Biology x AI
All Items
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Abstract:
Protein evolution in nature and in the laboratory proceeds through incremental, largely undirected mutational steps, restricting exploration to local regions of sequence space and limiting access to remote yet potentially functional proteins. We present EvoGUD, a single-sequence–conditioned diffusion framework for large-step exploration of protein sequence space under learned evolutionary...
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Abstract:
Both natural and directed evolution are powerful in improving protein functions but they are slow in exploring the nearly endless sequence space. Here, we present SPIN-dvEvo that couples few-shot low-rank adaptation (LoRA) of an ESM-2 protein language model with a genetic algorithm to quickly evolve functional remote homologs from a local cluster of highly-homologous, binary-labeled sequences. We...
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Abstract:
Large language models predominantly rely on the Transformer architecture, whose self-attention mechanism incurs a quadratic computational cost O(N2) with respect to input length, leading to significant memory and computation bottlenecks when processing ultra-long contexts. This work proposes LanguageFold, a hierarchical sparse attention mechanism inspired by the Self-Returning Random Walk model...
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Abstract:
The transport of molecules across biological membranes is essential for life, allowing cells to acquire nutrients, remove waste, maintain cellular homeostasis and communicate with their environment. Although there have been advances in de novo design of functional transmembrane proteins, designing synthetic transporters that robustly and selectively transport specific small molecules across...
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Abstract: Resolving compositional and conformational heterogeneity remains a fundamental bottleneck in single-particle cryo-EM. This challenge stems from a circular dependency: classification requires reliable references, while reference generation requires accurate classification. Current deep learning methods often resort to blind stochastic initialization, frequently becoming trapped in local minima...