Biomolecules
Most Recent
Nature biotechnology
Rationalized deep learning super-resolution microscopy for sustained live imaging of rapid subcellular processes
Array
Must ReadVIDEO: Alex Holehouse on A Computational Ecosystem for Exploring Disordered Proteins and Condensates
Bioinformatics
PScL-DDCFPred: an ensemble deep learning-based approach for characterizing multiclass subcellular localization of human proteins from bioimage data
The journal of physical chemistry B
Viscosity Measurement in Biocondensates Using Deep-Learning-Assisted Single-Particle Rotational Analysis
Array
Must ReadVIDEO: Emma Lundberg on Mapping the Spatiotemporal Proteome Architecture of Human Cells
iScience
Activation of gene expression by detergent-like protein domains
Biophysical journal
metapredict: a fast, accurate, and easy-to-use predictor of consensus disorder and structure
Array
SGnn
Frontiers in molecular biosciences
SGnn: A Web Server for the Prediction of Prion-Like Domains Recruitment to Stress Granules Upon Heat Stress
Nature
Highly accurate protein structure prediction with AlphaFold
Jill Bouchard
Editor in Chief, Condensates.com
This is one of two big papers that came out on the same day and could reshape how we study proteins involved in condensates. See also the Science paper about RoseTTAFold.
Science
Accurate prediction of protein structures and interactions using a three-track neural network
Jill Bouchard
Editor in Chief, Condensates.com
This is one of two big papers that came out on the same day and could reshape how we study proteins involved in condensates. See also the Nature paper about AlphaFold.
BioRxiv
metapredict: a fast, accurate, and easy-to-use cross-platform predictor of consensus disorder
Jill Bouchard
Editor in Chief, Condensates.com
Wanna try a new deep-learning disorder predictor that's been trained on consensus scores? Give this one a shot...
Bioinformatics (Oxford, England)
In-silico prediction of in-vitro protein liquid-liquid phase separation experiments outcomes with multi-head neural attention
Nanoscale
Rapid prediction of drug inhibition under heat stress: single-photon imaging combined with a convolutional neural network
Jill Bouchard
Editor in Chief, Condensates.com
This could be a really useful method for anyone wanting to screen drugs that may modulate stress granules.
bioRxiv
Machine learning models for predicting protein condensate formation from sequence determinants and embeddings
Frontiers in bioengineering and biotechnology
Potential of Microfluidics and Lab-on-Chip Platforms to Improve Understanding of ” prion-like” Protein Assembly and Behavior
Jill Bouchard
Editor in Chief, Condensates.com
Developments in microfluidic methods seem to have exploded this year. This review might spark some ideas for studying aggregation-prone condensates.
Proteins
cnnAlpha: Protein Disordered Regions Prediction by Reduced Amino Acid Alphabets and Convolutional Neural Networks
Jill Bouchard
Editor in Chief, Condensates.com
These authors put machine learning to work for predicting disordered regions. Have you tried it yet? It might turn out to be useful for new proteins found in condensates...
Assistant Professor of Biological Neurochemistry (Tenure Track)
Radboud University | Nijmegen, Netherlands
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