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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 34
MedGSSR: Generalizable Medical Image Super-Resolution 3D Reconstruction via Hierarchical Feed-forward Gaussian Splatting
High-resolution volumetric medical imaging is critical for clinical diagnosis, yet acquisition is often limited by scanner hardware, scan time, and for CT, radiation dose.A Comprehensive Review of Multimodal Facial State Analysis: Tasks, Methods, and Resources
Facial state analysis plays a crucial role in understanding human expressions, psychological modeling, and human computer interaction.Agentic BAIM-LLM Evaluation (ABLE): Benchmarking LLM Use of Protein Design Tools
We introduce ABLE, a benchmark for evaluating LLM agents' ability to use biological AI models (BAIMs), such as ProteinMPNN and AlphaFold3, in dual-use protein design workflows.A Generalizable Feature Extractor for Alzheimer's-Related Brain MRI Tasks
When there is not enough labeled data to properly train deep learning models, transfer learning can help.A Roadmap for MEG Foundation Models
Foundation models are beginning to reshape brain-signal analysis by moving the field beyond task-specific decoding pipelines toward reusable models pretrained on broad neural datasets.Spread of Chronic Wasting Disease under Stochastic Environmental Conditions and its Control using Deep Reinforcement Learning
Chronic wasting disease (CWD) is a fatal prion disease affecting deer, elk, moose, reindeer, muntjac, and other cervids.The 2024 MRSI Data Processing and Quantification Challenge Synthetic Dataset
Synthetic data is central to magnetic resonance spectroscopy method development because they provide ground truths for software validation, reproducible benchmarking, and machine- and deep-learning…Mutation--selection balance on an infinite trait space: confinement, drift and equilibrium
We study a trait-structured population model incorporating mutation, selection and density-dependent regulation on a countably infinite trait space.On the interpretation of the kinetics of ligand-receptor binding
When the rates of ligand binding are measured by methods such as surface plasmon resonance, it is common practice to use the observed rate constants for the onset and offset of binding to estimate…FLaG: Frequency-Domain Latent-attention Gated Pooling for Token Aggregation
Token aggregation converts token-level representations into fixed-dimensional sample representations, but most pooling methods operate only in the original token space.Pole-Zero Geometry, Model Reduction, and Identifiability in Sensory Adaptation
Sensory adaptation provides a concrete setting in which low-order system identification can fail qualitatively.Cross-Modal Guidance for Out-of-View Object Search in Simulated Prosthetic Vision
Out-of-view guidance is well established in virtual and augmented reality, but its effectiveness may depend on the visual bandwidth available to the user.A distributed-delay Wilson-Cowan model of sleep-related rhythms in the corticothalamic system
The corticothalamic circuit supports rhythms with timescales that differ by orders of magnitude: sleep spindles, the sigma-band events of non-rapid-eye-movement (NREM) sleep, and infra-slow…An Intelligent Decision Support System for Emotion Monitoring using Microscopic Fixational Dynamics
The rising prevalence of psychological disorders necessitates effective emotion monitoring, yet current methods relying on facial or physiological signals often suffer from intrusiveness and privacy…Temporally constraining source imaging estimates in an underdetermined neural system with eigenmodes of cortical geometry
Geometric eigenmodes provide a compact and biologically grounded representation of large-scale neural activity.SymFold: Synergizing Evolutionary and Structural Priors for Accurate Protein Inverse Folding
Protein inverse folding aims to recover amino acid sequences for a given 3D protein structure, underpinning broad applications such as enzyme engineering and drug discovery.Current methods often…PopPert: Population-level Joint-Distribution Modeling for Single-Cell Perturbation Prediction
Predicting transcriptional responses to specific perturbations is critical for understanding cellular regulatory mechanisms and accelerating drug discovery.In-Context Neurofeedback: Can LLMs Control Their Internal Representations through Privileged Access?
Whether large language models (LLMs) can control their own internal representations matters for both machine metacognition and AI safety.EEG-AS: Instance-Level Foundation Model Selection for EEG Foundation Models via Behavior Reconstruction
Electroencephalography (EEG) is a non-invasive technique for measuring neural activity and has been widely used in neuroscience applications.TWIX: a Two-Stage Approach for End-To-End Named Entity Recognition and Relation Extraction
The exponential growth of scientific publications calls for automatic Information Extraction (IE) systems to support knowledge discovery.
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