bioRxiv

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ARCADE: Controllable Codon Design from Foundation Models via Activation Engineering

bioRxiv Jan 1, 2025
Codon sequence design is crucial for generating mRNA sequences with desired functional properties for tasks such as developing mRNA vaccines or gene editing therapies. Yet existing methods lack flexibility and controllability to adapt to various desi...
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A large language model for predicting pancreatic ductal adenocarcinoma patients from blood-derived exosomal transcriptomics data

bioRxiv Jan 1, 2025
Traditional machine learning approaches for text or sequence classification rely on converting textual data into numerical representations. In this study, we investigate a reverse strategy in which numerical features are transformed into sequence rep...
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High-Quality Predicted Pathway Annotations Greatly Improve Pathway Enrichment Analysis of Metabolomics Datasets

bioRxiv Jan 1, 2025
Metabolism-level interpretation of metabolomics datasets requires aggregation analyses across metabolites. One highly-used aggregation analysis is pathway enrichment analysis (PEA), which involves detecting pathways enriched with metabolites that are...
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Phylogeny-agnostic strain-level prediction of phage-host interactions from genomes

bioRxiv Jan 1, 2025
Bacteriophages offer promising alternatives to antibiotics for treating drug-resistant infections and engineering microbiomes, but applications are limited by inability to select phages infecting specific strains. Selecting suitable phages requires e...
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Nuclear Irregularity as a Universal Diagnostic Tool in Solid Tumors

bioRxiv Jan 1, 2025
As tumors develop, cancer cells accumulate diverse genomic and phenotypic alterations to meet heightened demands for energy production and biosynthesis. Loss of lamina function and perturbations in energy production are associated with pronounced abe...
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AI-driven discovery and optimization of antimicrobial peptides from extreme environments on global scale

bioRxiv Jan 1, 2025
The escalating crisis of global antimicrobial resistance (AMR) necessitates the discovery of novel antibiotics. Antimicrobial peptides (AMPs), particularly those from under-explored extreme environments, represent a promising therapeutic class. Here,...
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Learning dynamically regulates stimulus discrimination of ventral striatal D1 receptor expressing neurons

bioRxiv Jan 1, 2025
Animals encounter a barrage of sensory stimuli, but only a subset of these are associated with appetitive outcomes, highlighting the importance of neural mechanisms for learning to distinguish reward-paired from unpaired cues. The ventral striatum pl...
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A predicted structural interactome reveals binding interference from intrinsically disordered regions

bioRxiv Jan 1, 2025
Proteins function through dynamic interactions with other proteins in cells, forming complex networks fundamental to cellular processes. While high-resolution and high-throughput methods have significantly advanced our understanding of how proteins i...
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Context-aware geometric deep learning for RNA sequence design

bioRxiv Jan 1, 2025
RNA design has emerged to play a crucial role in synthetic biology and therapeutics. Although tertiary structure-based RNA design methods have been developed recently, they still overlook the broader molecular context, such as interactions with prote...
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Assessment of Visual Function in Mice Using Light/Dark Box and Multi-Feature Machine Learning

bioRxiv Jan 1, 2025
The light/dark box test can be used to assess visual function in rodents based on their spontaneous behavior in response to light. Commonly used assay relies on a single behavioral metric, dwell time in the light or dark compartment, which may be inf...
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