bioRxiv

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Cross-Molecular Active Learning for the Discovery of Antimicrobial Polyacrylamides

bioRxiv Jan 1, 2025
Antimicrobial resistance poses an urgent and increasing threat to global health. The development of new antimicrobials is crucial. Synthetic copolymers are attractive as a potential solution, because they can be produced at scale and designed to mimi...
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Melody: Decoding the Sequence Determinants of Locus-Specific DNA Methylation Across Human Tissues

bioRxiv Jan 1, 2025
DNA methylation is a fundamental epigenetic modification that plays crucial roles in transcriptional regulation, cellular differentiation, and genome stability. However, how locus-specific DNA methylation is determined by intrinsic DNA sequence featu...
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Aligning transformer circuit mechanisms to neural representations in relational reasoning

bioRxiv Jan 1, 2025
Relational reasoning—the capacity to understand how elements relate to one another—is a defining feature of human intelligence, yet its computational basis remains unclear. Here, we combined human neuroimaging (7T fMRI) with artificial neural network...
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Cellohood: multi-granular discovery of cellular neighborhoods with a permutation-invariant set transformer auto-encoder

bioRxiv Jan 1, 2025
Discovering cellular neighborhoods and their roles in disease requires computational methods that consider the full breadth of data and offer multi-level granularity and interpretability. Here, we introduce Cellohood, a permutation-invariant set tran...
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PARAS: high-accuracy machine learning of substrate specificities in nonribosomal peptide synthetases

bioRxiv Jan 1, 2025
Nonribosomal peptides are diverse natural products with important applications in medicine and agriculture. Bacterial and fungal genomes contain thousands of nonribosomal peptide biosynthetic gene clusters (BGCs) of unknown function, providing a prom...
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Heimdall: A Modular Framework for Tokenization in Single-Cell Foundation Models

bioRxiv Jan 1, 2025
Foundation models trained on single-cell RNA-sequencing (scRNA-seq) data have rapidly become powerful tools for single-cell analysis. Their performance, however, depends critically on how cells are tokenized into model inputs – a design space that re...
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Iterative immunogen optimization to focus immune responses on a conserved, subdominant viral epitope

bioRxiv Jan 1, 2025
Designing effective vaccination strategies against genetically diverse viruses, such as HIV or influenza, is hindered by the ability of these pathogens to mutate and readily evade immune control. While these viruses contain conserved regions that can...
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Ancestral Sequences Cannot be Accurately Reconstructed via Interpolation in a Variational Autoencoder’s Latent Space

bioRxiv Jan 1, 2025
Standard methods for ancestral sequence reconstruction (ASR) rely on substitution models for the residues in a biological sequence and assume independent evolution across these sites, ignoring the epistatic interactions that shape molecular evolution...
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A Neurodevelopment-Inspired Deep Spiking Neural Network for Auditory Spatial Attention Detection using Single Trial EEG

bioRxiv Jan 1, 2025
This study presents a deep probabilistic spiking neural network designed to extract discriminative spatiotemporal features from EEG signals associated with rightward and leftward auditory attention. The network self-organizes its synaptic weights and...
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E1: Retrieval-Augmented Protein Encoder Models

bioRxiv Jan 1, 2025
Large language models trained on natural proteins learn powerful representations of protein sequences that are useful for downstream understanding and prediction tasks. Because they are only exposed to individual protein sequences during pretraining ...
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