bioRxiv

Showing 4251 to 4260 of 5016 articles

Network modularity reveals context and state-dependent reorganization of time-varying functional connectivity in single-cell resolved neural activity recordings

bioRxiv
An important goal of neuroscience is to understand how biological neural networks organize activity at multiple scales to enable complex information processing and behavioral output. To address this challenge, large-scale neural activity datasets wit...

Reinforcement learning for adaptive control of phenotypically heterogeneous bacterial populations

bioRxiv
Bacterial populations display extraordinary resilience to antibiotic stress, driven by diverse physiological states that allow some cells to persist and later repopulate. This phenotypic heterogeneity, amplified by environmental fluctuations, undermi...

Analyzing the Performance of Deep Learning Splice Prediction Algorithms

bioRxiv
SpliceAI has become the leading computational tool for predicting splice-altering variants, but restrictive licensing has limited its adoption by commercial clinical laboratories. While open-source reimplementations have emerged with author-reported ...

Genolator: A Multimodal Large Language Model Fusing Natural Language, Genomic, and Structural Tokens for Protein Function Interpretation

bioRxiv
Decoding the genetic code to unveil its genome functionality is a monumental task which would greatly advance the understanding of disease mechanisms and development of targeted treatment approaches. Although large language models (LLMs) have transfo...

Competition between memories for reactivation as a mechanism for long-delay credit assignment

bioRxiv
Animals can associate events with their outcomes, even if there is a long delay between the two. For example, in conditioned taste aversion, animals gain an aversion to a taste (the conditioned stimulus, CS) if sickness (an unconditioned stimulus, US...

Different learning algorithms achieve shared optimal outcomes in humans, rats, and mice

bioRxiv
Animals must exploit environmental regularities to make adaptive decisions, yet the learning algorithms that enabels this flexibility remain unclear. A central question across neuroscience, cognitive science, and machine learning, is whether learning...

XChrom: a cross-cell chromatin accessibility prediction model integrating genomic sequence and cellular context

bioRxiv
Single-cell chromatin accessibility offers unique insights into transcriptional regulation beyond gene expression. However, paired datasets of these two modalities remain relatively scarce, and existing computational models cannot simultaneously pred...

Assessing Scale and Predictive Diversity in Models for Single-Cell Transcriptomics based on Geneformer

bioRxiv
Foundation models are increasingly applied to single-cell transcriptomics, where they promise to capture generalizable representations that support diverse downstream analyzes. However, two central questions remain: Does scaling pre-training data rel...

RNAcentral in 2026: Genes and literature integration

bioRxiv
RNAcentral was founded in 2014 to serve as a comprehensive database of non-coding RNA sequences. It began by providing a single unified interface to more specialised resources, and now contains 45 million sequences. It has grown beyond providing a si...

MiRformer: a dual-transformer-encoder framework for predicting microRNA-mRNA interactions from paired sequences

bioRxiv
MicroRNAs (miRNAs) are small non-coding RNAs that regulate genes by binding to target messenger RNAs (mRNAs), causing them to degrade or suppressing their translation. Accurate prediction of miRNA–mRNA interactions is crucial for RNA therapeutics. Ex...