Proceedings of the National Academy of Sciences of the United States of America
Most Recent
bioRxiv
OpenCell: proteome-scale endogenous tagging enables the cartography of human cellular organization
Jill Bouchard
Managing editor, Condensates.com
Not only is this a really cool method at the intersection of proteomics and imaging, the database if full of amazing pictures!
bioRxiv
Yeast proteins reversibly aggregate like amphiphilic molecules
Nature Biotechnology
Drug startups coalesce around condensates
Cell reports
Predicting protein condensate formation using machine learning
Current opinion in structural biology
Artificial intelligence techniques for integrative structural biology of intrinsically disordered proteins
Jill Bouchard
Managing editor, Condensates.com
Is it time for you to find out what AI can tell you about your favorite condensate-loving IDP? I would start here.
Nanoscale
Rapid prediction of drug inhibition under heat stress: single-photon imaging combined with a convolutional neural network
Jill Bouchard
Managing editor, 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
MPI: Collective processes in non-equilibrium systems (winter term 2020/21)
Tuesday, November 3, 2020
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
Managing editor, Condensates.com
Developments in microfluidic methods seem to have exploded this year. This review might spark some ideas for studying aggregation-prone condensates.
bioRxiv
Phase separation of tunable biomolecular condensates predicted by an interacting particle model
Blavatnik National Awards for Young Scientists Announce 2020 Laureates
Proteins
cnnAlpha: Protein Disordered Regions Prediction by Reduced Amino Acid Alphabets and Convolutional Neural Networks
Jill Bouchard
Managing editor, 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...
Cytometry Part A : the journal of the International Society for Analytical Cytology
Development of Automated Microscopy-Assisted High-Content Multiparametric Assays for Cell Cycle Staging and Foci Quantitation
Trends in biochemical sciences
Learning of Signaling Networks: Molecular Mechanisms
bioRxiv
3D neural network-based particle tracking reveals spatial heterogeneity of the cytosol
Jill Bouchard
Managing editor, Condensates.com
Not to be confused with nuclear gems, these GEMs were used to carefully image and map the contents of the cytosol. How clever!
SLAS Europe 2019: Innovative Technologies for Tomorrow’s Discoveries
Wednesday, June 26, 2019 | Barcelona, Spain
Deep Learning for Image Analysis – EMBL Course
Monday, January 20, 2020 | Heidelberg, Germany
bioRxiv
Prediction of liquid-liquid phase separation proteins using machine learning
Jill Bouchard
Managing editor, Condensates.com
What a good idea: using machine learning to improve sequence prediction of phase separation!
eLife