bioRxiv

Showing 3431 to 3440 of 5001 articles

RawBench: A Comprehensive Benchmarking Framework for Raw Nanopore Signal Analysis Techniques

bioRxiv
Nanopore sequencing technologies continue to advance rapidly, offering critical benefits such as real-time analysis, the ability to sequence extremely long DNA fragments (up to millions of bases in a single read), and the option to selectively stop s...

Bioimage analysis for multiplexed FUCCI acquisitions powered by deep learning

bioRxiv
The FUCCI sensor fluorescently labels cell cycle phases, which is essential to assess normal and abnormal cell-cycle progression in physiological and pathological conditions of developing organisms. However, accurate cell-cycle decoding is challengin...

The persistence and loss of hard selective sweeps amid ancient human admixture

bioRxiv
The extent to which human adaptations have persisted throughout history despite strong eroding demographic events such as admixture, genetic drift, and fluctuations in selection pressures remains unknown. Understanding which loci are particularly res...

A Hybrid Knowledge- and Data-driven Model for Automatic Assessment of Chemically Induced Spiking Patterns in C-fiber Microneurography

bioRxiv
Analyzing temporal spike patterns in nociceptors recorded via microneurography is challenging due to the use of a single recording electrode, waveform variability, and high similarity of spike shapes across neurons limiting interpretation of sensory ...

Pathogen and pest communities in agroecosystems across climate gradients: Anticipating future challenges in the highland tropics

bioRxiv
Tropical cropping systems must adapt to the current and future geographic distribution of pathogen and pest communities. An important research gap is how climate change may shift the distribution of pathogens and pests in tropical lowlands and highla...

Multiple instance learning with spatial transcriptomics for interpretable patient-level predictions: application in glioblastoma

bioRxiv
Accurate prediction of patient outcomes remains a major challenge in oncology. While recent machine learning (ML) approaches often rely on bulk omics lacking spatial resolution or histology-based multiple instance learning (MIL), spatial transcriptom...

From microbial diversity to function; evaluating dimensionality reduction methods

bioRxiv
Artificial Intelligence (AI), and more specifically Machine Learning (ML), have become an increasingly prevalent tool in microbial oceanography. The high dimensionality of microbial diversity data from ‘omics observations is highly suitable for ML an...

Cooperative multi-view integration with Scalable and Interpretable Model Explainer

bioRxiv
Single-omics approaches often provide a limited perspective on complex biological systems, whereas multi-omics integration enables a more comprehensive understanding by combining diverse data views. However, integrating heterogeneous data types and i...

Cross-Species Insights from ART-D to Uncover Evolutionarily Conserved Oncogenic Mechanisms

bioRxiv
Cancer arises from oncogenic clones, yet the dynamic mechanisms governing their stepwise evolution toward malignancy remain incompletely understood. Here, we establish the Atlas of Ras-driven Tumors in Drosophila (ART-D), a systematic, cross-species ...

Context-Dependent Protein Structure Prediction Analysis and Stoichiometry Inference with MultimerMapper

bioRxiv
Advances in artificial intelligence (AI) have transformed the field of protein structure, notably with the accuracy level reached by AlphaFold in the prediction of monomeric and multimeric protein structures. However, while cloud implementations have...