Quantitative Biology
Meditation is quintessentially associated with a clear mind. This paper proposes that diverse findings in the science of meditation can be mapped onto a single, empirically tractable construct: functional signal-to-noise ratio in the brain,…
Spatial transcriptomics workflows increasingly combine large annotated data objects, notebook-based analyses, and resource-intensive statistical models that must be executed on high-performance computing (HPC) systems. In practice, these…
Current models of representational reliability in neural populations focus on temporal stability: whether population centroids are preserved across sessions and days. This framing leaves a fundamental question unanswered: how reliably does…
Precision oncology requires multifunctional platforms capable of integrating accurate tumor diagnosis, localized therapeutic delivery, immune modulation, and real-time monitoring of treatment response. Gelatin methacryloyl (GelMA) hydrogels…
Protein sequences carry a record of evolutionary history shaped by mutation, selection, drift, and epistasis. Recent generative models trained on homologous sequence families offer a new way to read this record: they define probabilistic…
Alzheimer's disease (AD) is characterized by the accumulation of Amyloid-$\beta$ ($A\beta$) plaques and hyperphosphorylated Tau proteins. However, many individuals exhibit substantial $A\beta$ and Tau pathology without developing dementia,…
Capsids are the protein shells that protect the genetic material of viruses. The precise structural description of capsids informs how viruses assemble and evolve and is key to the development of antiviral targets. Most viruses form…
While AI holds the potential to revolutionize space life sciences, realizing this promise is contingent upon the systematic restructuring of heterogeneous spaceflight biological data into machine-actionable, AI-ready forms. Even though open…
High-fidelity molecular docking simulations can produce biologically relevant estimates of epitope-receptor binding affinity but are computationally expensive and therefore limit the number of candidates that can be screened for vaccine…
This work examines perturbation generalization in spatial foundation-model embeddings derived from fluorescence microscopy images. Although these models can discriminate drug conditions accurately, it remains unclear whether the learned…
Background: Digital health technologies allow for frequent, remote gait monitoring in people with multiple sclerosis (MS). However, to differentiate daily variability from actual disease progression in longitudinal data, established minimal…
Background: Both between- and within-subject variations in circadian timing matter for health. If lifestyle changes could be used to regulate circadian timing, they would offer accessible and scalable routes to chronotherapy, but this link…
Evolutionary intermediates connect observed proteins, but the sequence of steps that produced them is rarely recoverable from extant data alone. Here we ask what can, and cannot, be inferred about such intermediates from the endpoints.…
Recent breakthroughs in synaptic-resolution network connectomics have revealed that brain circuits feature fine-scale structural connectivity, such as pairs of correlated synaptic couplings known as second-order motifs. Large-scale…
Ancestral sequence reconstruction (ASR) is a powerful approach for studying molecular evolution and the emergence of protein function. Yet most ASR methods assume that sites evolve independently, neglecting the epistatic constraints that…
Continuous attractor neural networks (CANNs) are the canonical computational framework for how the brain encodes continuous variables such as spatial position, head direction, and movement direction, and explain the activity of hippocampal…
Obesity is a global health crisis associated with metabolic disorders such as type 2 diabetes and cardiovascular disease. This study employed single-cell RNA sequencing to reconstruct the developmental trajectory of human adipocytes from…
In this work, we interpret developmental growth as a metabolic energy allocation problem and link the von Bertalanffy growth model to metabolic energy investments into the growth channel. Using a framework that specifies how metabolic…
Efficient evaluation of sequence data likelihoods and their high-dimensional gradients on phylogenetic trees improves inference under both maximum-likelihood and Bayesian frameworks. Here, we present BEAGLE 4.1, a high-performance library…
Stress is an adaptive response coordinated by neural and physiological systems. While acute stress can enhance survival, chronic stress drives structural brain changes, cognitive dysfunction, and increased psychiatric risk. At the cellular…