AIMC Journal:
bioRxiv

Showing 1721 to 1730 of 4956 articles

A Decade of Deep Learning-based Biomedical Image Segmentation

bioRxiv Apr 30, 2026
Biomedical image segmentation is a fundamental problem in computational biomedicine that aims to precisely delineate anatomical and biological structures, tissue types, or pathological regions in biomedical images. Accurate segmentation is essential ...
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NEURA: An agentic system for autonomous neuroimaging workflows

bioRxiv Apr 30, 2026
Neuroimaging is essential for studying the human brain; however, the deep interdisciplinary expertise required imposes a very high threshold, limiting its broader clinical and scientific applications. We introduce NEURA, a large language model (LLM)-...
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Molecular Translators as a Computational Primitive for Biomarker Discovery: Learnability Gains Under Conserved Information Ceilings

bioRxiv Apr 30, 2026
Virtual molecular mapping systems such as MISO and GigaTIME introduce a potentially transformative primitive in computational pathology: translation of H\&E whole-slide images into biologically structured molecular representations, learned on paired ...
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Fast learning, memorization and generalization: A computational characterization of sparse to dense hippocampal-cortical codes

bioRxiv Apr 30, 2026
Classic findings from neuropsychology and animal studies established the hippocampus as a key substrate for rapid learning and episodic memory, with the dentate gyrus exhibiting extreme sparse coding. Sparse coding has long been hypothesized to enabl...
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Sniffing Shapes Dopamine Signals for Reward Prediction

bioRxiv Apr 30, 2026
Adaptive behaviors depend on predicting outcomes from sensory evidence. Dopamine neurons in the ventral tegmental area (VTA) broadcast reward-prediction signals that guide learning. Yet the principles functionally coordinating information flow from i...
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Overcoming systematic data biases enables accurate prediction of enzyme kcat fold-changes for computational protein design

bioRxiv Apr 30, 2026
Machine learning is increasingly used to guide protein engineering by predicting how mutations affect desired properties. Recent models for the turnover number (kcat) of enzymes report high accuracy, suggesting that mutation effects can be inferred d...
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Systems Pharmacology Reveals Type I Interferon and Myeloid-Like B Cell Reprogramming as Druggable Axes in Antiphospholipid Syndrome

bioRxiv Apr 30, 2026
Antiphospholipid syndrome (APS) lacks targeted therapies beyond anticoagulation, and its molecular heterogeneity remains poorly characterized. We employed an integrative systems pharmacology approach combining weighted gene co-expression network anal...
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Species-specific transformer models of bacterial gene order and content for genomic surveillance tasks

bioRxiv Apr 30, 2026
Transformer models enable functionally meaningful representation of complex biological data, such as nucleotide or protein sequences. Existing foundation transformer models are trained on large multi-domain corpuses of unlabelled DNA or protein data,...
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Automatic deep learning-based segmentation and quantification of stented arterial cross-sections for morphometric analysis

bioRxiv Apr 30, 2026
Arterial vascular diseases, such as atherosclerosis, are among the most serious global health threats. In preclinical studies, morphometric analysis of histological arterial cross-sections is considered the gold standard for assessing vascular remode...
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Predicting Phage Host Interactions Across Taxonomic Levels: A Systematic Review and Meta-Analysis for Microbial Ecology

bioRxiv Apr 30, 2026
The prediction of phage-host interactions is key for several applications in biotechnology, medicine, and microbial ecology. Wide studies in machine learning tools have allowed the exploration of these interactions across multiple taxonomic levels. A...
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