定量方法
Research done using model organisms has been fundamental to the biological understanding of human genes, diseases and phenotypes. Model organisms provide tractable systems for experiments to enhance understanding of biological mechanisms…
Antibiotics are a vital class of drugs closely associated with the prevention and treatment of bacterial infections. Accurate prediction of molecular antimicrobial activity remains a key challenge in the pursuit of novel antibiotic…
There are a number of errors in "mbtransfer: Microbiome intervention analysis using transfer functions and mirror statistics" PLOS Comp Bio (2024) spanning multiple aspects of the paper. The wrong inputs were provided to comparator methods…
Breast cancer cell lines are indispensable tools for unraveling disease mechanisms, enabling drug discovery, and developing personalized treatments, yet their heterogeneity and inconsistent classification pose significant challenges in…
This study compares the predictive capacity of the Dynamic Habitat Index (DHI) - a remote sensing (RS)-based measure of habitat productivity and variability - against traditional land-use/land-cover (LULC) metrics in species distribution…
Single-cell gene expression measurements encode variability spanning molecular noise, cell-to-cell heterogeneity, and technical artifacts. Mechanistic stochastic models provide powerful approaches to disentangle these sources, yet inferring…
Recent advances in spatial omics technologies have revolutionized our ability to study biological systems with unprecedented resolution. By preserving the spatial context of molecular measurements, these methods enable comprehensive mapping…
Digital pathology has emerged as a transformative approach to tissue analysis, offering unprecedented opportunities for objective, quantitative assessment of histopathological features. However, the complexity of implementing artificial…
The macroscopic (population-level) dynamics of chemotactic cell movement -- arising from underlying microscopic (individual-based) models -- are often described by parabolic partial differential equations (PDEs) governing the…
Moving animal groups consist of many distinct individuals but can operate and function as one unit when performing different tasks. Effectively evading unexpected predator attacks is one primary task for many moving groups. The current…
Complex patterns emerge across a wide range of biological systems. While such patterns often exhibit remarkable robustness, variation and irregularity exist at multiple scales and can carry important information about the underlying agent…
How DNA-binding proteins locate specific genomic targets remains a central challenge in molecular biology. Traditional protein-centric approaches, which rely on wet-lab experiments and visualization techniques, often lack genome-wide…
Large-scale single-cell and Perturb-seq investigations routinely involve clustering cells and subsequently annotating each cluster with Gene-Ontology (GO) terms to elucidate the underlying biological programs. However, both stages,…
Shelf seas are important for carbon sequestration and carbon cycle, but shelf sea observations for carbon pools are often sparse, or highly uncertain. Alternative can be provided by reanalyses, but these are often expensive to run. We…
Longitudinal medical images are essential for monitoring disease progression by capturing spatiotemporal changes associated with dynamic biological processes. While current methods have made progress in modeling spatiotemporal patterns,…
A scientific-study protocol, as defined here, is designed to deliver results from which inductive inference is allowed. In the nineteenth century, triplication was introduced into the plant sciences and Fisher's p<0.05 rule (1925) was…
The spatial organization of chromatin within the nucleus plays a crucial role in gene expression and genome function. However, the quantitative relationship between this organization and nuclear biochemical processes remains under debate.…
Quantitative proteomics plays a central role in uncovering regulatory mechanisms, identifying disease biomarkers, and guiding the development of precision therapies. These insights are often obtained through complex Bayesian models, whose…
Dynamical systems theory describes how interacting quantities change over time and space, from molecular oscillators to large-scale biological patterns. Such systems often involve nonlinear feedbacks, delays, and interactions across scales.…
Accurate epidemic forecasting is critical for effective public health interventions. This study compares Bayesian and Frequentist estimation frameworks within deterministic compartmental epidemic models, focusing on nonlinear least squares…