T cell receptors (TCRs) are essential for adaptive immune recognition. Recently computational tools have been developed to predict the interactions between TCR and epitope, and artificial intelligence models have been proposed to generate the complem... read more
Despite remarkable advances in protein structure prediction, a fundamental question remains unresolved: how do proteins fold from unfolded conformations into their native states? Here, we introduce PathDiffusion, a novel generative framework that sim... read more
Eastern equine encephalitis virus (EEEV) is a deadly arboviral pathogen with 30% severe case fatality. EEEV exhibits pronounced 2-3 year cyclical outbreak patterns in the northeastern United States, linked to shifts in mosquito feeding preferences be... read more
Computation in recurrent networks of neurons has been hypothesized to occur at the level of low-dimensional latent dynamics, both in artificial systems and in the brain. This hypothesis seems at odds with evidence from large-scale neuronal recordings... read more
Accurately predicting how amino acid substitutions alter protein function is a central challenge in biology, with applications from interpreting disease variants to engineering vaccines and therapeutic proteins. We introduce HERMES, a family of fast,... read more
Genome-wide association studies have linked millions of genetic variants to biomedical phenotypes, but their utility has been limited by lack of mechanistic understanding and widespread epistatic interactions. Recently, Transformer models have emerge... read more
Aging, the leading risk factor for numerous diseases, manifests through diverse structural and architectural changes in human tissues, providing an opportunity to quantify and interpret tissue-specific aging. To address this, we present a comprehensi... read more
ObjectiveOur goal was to create open-source software for closed-loop EEG-TMS that allows researchers to rapidly prototype and develop novel stimulation paradigms in a high-level programming language. This addresses the limitations of current solution... read more
1Reconstructing genomes from metagenomic assemblies is foundational to microbiome research, yet metagenome binning remains constrained by a persistent trade-off between genome fidelity and deployable throughput. Many high-accuracy approaches rely on ... read more
Computational protein design using machine learning models has advanced rapidly since the introduction of AlphaFold2. There is now a suite of tools that enable in silico design of proteins with desired structures and properties. Most design workflows... read more
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