AIMC Journal:
bioRxiv

Showing 2751 to 2760 of 4979 articles

Physics-Informed Neural Network Methods for Predicting Plant Height Development

bioRxiv Jan 14, 2026
Plant growth is a dynamic process affected by genes and growing environment, with all kinds of interactions between them. These complex relationships make the prediction of plant growth challenging. We propose a hybrid modelling framework that combin...
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Multimodal Benchmarking of Foundation Model Representations for Cellular Perturbation Response Prediction

bioRxiv Jan 1, 2025
The decreasing cost of single-cell RNA sequencing (scRNA-seq) has enabled the collection of massive scRNA-seq datasets, which are now being used to train transformer-based cell foundation models (FMs). One of the most promising applications of these ...
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Transformer-based Deep Learning for Glycan Structure Inference from Tandem Mass Spectrometry

bioRxiv Jan 1, 2025
Glycans play critical roles in diverse biological processes, but their structural analysis by tandem mass spectrometry (MS/MS) remains a major challenge due to their branched structure and stereochemistry. Traditional computational methods, such as d...
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Fully functional AAV viral vectors with highly altered structural cores and subunit interfaces using ProteinMPNN

bioRxiv Jan 1, 2025
Adeno-associated viruses (AAV) have emerged as a viable vector for gene therapy, with several clinical approvals and a growing pipeline in clinical trials. These vectors have several challenges that need to be addressed to widen their use, including ...
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Linking age changes in human cortical microcircuits to impaired brain function and EEG biomarkers

bioRxiv Jan 1, 2025
Human brain aging involves a variety of cellular and synaptic changes, but how these changes affect brain function and signals remains poorly understood due to experimental limitations in humans, meriting the use of detailed computational models. We ...
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DGAT: A Dual-Graph Attention Network for Inferring Spatial Protein Landscapes from Transcriptomics

bioRxiv Jan 1, 2025
Spatial transcriptomics (ST) technologies provide genome-wide mRNA profiles in tissue context but lack direct protein-level measurements, which are critical for interpreting cellular function and microenvironmental organization. We present DGAT (Dual...
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Self-supervised learning enables unbiased patient characterization from multiplexed cancer tissue microscopy images

bioRxiv Jan 1, 2025
Multiplexed immunofluorescence microscopy offers detailed insights into the spatial architecture of cancer tissue. However, classical single-cell analysis approaches are limited by segmentation accuracy, reliance on predefined features, and the inabi...
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Human whole epigenome modelling for clinical applications with Pleiades

bioRxiv Jan 1, 2025
Gene regulation in humans extends beyond the four letter genetic code. Cytosine methylation, in particular, functions as a critical epigenetic switchboard, dynamically programming cellular identity, adapting gene expression in response to environment...
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CLIMBS: assessing carbohydrate-protein interactions through a graph neural network classifier using synthetic negative data

bioRxiv Jan 1, 2025
Carbohydrate-protein interactions are essential for biological processes, such as cellular signaling and metabolism, and represent a large pool of untapped targets for diagnostics and therapeutics. However, current design and prediction methods fail ...
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MEM-GAN: A Pseudo Membrane Generator for Single-cell Imaging in Fluorescent Microscopy

bioRxiv Jan 1, 2025
Fluorescent microscopy imaging is vital to capturing single-cell spatial data, characterizing tissue organization and facilitating comprehensive analysis of cellular state. Advancements in fluorescent microscopy imaging technologies have enabled prec...
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