AIMC Journal:
bioRxiv

Showing 2441 to 2450 of 4979 articles

Neuroscience-Inspired Deep Learning Brain-Machine Interface Decoder

bioRxiv Feb 10, 2026
Brain machine interfaces (BMIs) aim to decode motor intentions from neural activity to enable direct control of external devices. However, most existing decoders rely on monolithic architectures that fail to capture the distinct neural representation...
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A multi-agent platform for assessment and improvement of bioinformatics software documentation

bioRxiv Feb 10, 2026
Rapid advances in bioinformatics have transformed biomedical research in areas such as single-cell and spatial omics, digital pathology, and multi-modal data integration, yet software usability and reproducibility have not kept pace with the growing ...
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Single-Cell and Spatial Transcriptomics Integration Identifies Mural Cell Oxidative Stress Genes Clu and Gria2 as Key Biomarkers in Ischemic Stroke

bioRxiv Feb 10, 2026
Oxidative stress (OS) is a key factor in ischemic stroke (IS), but the characterization of OS-related genes in IS remains largely unexplored. Identifying key OS-associated genes could improve our understanding of OS in IS. We analysed single-cell RNA...
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SERPINA3 and NDRG1 are critical diagnostic immune genes associated with macrophages in preeclampsia

bioRxiv Feb 10, 2026
Objective: The immune system plays a role in the occurrence and progression of numerous pregnancy complications, particularly preeclampsia (PE). This study aims to identify critical immune biomarkers via machine learning and assess their predictive a...
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DUCK-Net: Automated deep learning segmentation of Ductular Reaction in murine liver injury captures multicellular niche dynamics from H&E morphology

bioRxiv Feb 10, 2026
Ductular Reactions (DRs) are dynamic and complex multicellular responses that occur as a result of various hepatic injuries. Precise identification and quantification of the extent of DRs is a cornerstone of pre-clinical modelling of liver disease, w...
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Autoregressive forecasting of future single-cell state transitions

bioRxiv Feb 10, 2026
Existing methods for dynamic analysis of static single-cell RNA-sequencing data can reconstruct temporal structures covered by observed cells, but cannot forecast unobserved future state transitions. We propose a temporal generative AI model, CellTem...
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DynMoCo: a Novel AI Framework to Reveal Modular Substructures of Protein From Molecular Dynamics

bioRxiv Feb 10, 2026
Proteins are dynamic molecular machines whose functions are determined by their structures. While static structures can offer initial insights or hypotheses about protein function, they are often insufficient for a detailed mechanistic understanding....
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Leveraging Foundation Models for the Characterisation of Small RNA Properties

bioRxiv Feb 10, 2026
ABSTRACT Small interfering RNAs (siRNAs) provide a promising therapeutic approach capable of selectively silencing disease-associated genes; however, achieving high efficacy and specificity while minimising off-target effects remains a significant ch...
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AI System Using Unsupervised Learning to Discover Novel Subtypes in Alzheimer's Disease

bioRxiv Feb 10, 2026
Early Alzheimer's disease often evades timely detection because typical diagnostics are based on symptomatic thinking rather than intrinsic neurodegeneration. Here, we use unsupervised machine learning to identify latent Alzheimer's phenotypes from s...
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Multi-omics Analyses of Facial Skin in Acne Identify Distinct Microbial and Metabolic Features at Lesional and Non-lesional Sites

bioRxiv Feb 10, 2026
The microbial and biochemical landscape of clinically normal-appearing skin in individuals with acne remains uncharacterized. Here, we performed longitudinal multi-omics profiling of facial skin from 10 individuals with moderate acne and 10 healthy c...
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