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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 30
Pheno-GS: Phenoscape-scale Geodesic Sinkhorn
High-throughput single-cell data is now collected across large patient cohorts.AI-Driven Neural Surrogates for In Silico Design of Cognitive-Affective Neuromodulation Targets
In neuropsychiatry, the primary goal is often not only to decode brain activity but to change it, for example to lessen a negative affective bias or an overly salient memory.BaseCamp --- An Agentic AI Framework for Automating DNA Sequencing Data Pipelines
DNA sequencing pipelines, spanning quality control, alignment, variant calling, and annotation, are now reliably executed by workflow management systems that orchestrate established bioinformatics…SpaFactor: Lightweight Spatial Context-Aware Gene Program Modeling for Histology-to-Transcriptomics Inference
Spatial transcriptomics (ST) profiles gene expression within tissue architecture, but its cost and experimental complexity limit routine use.RootQuantV2: Adapting a Vision Foundation Model for Root-Trait Regression from Minirhizotron Imagery
A lack of high-throughput phenotyping solutions for root traits in field-grown crops has severely constrained understanding and improvement of below-ground traits and processes.Entropy-Driven Initiation and Cytoskeletal Viscoelasticity in Endocytosis: An Onsager Variational Framework
Receptor-mediated endocytosis requires a particle to approach the cell membrane to within a few nanometers before ligand--receptor binding can occur.The Computational Value of Sensory-Aligned Receptive Fields Depends on Neuronal Expressivity
Biological sensory neurons have selective receptive fields organized along meaningful stimulus coordinates, such as frequency, motion direction, or retinotopic position.Vision Transformers versus convolutional neural networks for fine-grained orchid genus identification in a species-rich, data-poor flora: a controlled benchmark on the Orchidaceae of New Guinea
New Guinea is the world's richest island flora (~2,856 orchid species), yet most species are represented by only a handful of photographs, far fewer than direct species-level classification requires.Adapting Boltz-2 with limited experimental activity data improves early enrichment in virtual screening
Virtual screening aims to prioritize active compounds from large chemical libraries within a limited experimental budget.QLoRA Fine-Tuning of Ministral LLM for Sequence-to-Function Protein Annotation
Functional annotation of newly sequenced proteins remains a bottleneck in molecular biology: the number of sequences in public repositories grows far faster than the capacity for manual curation.Experimental evidence of generalization in quantum machine learning in small-data regime
Quantum machine learning is a promising paradigm for learning from limited data, a central bottleneck in domains such as medical imaging, clinical trials, and rare diseases.Combinatorial Network-Based Manifold Topological Deep Learning for Image Analysis
Medical image analysis remains fundamentally challenging because of the intricate geometric and topological structures present in medical data.Towards Accurate Prediction of Mutation-Induced Changes in Protein Structure
Proteins can possess numerous mutations relative to their wild-type amino acid sequences with minimal impact to their structure and function.A discrete generative model of neuronal spiking activity on microelectrode arrays
Generative models of neural activity could help characterize tissue dynamics, compare experimental conditions, and simulate population activity for applications ranging from disease and…Matched-Input Estimates Differ in Sign Across Architectures: Auditing EEG Foundation Models on Motor Imagery
Pretrained EEG foundation models are increasingly proposed as general-purpose encoders for brain-computer interfaces, yet recent benchmarks disagree about when their representations transfer to…WILSON - a pathology foundation model framework for patient-level analysis and diagnostic text generation
Pathologists integrate morphology across magnifications and across the slides of a patient case, whereas pathology foundation models encode thousands of tiles from single slides and aggregate their…Reconstructed holograms and explanation-aware evaluation for low-cost computational pollen analysis in veterinary cytology
Automated pollen analysis supports veterinary cytology, but brightfield microscopy is costlier and more complex than lens-less digital in-line holographic microscopy.Reliability-Centered Evaluation of Sparse Longitudinal CT Lesion-Size Forecasting with Conformal Interval Calibration and Gompertz-Inspired Regularization
Sparse longitudinal CT follow-up limits lesion-size forecasting when only a few prior observations are available.Learning Cardiac Features: ECG Biometrics Across Time and~Exercise
Electrocardiograms (ECGs) carry subject-specific patterns enabling reliable individual discrimination, forming the basis of ECG biometrics.BrainWideBench: Benchmarking large-scale pretraining and across-animal transfer in multi-region neural recordings
Advances in large-scale neural recording have made it possible to collect data across many animals and distributed brain regions, raising the question of whether this scale can be exploited to learn…
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