bioRxiv

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Voxel-accurate MRI-microscopy correlation enables AI-powered prediction of brain disease states

bioRxiv Jan 1, 2025
Magnetic resonance imaging (MRI) is essential for visualizing the healthy and diseased brain, yet the cellular basis of MRI signal and how it changes over time remain poorly understood. Here, we present BRIDGE (Brain Radiological Imaging with Deep-le...
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Chemoarchitectural studies of the rat hypothalamus and zona incerta. Chemopleth 1.0 – A downloadable interactive Brain Maps spatial database of five co-visualizable neurochemical systems, with novel feature- and grid-based mapping tools

bioRxiv Jan 1, 2025
The hypothalamus and zona incerta of the brown rat (Rattus norvegicus), a model organism important for translational neuroscience research, contain diverse neuronal populations essential for survival, but how these populations are structurally organi...
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omicML: An Integrative Bioinformatics and Machine Learning Framework for Transcriptomic Biomarker Identification

bioRxiv Jan 1, 2025
Transcriptomic biomarker discovery has been a challenge due to variation in datasets and platforms, complexity in statistical and computational methods, integration of multiple programming languages, and intricacy of ML workflow to evaluate biomarker...
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Adaptive disorder as the hallmark of nanobodies antigen-binding loops

bioRxiv Jan 1, 2025
Nanobodies are antigen-binding proteins of great interest as diagnostics and therapeutics. Accurate and fast characterization of their complementarity-determining regions (CDRs) is crucial to uncover the principles guiding their design. Yet, this tas...
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Gut Microbiota Modulates and Predicts Disease Severity in Experimental Pemphigoid Disease

bioRxiv Jan 1, 2025
Pemphigoid diseases (PD) are autoimmune blistering diseases with reported alterations in skin and gut microbiota, though their causal contribution to disease pathophysiology remains unclear. Using a passive model of bullous pemphigoid-like epidermoly...
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mzLearn, a data-driven LC/MS signal detection algorithm, enables pre-trained generative models for enhanced patient stratification

bioRxiv Jan 1, 2025
Metabolite alterations are linked to diseases, yet large-scale untargeted metabolomics remains constrained by challenges in signal detection and integration of diverse datasets for developing pre-trained generative models. Here, we introduce mzLearn,...
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Brain-Informed Fine-Tuning for Improved Multilingual Understanding in Language Models

bioRxiv Jan 1, 2025
Recent studies have demonstrated that fine-tuning language models with brain data can improve their semantic understanding, although these findings have so far been limited to English. Interestingly, similar to the shared multilingual embedding space...
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Self-supervised learning enables robust microbiome predictions in data-limited and cross-cohort settings

bioRxiv Jan 1, 2025
The gut microbiome plays a crucial role in human health, but machine learning applications in this field face significant challenges, including limited labeled data availability, high dimensionality, and batch effects across different cohorts. To add...
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Scale-dependent brain age with cosmological higher-order statistics from structural magnetic resonance imaging

bioRxiv Jan 1, 2025
Inferring chronological age from magnetic resonance imaging (MRI) brain data has become a valuable tool for the early detection of neurodegenerative diseases. We present a method inspired by cosmological techniques for analyzing galaxy surveys, utili...
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FveOCRs - a database for open chromatin prediction in wild strawberry based on a large language model

bioRxiv Jan 1, 2025
Woodland strawberry (Fragaria vesca) is a widely used model system for cultivated strawberries and Rosaceae for molecular genetic studies. Nevertheless, available databases for its cis-regulatory element identification are limited. With the emergence...
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