductor

Prolamins' 3D structure: A new insight into protein modeling using the language of numbers and shapes

Multi-well plate lid for single-step pooling of 96 samples for high-throughput barcode-based sequencing

Recording physiological history of cells with chemical labeling

Mechanisms and functions of protein S-acylation

Microsecond time-resolved cryo-electron microscopy

Live-cell imaging powered by computation

Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain