bioRxiv

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Viral Sentry AI (VirSentAI) - Automated Zoonotic Surveillance & Drug Repurposing Agent

bioRxiv Jan 1, 2025
Zoonotic viruses capable of jumping from animal reservoirs into human populations represent a persistent and unpredictable menace to global health. To confront this challenge, we developed Viral Sentry AI (VirSentAI), an autonomous agent designed to ...
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Weakly supervised learning uncovers phenotypic signatures in single-cell data

bioRxiv Jan 1, 2025
To deliver clinically relevant insights from large patient cohorts profiled with single-cell technologies, a key challenge is to relate sample-level and single-cell measurements. We present MultiMIL, a deep learning framework that applies attention-b...
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SpaCEy: Discovery of Functional Spatial Tissue Patterns by Association with Clinical Features Using Explainable Graph Neural Networks

bioRxiv Jan 1, 2025
Tissues are complex ecosystems tightly organized in space. This organization influences their function, and its alteration underpins multiple diseases. Spatial omics allows us to profile its molecular basis, but how to leverage these data to link spa...
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Sparse, random sampling is sufficient for central tolerance

bioRxiv Jan 1, 2025
Negative selection in the thymus limits autoimmunity by eliminating T cells that react strongly to self. Individual T cells, however, are only exposed to a small fraction of all self peptides during their “training” in the thymus, and it is puzzling ...
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PlantCAD2: A Long-Context DNA Language Model for Cross-Species Functional Annotation in Angiosperms

bioRxiv Jan 1, 2025
Understanding how DNA sequence encodes biological function remains a fundamental challenge in biology. Flowering plants (angiosperms), the dominant terrestrial clade, exhibit maximal biochemical complexity, extraordinary species diversity (over 100,0...
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Temporal Perturbation Scanning: AI-Driven Deconstruction of Universal Biomolecular Recognition Mechanisms

bioRxiv Jan 1, 2025
Understanding the physicochemical principles governing intermolecular recognition remains a fundamental challenge across biochemistry, drug discovery, and synthetic biology. While molecular dynamics simulations capture interaction dynamics and machin...
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Machine learning inference of natural product chemistry across biosynthetic gene cluster types

bioRxiv Jan 1, 2025
With ever-increasing volumes of sequencing data for biosynthetic gene clusters (BGCs), computational methods for the prediction of resulting secondary metabolites are critically needed. Here, we present CHAMOIS, a machine learning tool inferring meta...
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Coxmos: Interpretable survival models for high-dimensional and multi-omic data

bioRxiv Jan 1, 2025
Survival analysis in high-dimensional (HD) and multi-block (MB) settings, such as omic and multi-omic studies, poses major methodological challenges due to multicollinearity, low events-per-variable ratios, and limited model interpretability. While C...
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Counterfactual Diffusion Models for Interpretable Explanations of Artificial Intelligence Models in Pathology

bioRxiv Jan 1, 2025
Deep learning can extract predictive and prognostic biomarkers from histopathology whole slide images. However, explainable artificial intelligence approaches widely used in digital pathology, such as attention heatmaps and class activation mapping, ...
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Inferring spatial gene expression from tissue images using large-scale histology foundation model with SpaFoundation

bioRxiv Jan 1, 2025
Spatial transcriptomics (ST) has revolutionized biological research by enabling the joint profiling of gene expression and spatial context, along with histological images. However, current existing ST technologies remain high-cost and time-consuming,...
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