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bioRxiv

Showing 1271 to 1280 of 4956 articles

ATI_Box: A Simple tool for convolutional neural network-based image semantic segmentation

bioRxiv Jun 2, 2026
Quantitative analysis of microscopic images has become a standard in basic biological and biomedical research. Deep machine learning provided a powerful tool facilitating this process. However, practical adoption of deep machine learning to image ana...
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PepForge: Hierarchical HELM-Based Peptide Generation

bioRxiv Jun 2, 2026
Peptides carrying special connections such as macrocyclizations and various other structural modifications constitute a major class among peptide therapeutics, yet their chemical space remains largely inaccessible to computational generation methods....
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Category selectivity observed in the human brain is distinct from category selectivity observed in artificial neural networks

bioRxiv Jun 2, 2026
Category selectivity for images of faces, scenes, and bodies is among the most striking and reproducible findings in vision neuroscience. Artificial neural networks (ANNs) trained on visual tasks also develop category-selective units, which has led t...
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Bridging Ancestry Gaps in Genomic Risk Prediction with Tabular Foundation Models

bioRxiv Jun 2, 2026
Motivation: Models deployed for genomic prediction of diseases perform unevenly across populations, limiting clinical utility. Two factors drive this limitation: large imbalances in sample availability across ancestry groups and non-stationarity of g...
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Hierarchical refinements of cis-regulatory inputs improve scalable gene expression prediction

bioRxiv Jun 2, 2026
Deciphering the relationships between cis-regulatory elements (CREs) and target gene expression has long been a challenging problem in molecular biology. However, predicting gene expression from hundreds of candidate cis-regulatory elements (cCREs) r...
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Deciphering functional dark matter: Machine and deep learning-based processing of protein embeddings enables targeted function discoveries

bioRxiv Jun 2, 2026
The ever-expanding catalogue of uncharacterized proteins - the so called functional dark matter - poses a major challenge for biotechnological and biomedical exploitation. Functional assessment of most proteins is hindered by the technical limitation...
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SNV and indel error modeling of deep targeted cell-free DNA sequencing data for sensitive detection of circulating tumor DNA in colorectal cancer

bioRxiv Jun 2, 2026
Circulating tumor DNA (ctDNA) is a promising biomarker for cancer detection, but low tumor burden makes it difficult to distinguish true signal from background noise. To aggregate and better evaluate weak mutational signals, we propose PyDREAMS, whic...
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Combining transcriptomic resolutions and machine learning strategies uncovers new OXPHOS genes in Caenorhabditis elegans

bioRxiv Jun 2, 2026
Assigning functions to genes remains a major challenge in biology, as a large fraction of genes remain unannotated despite the availability of complete genomes. Oxidative phosphorylation (OXPHOS), the primary source of ATP in eukaryotes, exemplifies ...
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Real-time artificial intelligence prediction of peptide characteristics and MSFragger search improves multiplexed quantification of non-canonical HLA presented peptides in clear cell renal cell carcinoma.

bioRxiv Jun 2, 2026
Non-canonical HLA-presented peptides are promising therapeutic targets, but their low abundance makes them difficult to reproducibly identify and quantify, particularly in multiplexed immunopeptidomics workflows. Here we present MIRA-MS (Model-Inform...
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Equitable Health Intelligence: An Open Benchmark of Multi-Population Machine Learning for Omics-Based Cancer Prognosis

bioRxiv Jun 2, 2026
Purpose: Machine learning (ML) models for omics-based cancer prognosis are often trained on data from predominantly European-ancestry populations, producing biased predictions for other populations and undermining equitable genomic medicine. Existing...
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