AIMC Journal:
bioRxiv

Showing 2551 to 2560 of 4979 articles

Reconstructing N-Glycan Profiles of Individual Glycoproteins from the Total Blood Plasma N-Glycome: Implications for Immunoglobulin G N-Glycosylation GWAS

bioRxiv Feb 2, 2026
The genetic regulation of the plasma N-glycome variation in human populations is not fully characterized, partly due to the limited sample size in glyco-genetics studies. Here, we aimed to demonstrate that protein-specific N-glycan profiles, like tho...
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Serum Proteomic Profiling Implicates a Dysregulated Neurohormonal-Inflammatory Axis in Post-Fontan Tachycardia

bioRxiv Feb 2, 2026
Background: Post-operative tachycardia is a common and poorly understood complication following the Fontan procedure. Post-operative factors such as surgical scarring and venous hypertension can contribute to tachycardia risk, but the specific molecu...
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DeepUnitMatch: tracking neurons across days in electrophysiology using Deep Neural Networks

bioRxiv Feb 2, 2026
To understand neural processes such as learning or memory, we need to track the activity of populations of neurons at the level of single spikes and across days. Here, we leverage deep neural networks to build DeepUnitMatch, a software that reliably ...
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Machine Learning Guided Optimization of an Oral Microemulsion System: A Bayesian Optimization Approach

bioRxiv Feb 2, 2026
Oral microemulsions are one drug delivery system often implemented to improve intestinal permeability and oral bioavailability of poorly-water soluble drugs. They also present several practical advantages including high patient compliance and simplif...
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DBSOMA: A Machine Learning Method that Identifies Chemical Modulators of Transcriptional States Uncovers Effectors of Beta-Cell Maturation

bioRxiv Feb 2, 2026
The effects of perturbation on a biological system can be readily measured in terms of transcriptional changes. However, despite a wealth of transcriptional perturbation response data, there are currently few methods to draw equivalence between the m...
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METEOR: joint genome-scale reconstruction and enzyme prediction

bioRxiv Feb 2, 2026
Motivation: Current machine learning methods for enzyme function prediction primarily treat proteins as independent entities, ignoring the metabolic context in which they operate. This reductionist approach often generates biologically implausible an...
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Transcriptomics-based modeling of methionine metabolism effectively estimates sample-wise DNA methylation activity and epigenetic aging

bioRxiv Feb 2, 2026
DNA methylation is a central epigenetic modification that regulates gene expression, maintains genomic stability, and guides cellular differentiation. However, direct measurements of DNA methylation, such as whole genome bisulfite sequencing or DNA m...
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Neural Networks as Entropic Systems: Applications in Digital Pathology

bioRxiv Feb 2, 2026
Deep learning systems in digital pathology are widely regarded as opaque, limiting clinical trust and interpretability. We present a framework for empirically characterizing training-time learning dynamics in neural networks by directly measuring act...
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BIG-TB: A benchmark for evaluating prediction and interpretability of sequence-based machine learning using *Mycobacterium tuberculosis* genomes

bioRxiv Feb 2, 2026
Foundation models aim to learn useful representations of biological sequences. However, the applicability of these representations for a wide range of tasks, including phenotype prediction and variant discovery, is still in question, in large part du...
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Physics-Informed Neural Network for Mapping Vascular and Tissue Dynamics Using Laser Speckle Contrast Imaging

bioRxiv Feb 2, 2026
Significance: Quantitatively mapping both cerebral blood flow and tissue dynamics from laser speckle contrast imaging (LSCI) is powerful for studying cerebral blood flow in general and neural-vascular coupling and stroke in particular. Conventional m...
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