Clay weekly context brief for the Quantitative Biology category (ISO week 2026-W37). 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. An Integrative Computational Approach to Predict Viral Epitopes by Targeting the MHC-TCR Complexation Source: q-bio.BM (Biomolecules) Link: https://arxiv.org/abs/2609.03182 T-cell immunity acts as a major defense system against controlling viral infections in vertebrates. 2. 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. 3. The Identification of Biological Stains at Crime Scenes: A Promising Role for Proteomics and Machine Learning Source: q-bio.QM (Quantitative Methods) Link: https://arxiv.org/abs/2609.03521 Forensic body fluid identification is crucial for reconstructing crime scene events. 4. Scaling an Autoregressive Transformer for Single-Cell Generation Source: q-bio.GN (Genomics) Link: https://arxiv.org/abs/2608.02961 We study a self-supervised generation task for single-cell gene expression vectors: given a set of vectors from a cell type, we aim to generate additional gene expression vectors of that cell type. 5. 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. 6. Beyond species area curves: a theoretical approach to the relationship between diversity and area Source: q-bio.PE (Populations and Evolution) Link: https://arxiv.org/abs/2609.02365 Species area curves, which describe the number of species present as a function of area, have long been used to understand biodiversity and inform conservation efforts. 7. A large dataset of human EEG responses to short naturalistic videos for studying dynamic visual event processing Source: q-bio.NC (Neurons and Cognition) Link: https://arxiv.org/abs/2608.28768 Vision neuroscience has experienced a surge in the collection and use of large-scale datasets of brain responses to naturalistic images. 8. Systematic pathway comparison on the powerset of rule-based biochemical systems Source: q-bio.MN (Molecular Networks) Link: https://arxiv.org/abs/2608.23180 Computational pathway design often focuses on evaluating selected pathways or optimizing fluxes in a fixed network, but gives less direct access to the combinatorial question of which other enzyme subsets of the network can support productive alternative pathways. 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. Structural control over equilibrium silicon and oxygen isotopic fractionation: A first-principles density-functional theory study Source: q-bio.BM (Biomolecules) Link: https://arxiv.org/abs/2609.03486 Isotopic fractionation factors for oxygen and silicon in selected silicates (quartz, enstatite, forsterite, lizardite, kaolinite) have been calculated using first-principles methods. 11. 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. 12. Multiparametric MRI Radiomics and Machine Learning Framework for Predicting Treatment Response in Glioblastoma Source: q-bio.QM (Quantitative Methods) Link: https://arxiv.org/abs/2608.05733 Distinguishing True Progression (TP) from Pseudo-Progression (PsP) after chemoradiotherapy remains a major diagnostic challenge in GBM, as both entities present near-identical appearances on conventional contrast-enhanced post-treatment MRI. 13. EvoLen: Evolution-Guided Tokenization for DNA Language Model Source: q-bio.GN (Genomics) Link: https://arxiv.org/abs/2604.08698 Tokens serve as the basic units of representation in DNA language models (DNALMs), yet their design remains underexplored. 14. 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. 15. An adaptive time-tree transition kernel for Bayesian phylogenetic inference Source: q-bio.PE (Populations and Evolution) Link: https://arxiv.org/abs/2609.02445 Bayesian phylogenetic and phylodynamic analyses can be very time-consuming, owing to the combination of complex models that are used to estimate key parameters from increasingly large genomic data sets and their associated metadata. 16. Continual-learning rules shape representational drift Source: q-bio.NC (Neurons and Cognition) Link: https://arxiv.org/abs/2608.16141 Lifelong learning requires acquiring new knowledge without erasing the old. 17. Uncovering Cellular Resolution in scRNAseq via Unbiased Cell and Gene Network Analysis Source: q-bio.MN (Molecular Networks) Link: https://arxiv.org/abs/2608.22982 Conventional annotation of single-cell RNA-sequencing (scRNA-seq) data relies heavily on manual, marker-based thresholding, an approach that can obscure subtle transcriptomic gradients and collapse functionally distinct cell states into broad, heterogeneous populations. 18. Enhancer-promoter proximity predicts transcriptional competence but not transcriptional output in the Drosophila brain Source: q-bio.BM (Biomolecules) Link: https://arxiv.org/abs/2609.03058 How 3D genome architecture contributes to transcriptional specificity across neuronal cell types remains unclear. 19. 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. 20. SCALE:Scalable Conditional Atlas-Level Endpoint transport for virtual cell perturbation prediction Source: q-bio.QM (Quantitative Methods) Link: https://arxiv.org/abs/2603.17380 Virtual-cell models aim to predict how cell populations respond to perturbations, but control and treated cells are measured as unpaired populations, complicating the learning of perturbation-specific effects. 21. 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. 22. Estimating Time-Dependent COVID-19 Parameters Using Kolmogorov-Arnold Network and Physics-Informed Neural Network Source: q-bio.OT (Other Quantitative Biology) Link: https://arxiv.org/abs/2607.15302 We introduce a novel method for estimating COVID-19 time-varying parameters. 23. Fluctuating Environments Favor Extreme Reproductive Delays and Penalize Intermediate Ones Source: q-bio.PE (Populations and Evolution) Link: https://arxiv.org/abs/2512.05856 The timing of reproduction is crucial for biological fitness. 24. Backspace as a Natural Experiment: An Accelerated Failure Time Model of Selective Post-Error Motor Impairment in Parkinsons Disease Source: q-bio.NC (Neurons and Cognition) Link: https://arxiv.org/abs/2607.24796 Parkinson's disease (PD) selectively impairs distinct stages of motor control. 25. DigiPhen: a new paradigm for building predictive models of biological systems Source: q-bio.MN (Molecular Networks) Link: https://arxiv.org/abs/2608.22079 Reengineered biological systems have the potential to revolutionize chemical and material production, enhance critical mineral recovery, serve as threat sensors and improve human health. 26. SimpleDesign: A Joint Model for Protein Sequence and Structure Codesign Source: q-bio.BM (Biomolecules) Link: https://arxiv.org/abs/2609.03377 Proteins are fundamental to biological processes, with their function determined by the complex interplay between the amino acid sequence and the three-dimensional structure. 27. A quantitative model for the emergent population dynamics of the melanoma MITF rheostat Source: q-bio.CB (Cell Behavior) Link: https://arxiv.org/abs/2607.11820 Cancer progression is driven by the ability of cells with identical driver mutations to adopt biologically distinct adaptive phenotypes. 28. An Affordable Fiducial Marker Strategy for Reliable Autofocus in Long-Term Live Microscopy Source: q-bio.QM (Quantitative Methods) Link: https://arxiv.org/abs/2511.20890 Long-term time-lapse imaging of biological samples requires correcting for focal drift, which would otherwise gradually push the sample out of focus. 29. Storage-Centric System Designs for Enabling Fast, Efficient, and Low-Cost Genomic and Metagenomic Analyses Source: q-bio.GN (Genomics) Link: https://arxiv.org/abs/2608.31004 Genomic and metagenomic analyses play critical roles in many fields, such as precision medicine, urgent clinical settings, discovering early warnings of communicable diseases, ensuring food safety through pathogen monitoring, agriculture, and scientific discovery. 30. 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. 31. A mathematical model of HPAI transmission between dairy cattle and wild birds with environmental effects Source: q-bio.PE (Populations and Evolution) Link: https://arxiv.org/abs/2508.12201 Highly pathogenic avian influenza (HPAI), particularly H5N1, poses an increasing threat at the wildlife--livestock--environment interface, with recent detections in dairy cattle motivating multi-host transmission models. 32. Active Visual Semantics: A large-scale MEG and eye-tracking dataset for understanding visual intelligence in action Source: q-bio.NC (Neurons and Cognition) Link: https://arxiv.org/abs/2609.01055 Here we present the Active Visual Semantics (AVS) dataset, a large-scale collection of magnetoencephalography (MEG) and eye-tracking data recorded while five participants freely explored 4,080 natural scenes over 10 sessions each, yielding more than 200,000 fixation epochs in total. 33. Positive equilibria in mass action networks: geometry and bounds Source: q-bio.MN (Molecular Networks) Link: https://arxiv.org/abs/2409.06877 Any mass action network gives rise to a parameterised family of polynomial equations whose positive solutions are the positive equilibria of the network. 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.