npj Systems Biology and Applications

List of Papers (Total 606)

A rule-based simulation model illuminates the role of asymmetric mitochondrial fission on beta-cell health

Mitochondrial dynamics play a critical role in the development of aging-related diseases such as type 2 diabetes mellitus. To investigate how mitochondrial dynamics influence cellular behavior in pancreatic beta-cells, we developed a rule-based, multi-level simulation model of insulin secretion. The pancreatic beta-cell model encompasses metabolic pathways (glycolysis and...

Modeling epithelial deformation and cell rearrangement in response to external forces during Zebrafish epiboly

Morphogenesis in early development involves complex and extreme deformations in response to intra- and intercellular forces. Zebrafish epiboly, the spreading of the blastoderm to cover and engulf the large yolk cell, is a key early event that sets the stage for the establishment of the body plan, but the way the forces driving expansion are generated and mediated is poorly...

A double-staining automated flow cytometry method for real-time monitoring of bacteria in continuous bioreactors

In biotechnological processes, cell density and physiology are critical parameters for controlling the feed rate, harvest time, and process performance. We developed an automated flow cytometry approach that enables continuous, real-time (fully automated, hourly) monitoring of bacterial populations in continuous bioreactors. The method employed a double-staining protocol that...

Signed, sealed, delivered: a generalizable model for living biotherapeutic dosing and metabolism

Living Biotherapeutic Products (LBPs) offer a promising therapeutic strategy for metabolic disorders rooted in gut microbiome dysfunction, yet quantitative frameworks for predicting their efficacy remain underdeveloped. We introduce the Bacterial Compartment Absorption and Transit (BCAT) model, a pharmacokinetic-pharmacodynamic framework that couples probiotic transit, endogenous...

Overcoming vascular niche–mediated TKI resistance in acute myeloid leukemia through miR-126 inhibition

Acute myeloid leukemia (AML) is a hematologic malignancy originating in the bone marrow and often progressing to extramedullary sites. Despite advances in molecularly targeted therapies and hematopoietic stem cell transplantation, clinical outcomes remain poor. Tyrosine kinase inhibitors (TKIs) provide benefit to a subset of AML patients harboring FLT3-ITD mutations; however...

Optimal control theory as a method for designing multidrug adaptive therapy regimens

Evolutionarily informed regimens offer new approaches that hope to combat the development of resistance during cancer treatment. These regimens are often complicated to design. In this work, we use optimal control theory (OCT) to guide the design of a two-drug adaptive therapy regimen. We begin with a logistic differential equation model of a tumor composed of four populations...

Simulation-based inference of cell migration dynamics in complex spatial environments

To assess cell migration in complex spatial environments, microfabricated chips, such as mazes and pillar forests, are routinely used to impose spatial and mechanical constraints, and cell trajectories are followed within these structures by advanced imaging techniques. In systems mechanobiology, computational models serve as essential tools to uncover how physical geometry...

Dynamical network analysis reveals long-range residue couplings at the pMHC interface underlying enhanced immunogenicity

The interaction between a class I peptide-major histocompatibility complex (pMHC) and a T cell receptor (TCR) plays a central role in the elicitation of CD8+ T cell immune responses. As a result, considerable effort has been invested in understanding the structural, dynamic, and biophysical parameters that govern this recognition event, including designing altered peptide ligands...

The future of mathematical oncology in the age of AI

This perspective article discusses emerging advances at the interface of mechanistic modeling and data-driven machine learning, highlighting opportunities for AI to accelerate discovery, improve predictive modeling, and enhance clinical decision-making. We address critical limitations of current AI approaches and propose a perspective on a future where AI augments mechanistic...

Machine learning prediction for AML based on 3D genome selected circRNA

Acute myeloid leukemia (AML) is a clinically aggressive hematologic malignancy driven by complex genetic and epigenetic aberrations. Circular RNAs (circRNAs), characterized by covalently closed structures and exceptional stability, have emerged as promising diagnostic biomarkers. However, existing circRNA-based predictive models largely depend on differential expression...

Gene regulatory network transitions reveal the central transcription factors in lung adenocarcinoma progression

Transcription factors play a central role in cancer growth, progression, and metastasis, and contribute to intratumor phenotypic plasticity that enable drug tolerance and cancer relapse. Changes in the regulatory activities of transcription factors in cancer may not always be detected from mutational signatures or differential expression of the transcription factors, as done in...

Asthma-mediated control of optic glioma growth via T cell-microglia interactions: A mathematical model

Optic glioma, a slow-growing tumor, is associated with Neurofibromatosis type 1 (NF1) mutations and increased midkine (MDK) production. A connection between asthma and optic glioma has previously been observed, but the mechanisms are unclear. To elucidate the role of asthma in the regulation of glioma formation, we investigated the role of T cells and the subsequent pathways in...

Data driven network inference and longitudinal transcriptomics unveil dynamic regulation in Chronic Lymphocytic Leukaemia models

How do cancer cells respond to their environment, and what are the key regulators behind their behaviour? While immune cell reprogramming in the tumour microenvironment (TME) has been extensively studied, the dynamic regulatory changes within cancer cells in response to interactions with immune cells remain poorly understood. In Chronic Lymphocytic Leukaemia (CLL), this knowledge...

Mechanisms of rectified gap junctional coupling enhancing pacemaking activity of biologically engineered pacemaker cells

Bio-pacemakers offer a potential alternative to electronic devices, yet their stable implementation at cellular and tissue levels remains unresolved. In this computational study, we aimed to investigate possible effects of the electrotonic interaction between cardiac cells and the spatial distribution of the bio-pacemaker on the initiation and conduction of cardiac pacemaking...

Cross-platform metabolomics imputation using importance-weighted autoencoders

Metabolomics data are often generated through different platforms and quantification methods which makes their synthesis and large-scale replication challenging. This study developed an ensemble of importance-weighted autoencoders to perform cross-platform metabolomics imputation between two metabolomics platforms, Metabolon and National Phenome Centre (NPC) at Imperial College...

Delaying cancer progression by integrating toxicity constraints in a model of adaptive therapy

Cancer therapies often fail when intolerable toxicity or drug-resistant cancer cells undermine otherwise effective treatment strategies. Over the past decade, adaptive therapy has emerged as a promising approach to postpone emergence of resistance by altering dose timing based on tumor burden thresholds. Despite encouraging results, these protocols often overlook the crucial role...

Quantifying and comparing causal patterns in stochastic chemical reaction networks

Chemical reaction networks (CRNs) are broadly used to study biological systems via simulations. Gillespie’s Stochastic Simulation Algorithm (SSA) is commonly used to perform stochastic simulations with CRNs. Comparing two CRNs in such a setting relies on ad hoc signals obtained from the time series, which the simulations output by discarding causal patterns. To this end, we...

Computational approaches in chemical space exploration for carbon fixation pathways

Chemical space exploration is an important part of chemistry and biology, enabling the discovery and optimization of metabolic pathways, advancing synthetic metabolic functions, and understanding biochemical network evolution. We use a graph-based computational approach implemented in the cheminformatics software MØD, integrated with Integer Linear Programming (ILP) optimization...

Mathematical modeling of combinatorial antigen targeting with multiple CAR T-cell products for glioblastoma treatment

Glioblastoma is a highly aggressive and difficult-to-treat brain cancer that resists conventional therapies. Recent advances in chimeric antigen receptor (CAR) T-cell therapy have shown promising potential for treating glioblastoma; however, achieving optimal efficacy remains challenging due to tumor antigen heterogeneity, the tumor microenvironment, and T-cell exhaustion. In...

Rethinking medical education through systems biology to address complexity

While reductionism has advanced biology and medicine, it fosters a fragmented understanding of health, ill-suited to modern challenges like chronic and systemic diseases. Systems biology offers a new perspective, framing biological entities within interconnected networks. Using French medical education as an example, we argue that systems thinking should be foundational, not...

Bistability in type I toxin-antitoxin systems may lead to stress-induced persister formation

Antibiotic persistence, characterized by a dormant subpopulation of bacterial cells that causes chronic and recurrent infections, remains poorly understood despite being recognized nearly a century ago. Toxin–antitoxin (TA) systems, which include a toxin and an antitoxin, are promising candidates for elucidating persister formation. We present the first theoretical model of...