bioRxiv

Showing 4551 to 4560 of 5021 articles

Improving ADMET prediction with descriptor augmentation of Mol2Vec embeddings

bioRxiv Jan 1, 2025
The accurate prediction of ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) properties is crucial for early-stage drug development, enabling the reduction of late-stage attrition and guiding compound prioritization. In recent yea...
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CitriBEiTNet: A Hybrid CNN-Transformer Architecture Combining MobileNetV2 with BEiT’s Global Attention for Automated Citrus Leaf Disease Diagnosis

bioRxiv Jan 1, 2025
Citrus farming plays an essential role in agriculture; however, diseases like canker, greening, black spot, and melanose significantly reduce yield and fruit quality. Efficient classification of citrus leaf diseases is important for crop health maint...
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DPCMHC: efficient prediction of MHC-peptide binding affinity by deep learning based on dual-padding convolution

bioRxiv Jan 1, 2025
Predicting peptide binding affinities to major histocompatibility complex class I (MHCI) is a crucial challenge in immunological bioinformatics and is essential for identifying neoantigens in personalized cancer vaccines. Current deep learning method...
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Deep Learning-Based Drug Repurposing Using Knowledge Graph Embeddings and GraphRAG

bioRxiv Jan 1, 2025
Drug repurposing has become a crucial strategy to accelerate drug discovery and reduce development costs. Conventional drug development is time consuming and expensive; it often takes more than a decade and billions of dollars to bring a new drug int...
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Reinforcement learning enables single-cell foundation models to learn cellular differentiation

bioRxiv Jan 1, 2025
While single-cell foundation models excel at static representation learning and single-step perturbation prediction, their capacity to model and control dynamic, sequential cell state transitions remains underexplored. Here, we introduce Differentiat...
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Decoding Prokaryotic Whole Genomes with a Product-Contextualized Large Language Model

bioRxiv Jan 1, 2025
Genomes encode the instructions for life, yet their full interpretation requires models capable of capturing long-range context and functional meaning at scale. Existing genome language models (gLMs) are limited by short context windows, high computa...
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Trainable computation in molecular networks

bioRxiv Jan 1, 2025
Reports of learning in single cells without genetic change span decades yet remain controver-sial, in part because there is no accepted general molecular mechanism for training comparable to gradient-based training or Hebbian learning in neural circu...
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A transcription factor-responsive enhancer discovery platform for targeted immunotherapy

bioRxiv Jan 1, 2025
Synthetic enhancers with high specificity are crucial for therapeutic gene control. Although existing experimental screens and machine learning-based designs have advanced their discovery, these strategies remain context-restricted, typically requiri...
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Evolutionarily Conserved T-tubule-Mitochondria Contacts in Striated Muscle

bioRxiv Jan 1, 2025
The intricate architecture of skeletal muscle is essential for its contractile function, with the spatial organization of organelles such as T-tubules and mitochondria playing a crucial role in maintaining muscle performance and health1,2. T-tubules ...
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A subject-specific reversible folding model reveals geometry-driven white-matter organization

bioRxiv Jan 1, 2025
Tractography currently relies almost exclusively on diffusion data and seed maps, which alone remain insufficient for anatomically accurate fiber reconstruction. During brain development, white-matter fibers elongate alongside cortical folding, sugge...
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