AIMC Journal:
bioRxiv

Showing 2811 to 2820 of 4993 articles

Mechanistic modeling and machine learning identifies optimum radiotherapy schedules to prevent treatment-induced metastasis

bioRxiv Jan 1, 2025
Lung cancer patients often experience increased metastasis formation after radiotherapy. However, it is incompletely understood whether radiation affects the migratory behavior of tumor cells and how altered radiotherapy schedules might mitigate this...
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Atomic resolution ensembles of intrinsically disordered proteins with Alphafold

bioRxiv Jan 1, 2025
Intrinsically disordered proteins are ubiquitous in biological systems and play essential roles in a wide range of biological processes and diseases. Despite recent advances in high-resolution structural biology techniques and breakthroughs in deep l...
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GARN3: A coarse-grained helix centered technique for RNA 3D structures prediction

bioRxiv Jan 1, 2025
The study of the prediction of three-dimensional structures of RNA (ribonucleic acids) has been increasing over the last decades, especially with advances in artificial intelligence. However, there are still many gaps. Among the known techniques, GAR...
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Brainwide hemodynamics predict EEG neural rhythms across sleep and wakefulness in humans

bioRxiv Jan 1, 2025
The brain exhibits rich oscillatory dynamics that play critical roles in vigilance and cognition, such as the neural rhythms that define sleep. These rhythms continuously fluctuate, signaling major changes in vigilance, but the widespread brain dynam...
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Host Microenvironment Reprogramming by Saccharides Overcomes Lung Barriers for mRNA Therapeutics

bioRxiv Jan 1, 2025
Overcoming biological barriers remains the paramount challenge for pulmonary mRNA therapeutics. Conventional approaches focus exclusively on passively optimizing formulation quality without controlling dynamic host barriers. Here, we pioneer a host-c...
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SpatialMap: A Scalable Deep Learning Method for Cell Typing in Subcellular Spatial Transcriptomics

bioRxiv Jan 1, 2025
Subcellular imaging transcriptomics has offered unprecedented resolution of spatial mapping of gene expressions at subcellular level. However, accurate and robust cell type annotation at cellular level remains a challenge. Here we present SpatialMap,...
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Inferring metabolite states from spatial transcriptomes using multiple graph neural network

bioRxiv Jan 1, 2025
Metabolism serves as the pivotal interface connecting genotype and phenotype in various contexts, such as cancer reprogramming and immune metabolic reprogramming. Compared to the transcriptome, the development of the single-cell metabolome faces sign...
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A gradient of complementary learning systems emerges through meta-learning

bioRxiv Jan 1, 2025
Long-term learning and memory in the primate brain rely on a series of hierarchically organized subsystems extending from early sensory neocortical areas to the hippocampus. The components differ in their representational attributes and plasticity, w...
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A shotgun approach for highly multiplexed mammalian metabolic engineering

bioRxiv Jan 1, 2025
Mammalian metabolic engineering is critical to advancing basic biology, bioproduction, and cell therapy. However, as pathway complexity increases, so does the size of both the combinatorial design space and the DNA constructs required, rendering unbi...
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Fluctuation structure predicts genome-wide perturbation outcomes

bioRxiv Jan 1, 2025
Pooled single-cell perturbation screens represent powerful experimental platforms for functional genomics, yet interpreting these rich datasets for meaningful biological conclusions remains challenging. Most current methods fall at one of two extreme...
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