AIMC Journal:
bioRxiv

Showing 641 to 650 of 4938 articles

Multi-channel high-density single-molecule localization

bioRxiv Jul 26, 2026
Deep learning has enabled single-molecule localization microscopy (SMLM) at high emitter densities, but only for single channel systems. Here we present DECODE-Plex, a deep-learning-based framework to localize dense single molecules with overlapping ...
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Deep-learning predictions of biomolecular structures : persistent limitations and new horizons extended by explicit ion addition

bioRxiv Jul 26, 2026
The advent of deep learning-driven tools such as AlphaFold has revolutionized the prediction of biomolecular structures, offering unprecedented accuracy and accessibility for proteins, RNA, and their complexes. While these tools have demonstrated rem...
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Comparison of nuisance function construction strategies for double machine learning causal inference in single-cell transcriptomics: shared unsupervised deep learning does not require cross-fitting

bioRxiv Jul 26, 2026
Inferring "whether a change in the expression of a given gene causally affects the disease state" from observational single-cell transcriptomic data is one of the central problems in single-cell biology. The difficulty lies in confounding: cell state...
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EMG-BIDS: an extension to the Brain Imaging Data Structure for electromyography

bioRxiv Jul 26, 2026
Electromyography (EMG) is fundamental to clinical assessment, rehabilitation, neuromuscular research, and human-machine interfaces. Despite decades of use, no widely adopted standard exists for organizing and sharing EMG data, limiting reusability an...
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Benchmarking Neural Decoders for Brain-Computer Interfaces and Neural Population Analysis

bioRxiv Jul 26, 2026
The most accurate neural decoder on held-out trials is not necessarily the most useful for brain-computer interfaces or neural population analysis. In practical use, neural decoders may also need to remain robust to noisy neural inputs, satisfy calib...
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Cortical Sites Critical for Speech and Language Exhibit Distinct fMRI-Derived Network Features

bioRxiv Jul 26, 2026
Direct electrocortical stimulation (ECS) is a well-established brain mapping technique that helps achieve safe and effective resection of epileptic foci, tumors or vascular malformations. Recent studies using electrocorticography (ECoG) suggest that ...
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AI segmentation requires accounting for brain size to maintain performance on developmental MRI cohorts

bioRxiv Jul 25, 2026
The human brain undergoes rapid developmental changes through early life, underpinning the emergence of function but also marking a period of vulnerability to a range of neurodevelopmental disorders. With dynamic changes to brain size, morphology, an...
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Routine FFPE sections support clinically compatible single-nucleus transcriptomics across six human cancer types

bioRxiv Jul 24, 2026
Tumor cellular composition, including malignant cell states, immune populations, and stromal populations, is increasingly recognized as a determinant of therapeutic response and resistance to anti-cancer agents, yet comprehensive cellular profiling r...
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Functional covariance modes reveal aligned fetal and neonatal brain functional connectomes.

bioRxiv Jul 24, 2026
Spatially distributed functional networks are a fundamental property of brain organisation. While these networks are already present at full-term birth, establishing whether they exist before birth remains problematic, given the challenges inherent t...
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Leveraging Uncertainty Estimates for Drug Response Prediction in Cancer Cell Lines

bioRxiv Jul 24, 2026
Machine learning models for drug response prediction in cancer cell lines carry the potential to advance precision oncology by tailoring treatments to the molecular tumor profile. Their application is challenged by variability in prediction quality a...
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