AIMC Journal:
bioRxiv

Showing 1111 to 1120 of 4938 articles

Network analysis of α-synuclein pathology progression reveals p21-activated kinases as regulators of vulnerability

bioRxiv Jun 12, 2026
-Synuclein misfolding and progressive accumulation drive a pathogenic process in Parkinson's disease, yet many brain regions develop more or less pathology than would be predicted by connectivity alone, indicating that intrinsic biological factors in...
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XL-MS-Guided Structure Prediction of Disordered Encephalitozoon hellem Proteins

bioRxiv Jun 12, 2026
Microsporidia such as Encephalitozoon hellem are obligate intracellular human parasites that remain genetically intractable, limiting functional characterization of their proteomes. Structural studies based on homology-based modeling and the use of d...
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The dynamic relationship between pupil dilation and neural surprise in natural language comprehension

bioRxiv Jun 12, 2026
Predictive processing accounts hold that the brain continuously generates predictions and updates internal models from error signals, but it remains unclear whether prediction representation and model-updating reflect a single graded computation or c...
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MipSScs: Artificial neural network-based data integration of 2D/3D single-cell spatial RNA sequence data from virus-infected human cerebral organoids

bioRxiv Jun 11, 2026
There is interest in the use of recent single-cell spatial transcriptomic technologies to gain biological insights into disease mechanisms. Previously, we characterized the use of herpes simplex virus 1 (HSV-1) induced neuroinflammation in 2D dissoci...
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An AI-Powered Trisomy 21 Research Assistant

bioRxiv Jun 11, 2026
Down syndrome, caused by trisomy 21, increases the risk of diverse co-occurring conditions. With more than 34,000 related publications indexed in PubMed as of early 2026, keeping pace with this expanding literature is challenging. While general-purpo...
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Calibrated Uncertainty Quantification for Patient-Level AML Drug Sensitivity Prediction Using Split Conformal Prediction

bioRxiv Jun 11, 2026
Accurate prediction of ex vivo drug sensitivity in acute myeloid leukemia (AML) patients from transcriptomic data is a critical challenge for precision oncology. Existing computational approaches have explored uncertainty quantification in cancer dru...
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Breaking the bottleneck: self-supervised deep learning framework for fully automated fossil CT segmentation

bioRxiv Jun 11, 2026
Semantic segmentation of domain-specific imaging data where labelled training examples are scarce and foreground-background contrast is low remains an open challenge in deep learning applied to science. Palaeontological computed tomography (CT) exemp...
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Machine Learning-Guided Discovery of Bacterial-Selective Membrane-Active Compounds Reveals Mechanistic Bias in Antibiotic Training Datasets

bioRxiv Jun 11, 2026
The rise of antibiotic resistance necessitates the discovery of antibacterial compounds with novel mechanisms of action (MoAs). Recent machine learning approaches have shown promise in antibacterial compound discovery, but often identify derivatives ...
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AGZArank: Investigating epitope-conditioned antibody binder ranking with structure-derived synthetic supervision

bioRxiv Jun 11, 2026
Computational antibody design methods can generate large libraries of candidate binders for a target epitope, but prioritizing which candidates to test experimentally remains a major bottleneck. Existing scoring approaches, including physics-based af...
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GermRL: Alleviating The Germline Bias In Autoregressive Antibody Language Models Through Reinforcement Learning

bioRxiv Jun 11, 2026
Antibodies are powerful therapeutics whose antigen specificity arises from sequence diversity shaped during development. Recently, language models trained on large antibody repertoire datasets have enabled the generation and screening of novel candid...
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