138 papers
By integrating high-content morphological profiling, phospho-protein arrays, and systems modeling, this study reveals that neuregulin-1 uniquely drives cardiomyocyte elongation and area expansion through distinct PI3K and p38 signaling pathways, offering new mechanistic insights for selectively targeting maladaptive cardiac remodeling.
This study demonstrates that integrating postmortem metabolomics with machine learning on real Swedish forensic cases enables accurate detection and subtyping of ketoacidosis-related deaths, achieving over 90% detection accuracy and over 80% subtyping accuracy.
This study proposes an interpretable, network-based framework that integrates gene co-expression analysis with multiple centrality measures to prioritize biologically meaningful candidate genes for Alzheimer's disease, overcoming the limitations of traditional differential expression methods by capturing system-level inter-gene relationships.
GRNFormer is a generalizable graph transformer framework that accurately infers gene regulatory networks from single-cell and bulk transcriptomics data across diverse species and cell types by integrating a transformer-based expression encoder with a variational graph autoencoder and transcription factor-anchored sampling, outperforming existing methods in benchmark evaluations.
This study demonstrates that standard linear machine learning models can reveal nuanced mRNA-protein coordination in cancer metastasis, showing that while both modalities often provide consistent phenotypic information, integrating their complementary and reinforcing signals yields superior predictive performance compared to using transcriptomics alone.
OrthoGather is a locally hosted web application designed to streamline comparative proteomic analysis and Gene Ontology enrichment across species by integrating orthology inference with flexible functional annotation, thereby lowering technical barriers for researchers without computational expertise.
This study utilizes large-scale multi-omics profiling of sedentary humans to characterize the distinct and shared temporal blood-based molecular responses to acute endurance and resistance exercise, revealing novel insights into systemic health pathways such as immune regulation, lipid metabolism, and tissue repair.
This study employs computational modeling and sensitivity analysis of caspase-mediated apoptosis signaling to identify key mechanistic targets for overcoming intrinsic drug resistance in castration-resistant prostate cancer when treated with Tocopheryloxybutyrate, Narciclasine, and Celecoxib.
This study systematically demonstrates that promoter binding-site strength is the primary modulator of gene expression levels, followed by transcription factor localization and concentration, while affinity variations are largely buffered, revealing key performance trade-offs between these trans-acting determinants.
This study reveals that while the overall T cell receptor repertoire is similar between sexes, females exhibit a specific thymic selection bias characterized by an increased prevalence of T cells targeting autoimmunity-associated self-antigens and a reduced frequency of regulatory T cells with such specificities, providing a mechanistic explanation for the higher susceptibility of women to autoimmune diseases.
This paper establishes that the phase-space distance between stationary states, rather than potential depth, serves as a robust geometric determinant of transition probabilities and timescales in breast cancer gene regulatory networks, thereby explaining the distinct dynamical robustness of HER2+ tumors versus the high heterogeneity and sensitivity of TNBC.
The paper introduces TRACER, a reference-free method that leverages gene-gene coherence and spatial co-localization to reconstruct biologically coherent cellular profiles from imaging-based spatial transcriptomics data, thereby resolving mixed profiles and recovering cells with undetected nuclei to improve downstream biological analyses.
This study utilizes multi-omic profiling to map the distinct, time-resolved molecular responses of abdominal subcutaneous adipose tissue to acute endurance and resistance exercise in sedentary adults, revealing specific mechanisms involving angiogenesis, metabolism, and exerkine release that underpin exercise-induced metabolic health benefits.
The paper introduces MAPLE, a framework utilizing structured validation schemas to facilitate collaboration between large language models and human modelers, thereby ensuring the accurate, provenance-rich, and reproducible extraction of calibration data for quantitative systems pharmacology models while mitigating common LLM errors like hallucination.
This study introduces a network-driven framework that aligns metal-binding sites as atomic point clouds to reveal conserved geometric motifs across sequence-divergent proteins, thereby elucidating evolutionary relationships and predicting drug off-targets based on structural similarity rather than sequence homology.
This study utilizes a network pharmacology framework combined with experimental validation to identify and confirm the therapeutic potential of repurposing the drugs TUDCA and arundine for Alzheimer's disease by rescuing disease-relevant phenotypes through the regulation of G protein signaling.
This study demonstrates that short-term, low-dose supplementation with either high-fructose corn syrup or Momordica charantia reduces pulmonary hypertension severity in broiler chickens, with high-fructose corn syrup showing superior efficacy, while validating the use of a system dynamics model to evaluate these nutritional interventions.
This paper demonstrates that the apparent dominance of additive and pairwise interactions in microbial communities is a generic consequence of structural and statistical detection limits—specifically exponential noise amplification and combinatorial geometric dilution—rather than evidence for intrinsically weak higher-order interactions.
The paper introduces the Toroidal Search Algorithm (TSA), a novel topology-inspired metaheuristic that eliminates boundary stagnation through toroidal geometry and winding numbers, demonstrating superior performance in high-dimensional optimization and successfully solving inverse parameterization problems in mathematical oncology.
By integrating multi-omic data from the dorsolateral prefrontal cortex, this study reconstructs a metabolic regulatory network in Alzheimer's disease that reveals a coordinated downregulation of energy-producing pathways driven by reduced enzyme abundance and inhibitory allosteric effects, alongside conflicting regulatory influences on glycolysis.