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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.
608 papers, from 31 August 2026 to 5 November 2026: 425 arXiv preprints, 128 bioRxiv preprints and 55 OpenAlex records.
Newest papers, page 15
Representing short-term movement to reveal animal identity and learning progress
How learning progresses over time and varies across individuals is a longstanding question in cognitive and behavioral science.Cross-disorder Learning of Imaging-derived Joint Mophometric Markers in Alzheimer's and Parkinson's Diseases
As two most prevalent neurodegenerative diseases (NDDs), Alzheimer's disease (AD) and Parkinson's disease (PD) shared commonalities both in symptomology and pathophysiology.Magnolia: A Persistent-Memory Agent Framework for Computational Chemistry
Chemistry has recently entered a high-data regime as molecular databases from high-throughput platforms or computational studies have become available.EMBER: Predicting TCR--pMHC Binding Without a Docked Complex
We propose EMBER, a structure-based framework for TCR--pMHC binding prediction that eliminates the need for a predicted docked complex, and with it the placement error that dominates such predictions.QProtFuse: Query-Guided Layer Fusion for Retrieval-Augmented Protein Function Prediction
Predicting protein functions from amino acid sequences is essential to understanding biological processes.Label-Space Mismatch Distorts Cross-Cohort Evaluation in Breast Cancer Molecular Subtyping
Cross-cohort evaluation of breast cancer subtype classifiers is unreliable when source and target cohorts use different annotation standards: METABRIC labels six classes, PAM50 defines five, and a…Simulating Infant Senses with Age-Tuned Networks
What a newborn sees, hears and feels, and how this changes month by month, has been measured sense by sense, with different methods and in different units.CADS: Measuring the Incremental Contribution of LLM Proposers in Sequential Biological Screens
Large language models are increasingly used to guide sequential biological screens, yet standard evaluations rely on raw hit counts that conflate a proposer's value with the discovery capacity of…Aptamers as a sandbox for lab-in-the-loop agentic molecular discovery
Despite breakthroughs in AI-driven molecular generation, existing discovery pipelines operate largely in silico, with wet-lab feedback reserved for validation rather than iterative improvement.Multilingual Brain Decoding Reveals Shared Cortical Semantic Geometry
Human languages differ markedly in lexical and syntactic form yet can convey similar semantic content.MultiPASE: Shape-Aware Comparative 3D Genome Analysis
3D genome structures reconstructed from Hi-C data provide valuable insights into chromatin organization, but comparing them across conditions and time points remains challenging because of noise…What Shapes Brain Alignment of Large Language Models during Dialogue? Insights from Language Production and Comprehension
Brain alignment of large language models (LLMs) offers a way to investigate representational similarities between LLMs and the human brain during language processing.Multiscale Quantum-Classical Simulation of Protein Autoproteolysis in a Million-Atom Membrane Environment
Predicting chemical reactions in biomolecules is challenging because reactive centers are embedded within complex environments that strongly influence their energetics and mechanisms.Deep LLM layers expose passage-level context in EEG during silent reading
In a previous report we showed that a decoder can recover open-vocabulary word-level information from 19-channel EEG recorded during silent reading, by aligning short EEG windows with hidden-state…ProtoGTX: Prototype-Aligned Graph Transformer for Explainable Whole-Slide Image Analysis
Deep learning has achieved strong performance in computational pathology, but explaining whole-slide image (WSI) predictions remains challenging.LLM Evolution in a Simple Simulated Market
Arguments that AI systems will evolve in harmful ways are largely made in the abstract.GliomaINK: A Tumor and Anatomy Conditioned Flow Matching Framework for 3D MRI Sequence Synthesis in Glioma Patients
Incomplete multiparametric MR examinations limit glioma characterization and downstream AI tools.Reducing double-dipping in single-cell topic models with three-way count splitting
Topic models learn gene programs from single-cell RNA sequencing (scRNA-seq) data, and the same counts are then used to test which genes and donors are associated with those programs.Indirect Influences of Artificial Intelligence Advice on Complex Sepsis Treatment Decisions
Sepsis is a major public health concern, and many sepsis patients die due to ineffective hemodynamic management.OmicsBench: a long-horizon multi-turn benchmark of AI agents on research-study-scale bioinformatics
Computational biologists increasingly delegate substantial analyses to AI agents in long-horizon, multi-turn sessions, yet most benchmarks of agents' bioinformatics capabilities pose a single short…
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