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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 23
Tensor-based Fusion of Multi-modal Data for Predicting Cancer Risk Levels
Cancer diagnosis and treatment increasingly rely on multi-modal diagnostic technologies that generate high-dimensional datasets.MORAD: Reinforcement Learning with Multi-Objective Rewards for RNA Inverse Design
We introduce MORAD, an online reinforcement learning framework for backbone-conditioned RNA diffusion models that trains a single shared policy across diverse target backbones.Designing Protein Structures from Natural Language
A central challenge in de novo protein design is generating proteins with desired structural and functional properties.DyssomniaNN: Multi-Scale Spiking Neural Modeling of Human Sleep Disorders and Perceived Restedness
Clinical sleep medicine repeatedly documents profound divergences between objective sleep duration and subjective daytime impairment, notably exemplified by sleep state misperception in paradoxical…Beyond Discrimination: Evaluating Probability Calibration in Radiomics-Image Fusion for Renal Cell Carcinoma Classification
Reliable probability estimates are important for the clinical interpretation of machine-learning classifiers, yet radiomics--image fusion models for renal cell carcinoma (RCC) are commonly evaluated…Predictive Multiplicity in Cell-Fate Assignment: Label-Free Rashomon Sets and the Limits of Per-Cell Certification
Single-cell trajectory inference maps transcriptomic measurements onto developmental continua, yet configurations that fit the data equally well can assign conflicting cell fates.Cross-species representation learning aligns mouse and human neural dynamics and tracks clinical drug efficacy
Preclinical models poorly predict human drug efficacy, particularly in neurological disorders.Beyond Action Entropy: Quotient-Space Exploration for Genome-Scale Metabolic Model Repair
Repairing scientific models from functional observations differs fundamentally from supervised prediction: feedback may certify a solution without revealing which structural correction is responsible.Elucidating the Space of Enzymatic Reaction: A Unified Benchmark and Pretrained Model
Existing reaction models primarily learn molecular transformations, whereas enzy- matic reactions depend jointly on molecular structure and catalytic function.Neural Decoding as Cognitive Inference
The brain maintains stable cognition despite continuously changing neural activity.La-Ribo: RNA Co-Design via Geometry-Latent Flow Matching
RNA function arises from the coupling of nucleotide sequence and three-dimensional structure, motivating their joint design.Unlocking the Regulatory Genome by ARGUS: An Evidence-Constrained Agentic Framework for Interpreting Single Nucleotide Variants
Over 90% of disease-associated variants from genome-wide association studies fall in noncoding regulatory regions, yet their functional interpretation remains a central open problem in genomic…Predictable Accuracy of Martini 3 Absolute Protein-Ligand Binding Free Energies across 15 Targets
Alchemical free-energy calculations predict protein-ligand binding affinities with close-to-experimental accuracy, but their cost restricts them to small sets of ligands.FaceKit: a Toolkit for Interpretable Facial Phenotyping, Synthetic Image Generation and Privacy Analysis in Rare Diseases
Many rare genetic diseases are associated with recognizable craniofacial features.MovieSTAGE: Scene, Transition, and Global Encoding for Movie-fMRI ADHD Classification
Naturalistic movie-fMRI provides a shared, temporally structured probe of brain dynamics, yet predictive models commonly rely on whole-run functional connectivity (FC) or temporally generic…Many Brains, One Geometry: A Shared Visual-Semantic Space for Cross-Dataset fMRI Decoding
Visual decoding from fMRI is typically siloed by participant and experiment, obscuring whether heterogeneous neural measurements can be organized within a common computational geometry.CircuitATLAS: Agentic reasoning over a systems neuroscience knowledge graph for target discovery in circuitopathies
Drug discovery for neurological disease has traditionally centered on the molecules altered by disease.Do Generative Priors Align with Human Naturalness Perception?
Visual generative models are trained to capture the probability distributions of natural images, yet whether their native priors reflect the regularities governing human perception of image…Structure alone supports efficient visual computation in the Drosophila visual system
Understanding the extent to which measured synaptic wiring determines computation remains a central challenge.Label-free cell counting and viability prediction with brightfield imaging and deep learning
Cell viability assessment is a core requirement in cell culture systems, with critical applications in biopharmaceutical manufacturing and drug development.
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