Clay weekly context brief for the Quantitative Biology category (ISO week 2026-W40).

Clay tracks publications from the Quantitative Biology feed list. Below are recent items from this category, each with its source and a short description of what the publication covers when one is available in the source feed.

Recent publications:
1. Phylodynamic inference with the bounded coalescent: a point process perspective
   Source: q-bio.PE (Populations and Evolution)
   Link: https://arxiv.org/abs/2609.29035
   The coalescent is a central framework in population genetics for modelling the ancestral relationships among sampled individuals through a genealogy, represented as a rooted and ranked binary tree.
2. A Deep Neural Network for Predicting Continuous Human EEG Across the Auditory Pathway in Response to Sound
   Source: q-bio.NC (Neurons and Cognition)
   Link: https://arxiv.org/abs/2609.20595
   Computational models of auditory physiology commonly target specific responses or stages of the auditory pathway, limiting their ability to integrate findings across experimental paradigms and neural timescales.
3. BaseCamp --- An Agentic AI Framework for Automating DNA Sequencing Data Pipelines
   Source: q-bio.GN (Genomics)
   Link: https://arxiv.org/abs/2609.28557
   DNA sequencing pipelines, spanning quality control, alignment, variant calling, and annotation, are now reliably executed by workflow management systems that orchestrate established bioinformatics tools at scale.
4. PocketVE: Stable and Property-Guided Structure-Based Drug Design with Variance-Exploding Diffusion
   Source: q-bio.BM (Biomolecules)
   Link: https://arxiv.org/abs/2609.08101
   Protein-conditioned 3D molecule generation is a central challenge in structure-based drug design, requiring a balance between pocket compatibility, molecular properties, and physical geometry.
5. BixBench3: Benchmarking AI agents on research-study-scale computational biology tasks
   Source: q-bio.QM (Quantitative Methods)
   Link: https://arxiv.org/abs/2608.25286
   Artificial intelligence (AI) promises to accelerate biological research by automating computational analyses.
6. A flux-based approach for analyzing the disguised toric locus of reaction networks
   Source: q-bio.MN (Molecular Networks)
   Link: https://arxiv.org/abs/2510.03621
   Dynamical systems with polynomial right-hand sides are very important in various applications, e.g., in biochemistry and population dynamics.
7. EPI-KAN: A Method For Estimating and Forecasting Time-Dependent COVID-19 Parameters
   Source: q-bio.OT (Other Quantitative Biology)
   Link: https://arxiv.org/abs/2607.15302
   We introduce EPI-KAN, a novel method for estimating COVID-19 time-varying parameters.
8. Speed and stability of segregated waves in a pressure-based model of heterogeneous cell populations
   Source: q-bio.CB (Cell Behavior)
   Link: https://arxiv.org/abs/2609.09043
   We consider a minimal pressure-based model of heterogeneous cell populations consisting of proliferative and non-proliferative cells with different mobilities.
9. Continuum modeling of fluidic and elastic flow during growth-driven wound closure in partial-EMT cell monolayers
   Source: q-bio.TO (Tissues and Organs)
   Link: https://arxiv.org/abs/2607.05820
   Large-scale circular gap closure occurs over a time scale on which cell growth and proliferation become important.
10. Predator self limitation controls pattern formation in a predator prey system with additional food: a Turing Hopf analysis
   Source: q-bio.PE (Populations and Evolution)
   Link: https://arxiv.org/abs/2609.29052
   Supplying a released predator with additional, non reproducing food is a standard lever in augmentative biological control, with a known drawback with nothing limiting the predators own numbers, the extra food lets its population grow without bound.
11. Two base rates, two weights: base-rate neglect has a second axis
   Source: q-bio.NC (Neurons and Cognition)
   Link: https://arxiv.org/abs/2608.05658
   Base-rate neglect is usually treated as one mistake: giving the prior too little weight.
12. BreCol: Benchmarking Classical and Deep-Learning Methods for Microbiome-Based Cancer Detection
   Source: q-bio.GN (Genomics)
   Link: https://arxiv.org/abs/2609.27207
   DNA sequencing of the gut microbial community shows promise for cancer detection, but questions remain about the generalizability of results across studies.
13. ProteoEM: probabilistic protein abundance estimation from iterative affinity traces
   Source: q-bio.BM (Biomolecules)
   Link: https://arxiv.org/abs/2609.29155
   Single-molecule affinity mapping enables molecular-level measurement of proteins and proteoforms, but imperfect and nonspecific probe binding makes individual affinity traces compatible with multiple molecular identities.
14. Flow Matching for Count Data
   Source: q-bio.QM (Quantitative Methods)
   Link: https://arxiv.org/abs/2605.07746
   High-dimensional count data arise in applications such as single-cell RNA sequencing and neural spike trains, where mappings between distributions across successive batches or time points form critical components of data analysis.
15. Implementation of Linear Regression and Linear Interpolation using Reaction Networks
   Source: q-bio.MN (Molecular Networks)
   Link: https://arxiv.org/abs/2606.12573
   Statistical inference is a fundamental component of data science.
16. Aletheia: An Offline-First Clinical Decision Support System for Differential Diagnosis in Low-Resource Healthcare Settings
   Source: q-bio.OT (Other Quantitative Biology)
   Link: https://arxiv.org/abs/2607.24814
   Access to specialist clinical expertise remains severely limited across sub-Saharan Africa, where physician-to-patient ratios can fall below 1:25,000 in rural settings.
17. SpCAST enables scalable and interpretable integration of single-cell RNA sequencing and single-cell-resolved spatial transcriptomics
   Source: q-bio.CB (Cell Behavior)
   Link: https://arxiv.org/abs/2605.26904
   Single-cell-resolution spatial transcriptomics (scST) preserves tissue architecture but often provides targeted or sparse transcriptomic measurements, whereas scRNA-seq offers broader coverage without spatial context.
18. CharacteriSations of Planar Galled Network
   Source: q-bio.PE (Populations and Evolution)
   Link: https://arxiv.org/abs/2609.28597
   Rooted phylogenetic networks are widely used to represent the evolution of species that have undergone reticulate processes.
19. Persistent Memory Through Triple-Loop Consolidation Under Stochastic Unit Turnover
   Source: q-bio.NC (Neurons and Cognition)
   Link: https://arxiv.org/abs/2603.27188
   Dissipative cognitive architectures maintain computation through continuous energy expenditure, where units that exhaust their energy are stochastically replaced with fresh random state.
20. Large-scale spatial variable gene atlas for spatial transcriptomics
   Source: q-bio.GN (Genomics)
   Link: https://arxiv.org/abs/2510.07653
   Spatial variable genes (SVGs) reveal critical information about tissue architecture, cellular interactions, and disease microenvironments.
21. Task- and dataset-specific information in protein language models
   Source: q-bio.BM (Biomolecules)
   Link: https://arxiv.org/abs/2608.12090
   Protein language models (PLMs) have transferred the latest advances from natural language processing to computational biology.
22. Simulation-free Structure Learning for Stochastic Population Dynamics
   Source: q-bio.QM (Quantitative Methods)
   Link: https://arxiv.org/abs/2510.16656
   Modeling dynamical systems and unraveling their underlying structural dependencies is central to many domains in the natural sciences.
23. Thermodynamic Space of Chemical Reaction Networks
   Source: q-bio.MN (Molecular Networks)
   Link: https://arxiv.org/abs/2407.11498
   Living systems operate out of equilibrium, continuously consuming energy to sustain organised, functional states.
24. Conservative deterministic Markov models in mathematical biology: uniqueness of steady states, reversibility and computational methods
   Source: q-bio.OT (Other Quantitative Biology)
   Link: https://arxiv.org/abs/2608.27252
   Ordinary differential equations are commonly used throughout the sciences to build mechanistic models of time-dependent processes.
25. Antipolar Cell-cell Adhesion-causing Collective Motility Disorder
   Source: q-bio.CB (Cell Behavior)
   Link: https://arxiv.org/abs/2609.01946
   In this study, we aim to theoretically investigate antipolar cell-cell adhesion, in which adhesion sites are located on the opposite side of the leading edge of migrating cells, as a candidate for irregularly polarized adhesion that induces disorder in collective cell migration.
26. Consistent determination of stability regimes in natural ecological communities from abundance time series
   Source: q-bio.PE (Populations and Evolution)
   Link: https://arxiv.org/abs/2609.30154
   The stability of an ecological community is conventionally defined through species interactions, which quantify how species affect one another.
27. Three Failures of Pain Location: Why Its Diagnostic Utility Is Three Quantities, Not One
   Source: q-bio.NC (Neurons and Cognition)
   Link: https://arxiv.org/abs/2607.26297
   Patient-reported pain location is diagnostically decisive for some presentations and nearly uninformative for others.
28. Incorporating LLM Embeddings for Variation Across the Human Genome
   Source: q-bio.GN (Genomics)
   Link: https://arxiv.org/abs/2509.20702
   Recent advances in large language model (LLM) embeddings have enabled powerful representations for biological data, but most applications to date focus on gene-level information.
29. Sampling at intermediate temperatures is optimal for training large language models in protein structure prediction
   Source: q-bio.BM (Biomolecules)
   Link: https://arxiv.org/abs/2603.29529
   Using a statistical mechanics framework, we investigate the parameter space of transformer models trained on protein sequence data.
30. Machine Learning of Temperature-dependent Chemical Kinetics Using Parallel Droplet Microreactors
   Source: q-bio.QM (Quantitative Methods)
   Link: https://arxiv.org/abs/2512.19416
   Temperature is a fundamental regulator of chemical and biochemical kinetics, yet capturing nonlinear thermal effects directly from experimental data remains a major challenge due to limited throughput and model flexibility.
31. Are You Learning Biological Signal or Shortcuts? Auditing and Mitigating Bias in Protein-Protein Interaction Datasets
   Source: q-bio.MN (Molecular Networks)
   Link: https://arxiv.org/abs/2609.10193
   Protein-protein interaction (PPI) databases do not faithfully reflect biological realities.
32. COLD-CI: A large-scale very high-resolution label polygon dataset for cocoa and non-cocoa classification in Cote d'Ivoire
   Source: q-bio.OT (Other Quantitative Biology)
   Link: https://arxiv.org/abs/2606.20767
   Spatially explicit information on cocoa cultivation is essential for land-use planning, deforestation monitoring, environmental assessment, and supply-chain analysis.
33. Stochastic mutation as a mechanism for the emergence of SARS-CoV-2 new variants -- A Scientific Conjecture on Artificial Intelligence Paradigm
   Source: q-bio.CB (Cell Behavior)
   Link: https://arxiv.org/abs/2502.10471
   The article summaries authors' researches on spreading dynamics of COVID 19 by use of the method of continuously asking and answering questions.

Sources in this brief: q-bio.BM (Biomolecules); q-bio.CB (Cell Behavior); q-bio.GN (Genomics); q-bio.MN (Molecular Networks); q-bio.NC (Neurons and Cognition); q-bio.OT (Other Quantitative Biology); q-bio.PE (Populations and Evolution); q-bio.QM (Quantitative Methods); q-bio.TO (Tissues and Organs).
Selected 33 of 490 available items for this weekly brief.