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bioRxiv

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Mapping trans-eQTLs at single-cell resolution using Latent Interaction Variational Inference.

bioRxiv Feb 6, 2026
Single-cell expression quantitative trait loci (eQTL) studies hold promise for linking genetic variants to changes in gene expression in individual cells, thereby offering deeper insights into the genetic basis of human traits and diseases. Existing ...
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Practical utility of sequence-to-omics models for improving the reproducibility of genetic fine-mapping

bioRxiv Feb 6, 2026
Recent advances in deep learning have led to the development of sequence-to-omics (S2O) models that predict molecular phenotypes directly from DNA sequences. Here, we systematically evaluate the utility of these models, e.g., AlphaGenome, Borzoi, Enf...
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ASPECT: Alternative Splicing Event Classification with Transformers

bioRxiv Feb 6, 2026
Motivation: Alternative splicing (AS) is a fundamental regulatory mechanism that expands transcriptomic and proteomic diversity by generating multiple mRNA isoforms from a single gene. Aberrant AS has been implicated in numerous diseases through the ...
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A lightweight, ultrafast and general embedding framework for large-scale spatial omics data

bioRxiv Feb 6, 2026
Deciphering ultra-large-scale omics data with minimal resources while maintaining high computational efficiency is a longstanding challenge in biology. Here, we present Local Pooling (LP), a lightweight, ultrafast and general framework that leverage ...
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Macro-Equi-Diff (MED): Scaffold-based Macrocycles Generation Using Equivariant Diffusion

bioRxiv Feb 6, 2026
Macrocyclic compounds are essential in drug discovery as they can modulate protein-protein interactions and enhance selectivity. Their structural complexity enables access to molecular diversity beyond traditional small molecules; however, designing ...
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Model Ensembling and Machine Learning Approaches to Predict the First Dose of Amoxicillin in Intensive Care

bioRxiv Feb 5, 2026
A priori model informed precision dosing (MIPD) recommends an appropriate first dose based solely on the covariates of the patient enabling faster target attainment without required concentration measurements. Population pharmacokinetic model ensembl...
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Automated Ventricle Assessment via Three-dimensional Anatomical Reconstruction (AVA-TAR): a computational toolkit for autonomous lateral ventricle assessment in preclinical hydrocephalus models

bioRxiv Feb 5, 2026
Introduction: Current workflows for studying hydrocephalus in rodent models rely on manual segmentation or qualitative assessment of ventricular size on small animal magnetic resonance imaging, which are both inefficient and prone to variability. Atl...
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Predicting Post-Stroke Aphasia Speech Performance from Multimodal Data with Explainable Machine Learning

bioRxiv Feb 5, 2026
Aphasia, an acquired language deficit, is the most common post-stroke focal cognitive impairment, and roughly 60% cases become chronic (duration >6 months). Aphasia therapies could be optimized if clinicians could make personalized predictions of how...
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A Shape Analysis Algorithm Quantifies Spatial Morphology and Context of 2D to 3D Cell Culture for Correlating Novel Phenotypes with Treatment Resistance

bioRxiv Feb 5, 2026
Numerous studies have shown that the morphological phenotype of a cell or organoid correlates with its susceptibility to anti-cancer agents. However, traditional methods of measuring phenotype rely on spatial metrics such as area, volume, perimeter, ...
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Intrinsic properties ensure reliable attractor dynamics in learned neural assemblies embedded within noisy, asynchronous networks

bioRxiv Feb 5, 2026
Neural representations rely on the ability of neuronal assemblies to display organized spiking patterns, despite being embedded within noisy networks. These structured patterns arise from attractor dynamics due to activity reverberation promoted by l...
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