AIMC Journal:
bioRxiv

Showing 111 to 120 of 4935 articles

A moving target: non-stationary selection governs unsupervised prediction of viral fitness

bioRxiv Sep 30, 2026
Anticipating how mutations change viral fitness is central to genomic surveillance and vaccine design, yet the supervised phenotype data behind the most accurate variant-effect predictors are unavailable for most emerging pathogens. We ask how far la...
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Bridging the gap between omics and structural data: A framework for interpreting protein-RNA interaction specificity

bioRxiv Sep 30, 2026
Protein-RNA interactions play a central role in many cellular processes, such as gene regulation, protein synthesis and viral infections. Although a few thousand protein-RNA complexes have been structurally characterized, they represent only a small ...
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Evo 2 as a classification machine: evidence from in-context learning and mechanistic interpretability

bioRxiv Sep 30, 2026
In-context learning (iCL) is an emergent capability of Large Language Models (LLMs), allowing them to perform new tasks at inference time using prompt-injected examples. While extensively studied in LLMs, the boundaries of its capabilities and underl...
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VRPTR prediction of individual language activation and uncertainty from resting state fMRI

bioRxiv Sep 30, 2026
Resting-state connectivity can predict task-evoked fMRI activation, but correspondence with an individual task map may partly reflect a shared population pattern. We evaluated the Variational Resting-state-to-Task Prediction TransformeR (VRPTR), a th...
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RNA-guided contrastive learning enhances patient-level prediction from histology

bioRxiv Sep 30, 2026
Predicting molecular receptor status, including estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2), directly from routine hematoxylin and eosin (H&E)-stained whole-slide images (WSIs) could reduce ...
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Repurposing PeTriBERT for Protein Protein Interaction Prediction with Sequence Structure Fusion

bioRxiv Sep 30, 2026
Recent advances in artificial intelligence have enabled models to capture protein sequence and structural features. We present PeTriPPI2, a hybrid framework for protein--protein interaction (PPI) prediction that combines sequence embeddings from ESM-...
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Physics and Morphology Constrained Quantitative Susceptibility Based Segmentation of Cerebral Veins

bioRxiv Sep 30, 2026
Purpose: Quantitative susceptibility mapping (QSM) provides venous contrast through the paramagnetic susceptibility of deoxyhemoglobin and can be used to estimate oxygen extraction fraction (OEF), a marker of cerebral metabolism. However, cerebral ve...
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Multi-Model Machine Learning Consensus Identifies a Dual-Interferon Gene Signature in Ischemic Stroke: An Integrative Single-Cell Transcriptomic Analysis

bioRxiv Sep 30, 2026
An Ischemic stroke is one of the main causes of death and long-term disability around the world. There are very few treatment options available, especially for the cases where the short time period to give clot dissolving medicine has passed (Powers ...
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Animate-inanimate object categorization from minimal visual information in the human brain, human behavior, and deep neural networks

bioRxiv Sep 30, 2026
The distinction between animate and inanimate things is a main organizing principle of information in perception and cognition. Yet, animacy, as a visual property, has so far eluded operationalization. Which visual features are necessary and sufficie...
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Mendel, a foundation model of human genetic variation, prioritizes regulatory variants and improves gene expression prediction

bioRxiv Sep 30, 2026
Human genome-wide association studies have identified hundreds of thousands of variant trait associations, but interpreting their mechanistic consequences at allele resolution remains a central bottleneck. DNA foundation models pretrained on genomic ...
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