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Life Sciences
Life scientists post their preprints on bioRxiv, and quantitative biology appears on arXiv too. This page shows the newest papers ReadSearch has read from both, from cell biology and genetics to neuroscience, ecology and immunology.
709 papers, from 31 August 2026 to 6 November 2026: 426 arXiv preprints, 228 bioRxiv preprints and 55 OpenAlex records.
Newest papers, page 28
A General Harness for Protein Foundation Model Fitness Prediction
Accurate fitness prediction is central to protein engineering and understanding sequence-function relationships.Separating personal from population gains when calibrating EEG foundation models for new users
Foundation models are increasingly adapted to individual users, but an apparent personalization gain can simply reflect a stronger population model.On the Limits of Metacognitive Monitoring in LLMs
Reliable decisions depend on recognizing when an answer may be wrong.Continuous Variational Synthesis
Biological machine learning was long bottlenecked by the ability to synthesize designed DNA.DoAtlas-2: A Foundation for Self-Evolving Causal Biomedical Discovery
We introduce DoAtlas-2, a foundation for self-evolving causal biomedical discovery that organizes knowledge around causal mechanisms and advances through external evidence from human populations.Hybrid epidemic simulation framework coupling equation-based and individual-based models
Mass gathering events like concerts, sports matches, and festivals bring many people into close contact within a short period, creating localized bursts of infection that can shape epidemic outcomes…Uncertainty Quantification in Cardiac Model Personalisation from Ultrafast Ultrasound
Cardiac model personalisation requires inferring mechanical parameters that are not directly measurable in vivo.NeuronDiscover: Agent-in-Twin for Mechanistic Discovery in Neuronal Microenvironments with World Action Models
Mechanistic discovery in neuronal microenvironments requires interventions and measurements that separate competing explanations of solute transport and neuronal response.An integrated geometric quantification and shape analysis framework for axillary lymph node metastasis in breast cancer patients
Quantitative characterization of lymph node morphology is important for assessing axillary lymph node metastasis in breast cancer.NeuronSifter: Intervention Planning in CNS Microenvironments
Prioritizing central nervous system (CNS) interventions requires predicting how a dose, route, and schedule act on a partially observed microenvironment, then choosing the measurement that would…Mirror-Score: Calibrated, Inference-only Scoring Exposes the Limits of Sequence-compatibility Ranking in D-peptide Design
D-peptides combine protease resistance with high target specificity, but computational design of D-peptide binders remains immature.Better Behavioral Prediction, More Faithful Model Ablations? Evidence from Sequential Choice
Using predictive models to explain cognition requires more than accurate behavioral predictions.Explainability from Training with Applications to TCR-Epitope Prediction
Deep learning models have achieved strong performance in artificial intelligence for science, yet their black-box nature limits our understanding of how they learn scientific tasks.Cross-attention encoding models reveal dynamic spatiotemporal routing across human higher visual cortex
Understanding how the brain parses actions and events from time-varying natural inputs is a central challenge in neuroscience.Receptive-field-constrained stimulus optimization for human early and intermediate visual cortex
An ongoing challenge in sensory neuroscience is to characterize the feature dimensions encoded by cortical populations.Where Should Physics Enter a Molecular Crystal Generator?
Generative models make molecular crystal structure prediction fast, but their samples still exhibit geometric and packing violations.KoopCell: Koopman-Based Generative Model for Learning Single-Cell Dynamics from Distribution Snapshots
Learning population dynamics from temporally sparse, unpaired distribution snapshots is a fundamental challenge in developmental biology.Explainable Deep Learning of Resting-State Functional Connectomes Reveals Network Biomarkers of Adolescent Intelligence
Mapping resting-state brain organization to individual differences in cognitive ability remains a major challenge in population neuroinformatics.Robust Biomolecular Complex Design Across Protein Conformational Landscapes
Proteins populate conformational ensembles, yet structure-based biomolecular design typically optimizes candidates against a single target conformation.T-SNN: Temporal Simplicial Neural Network for EEG Decoding
Decoding brain states requires models that capture both the evolution of neural activity and interactions among groups of brain regions.
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