Researchers are embarking on the RNA equivalent of the Human Genome Project, including sequencing all the chemical modifications that make cells unique.
PLAID is a multimodal generative model that can generate protein sequence and all-atom structure based on conditional function and taxonomic prompts. Please see our ...
Our Atomic Composition Protein Calculator provides a precise elemental breakdown of your protein sequence. By simply inputting a sequence, this tool calculates the exact number of Carbon (C), Hydrogen ...
This fundamental study presents a compelling and comprehensive analysis of the newly defined Lipocone superfamily, offering unprecedented insights into the evolutionary origins of Wnt proteins. The ...
Welcome to the inference code for the paper "Protein Sequence Modelling with Bayesian Flow Networks". With this code, you can sample from our trained models ProtBFN, for general proteins, and AbBFN, ...
Pranam Chatterjee, PhD, assistant professor of bioengineering at the University of Pennsylvania (UPenn), emphasizes that text is all you need for artificial intelligence (AI) models to effectively ...
Our Protein Extinction Coefficient Calculator is a comprehensive, web-based tool for analyzing the essential biochemical and physical properties of your protein sequences. By simply inputting a ...
Protein engineering holds significant promise for designing proteins with customized functions, yet the vast landscape of potential mutations versus limited lab capacity constrains the discovery of ...
The authors report how a previously published method, ReplicaDock, can be used to improve predictions from AlphaFold-multimer (AFm) for protein docking studies. The level of improvement is modest for ...
This article was featured in One Great Story, New York’s reading recommendation newsletter. Sign up here to get it nightly. Chungin “Roy” Lee stepped onto Columbia University’s campus this past fall ...
Abstract: In this paper, we investigate the sequence-based protein-protein interaction prediction by machine learning methods. Specifically, we propose to build classifiers in the space of domain ...