Biophysics & Systems Biology · Life Sciences
Quantitative Methods
The newest papers in Quantitative Methods that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
140 papers, from 4 September 2026 to 5 November 2026: 140 arXiv preprints.
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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.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.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.Structured Population Models for Follicular Development
Ovarian follicle development has been modeled either by compartmental models, where developmental stages are represented by discrete compartments, or by physiologically structured population models…Discover, Falsify, Revise: Auditing Input-Use Claims from Source Code to Predictive Contribution in Agent-Discovered Cell Models
AI virtual cells aim to predict cellular responses to specified interventions, yet held-out predictive performance alone does not establish use of the supplied perturbation information.Pheno-GS: Phenoscape-scale Geodesic Sinkhorn
High-throughput single-cell data is now collected across large patient cohorts.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.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.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.Dynamic Generalized Gromov-Wasserstein Optimal Transport
Gromov--Wasserstein optimal transport (GW-OT) extends classical optimal transport by introducing structure-aware transport cost.Sharpness-Aware Minimization (SAM) Improves Classification Accuracy of Bacterial Raman Spectral Data Enabling Portable Diagnostics
Antimicrobial resistance is expected to claim 10 million lives per year by 2050, and resource-limited regions are most affected.Decoding Extrahepatic Targeting of Lipid Nanoparticles with Interpretable Machine Learning
Lipid nanoparticles (LNPs) have transformed RNA medicine, yet their clinical utility remains constrained by predominant hepatic accumulation after systemic administration.When AI Generates Covariates: Causal Typing and Estimand Drift in Sequential Experiments
AI-generated covariates from notes, conversations, images, and wearable streams can change the causal question when their roles are left unspecified.Information Set Emulation: Causal Certificates for AI Derived EHR Features
AI and large language models can recover clinically meaningful features from electronic health records (EHRs), but predictive usefulness does not establish admissibility for causal inference.