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.
Get the few papers worth your time in Quantitative Methods every morning.
Follow Quantitative Methods and ReadSearch reads its new papers each day, then brings you the few worth reading, each with its key finding in a sentence.
Newest papers, page 5
Linear Fitness Subspace in Protein Language Models Enables Sample-Efficient Directed Evolution
Model-guided directed evolution seeks to identify high-fitness protein variants under limited oracle budgets.Neural Petri flows for chemical reactions
Petri nets have been used to describe chemical processes such as reactions.They map well to chemistry: Places are the bonds between atoms and the free valence of each atom, a token is a unit of bond…APOD: reasoning-guided agentic population ordinary differential equation discovery for pharmacological digital twins
Establishing ordinary differential equations (ODEs) describing population data is a fundamental part of mathematical modeling in pharmacology, crucial to developing digital twins.LifeLong Digital Twin: A Unified Modeling Paradigm and Agent Harness for Event-Driven Lifelong Health State Trajectories
Human health is a continuous, dynamic trajectory shaped by the cumulative interplay of biological processes, clinical events, behaviors and environmental exposures across the life course.Multimodal reasoning for broadly neutralizing antibody discovery from label-free human B cell repertoires across virus families
Discovering broadly neutralizing antibodies (bnAbs) from human natural immune repertoires remains a fundamental challenge in immunology, hindered by: the extreme rarity of bnAb, incomplete…OncoNoteBERT: A Foundation Representation Model for Natural Language Processing of Real-World Outpatient Oncology Notes
Real-world outpatient oncology notes contain specialised terminology, tumour staging expressions, treatment names, toxicity descriptions, and institution-specific de-identification markers that may…MorphoBranch: A Fine-Structure-Preserving Workbench for Morphometric Analysis of Branched Cellular Structures
Background and Objectives: Fluorescence-labeled cellular arbors provide readouts of neuronal and microglial morphology, but fine and weakly labeled processes are prone to fragmentation and false…Can LLMs Reliably Annotate Bioassay Metadata to Improve Data Readiness?
The emergence of foundation models for molecular property prediction requires a high degree of AI data readiness, including reliable metadata annotation.Analysis of Quantized and Efficiently Adapted Protein Language Models
Protein language models (PLMs) are increasingly used for sequence generation and property prediction, but their size makes fine-tuning and deployment expensive.ORBIT-FMIB: Tracking Order-Resolved Epistatic Information Through ESM-2
Protein foundation models support mutation-effect and structural prediction, but predictive performance alone does not reveal which forms of biological interaction information remain accessible…Toward Controlling Biology with Language:Offline Learning of Prompt-Conditioned Interventions for Cells, Organoids, and Biobots
Artificial intelligence increasingly serves as a natural-language interface to complex technical systems, letting people accomplish sophisticated tasks by describing what they want rather than…Scalable Diffusion SBI for Compositional Inference under Simulator Misspecification
Simulation-based inference is challenging when many heterogeneous observations must be composed, hierarchical latent structure must be preserved, and the simulator is misspecified relative to…AssayRouter: Historical Utility Priors for Frozen Molecular Predictor Routing
Laboratories often face a new molecular assay with 16-64 labels and a bank of predictors whose training data and parameters are unavailable.Benchmarking graph-based models for in-silico toxicity prediction in drug discovery
Drug discovery is a costly and high-risk process, where toxicity-related failures remain a major cause of attrition in both preclinical and clinical stages.OmniVCBench: Benchmarking Evidence-Grounded Multimodal Reasoning Towards AI Virtual Cells
Artificial Intelligence Virtual Cells (AIVCs) are envisioned as scientific agents that simulate cellular responses, explain underlying mechanisms, and support hypothesis-driven discovery.RetroGEF: Dynamic Graph Edit Flow for Single-Step Retrosynthesis
Retrosynthesis enables the discovery of viable synthetic routes to target molecules.A General Harness for Protein Foundation Model Fitness Prediction
Accurate fitness prediction is central to protein engineering and understanding sequence-function relationships.DoAtlas-2: A Foundation for Self-Evolving Causal Biomedical Discovery
We introduce DoAtlas-2, a foundation for self-evolving causal biomedical discovery that organizes knowledge around causal mechanisms and advances through external evidence from human populations.Uncertainty Quantification in Cardiac Model Personalisation from Ultrafast Ultrasound
Cardiac model personalisation requires inferring mechanical parameters that are not directly measurable in vivo.An integrated geometric quantification and shape analysis framework for axillary lymph node metastasis in breast cancer patients
Quantitative characterization of lymph node morphology is important for assessing axillary lymph node metastasis in breast cancer.