AIMC Journal:
bioRxiv

Showing 901 to 910 of 4938 articles

Application of Machine Learning Tools for Waterbird Colony Monitoring Provides Gains in Precision and Temporal Efficiency

bioRxiv Jul 2, 2026
Waterbirds serve as important indicators of both aquatic and terrestrial ecosystem health, making effective monitoring essential for tracking population health and identifying potential causes of decline. Drones have provided opportunities to overcom...
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Shared Pain, Shared Decisions: How Empathy Shapes Social Conformity Through Physiology and Visual Attention

bioRxiv Jul 2, 2026
Empathy enables individuals to attune to others' experiences through shared affective, sensorimotor, and neural representations, but its influence on higher-level decision-making and social alignment remains unknown. We examined whether empathy promo...
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Frequent, context-dependent effects of human genetic variation on Cas9 activity revealed by population-scale GUIDE-seq-2 and deep combinatorial CHANCE-seq profiling

bioRxiv Jul 2, 2026
Genome editing enzymes can introduce targeted changes to the DNA in living cells, transforming biological research and enabling the first approved gene editing therapy for sickle cell disease. However, their genome-wide activity can be altered by gen...
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Knowledge-guided Bayesian optimization using pre-trained LLMs speeds up the identification of superior genotypes from germplasm collection

bioRxiv Jul 2, 2026
Background: Germplasm collections contain wide genetic diversity that is valuable for plant breeding, but conducting phenotypic evaluation for all genotypes in field trials is rarely feasible. Bayesian optimization offers a way to decide, season by s...
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EEG biomarkers of reinforcement learning and motivation: A multi-task battery

bioRxiv Jul 2, 2026
Serotonin and dopamine make dissociable contributions to reinforcement learning (RL) sub-components, yet we lack neural biomarkers capable of detecting their differential effects. Here, we report the development of a five-task EEG battery designed to...
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Models trained with noisy genomes extend bacterial phenotype prediction into deep time

bioRxiv Jul 2, 2026
Predicting phenotype from genotype in extant organisms is increasingly tractable through the accumulation of genome sequences and the development of machine-learning algorithms. Here we show that machine learning can be applied to reconstructed ances...
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Dynamic consensus pocket detection across molecular dynamics ensembles reveals persistent and transient druggable sites

bioRxiv Jul 2, 2026
The traditional 'one drug, one target' paradigm assumes that drugs interact with a single specific binding site. Modern pharmacology has proven this definition overly simplistic and, instead, recognizes that drugs operate within complex biological sy...
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Zero-Shot Metabolite Prediction from Gene Expression via Physics-Informed Graph Neural Networks

bioRxiv Jul 2, 2026
Predicting metabolite concentrations from gene expression is instrumental for linking regulatory programs to metabolic phenotypes. Prior approaches rely on static enzyme-metabolite mappings and often omit data-driven learning or biochemical constrain...
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WattmaMod enables high-resolution and extensible RNA modification profiling for nanopore direct RNA sequencing

bioRxiv Jul 2, 2026
Nanopore direct RNA sequencing enables direct profiling of RNA modifications on native transcripts, but accurate multi-modification detection remains limited by non-stationary signals and heterogeneity across chemistries. Here, we develop WattmaMod, ...
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ConfDock: Atom-specific Uncertainty Quantification for Molecular Docking via Conformal Prediction

bioRxiv Jul 1, 2026
Molecular docking is widely used in structure-based drug discovery, yet most approaches provide point estimates without rigorous uncertainty quantification. This limitation makes it difficult to assess when a predicted pose should be trusted, especia...
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