During photoheterotrophic growth on organic substrates, purple nonsulfur photosynthetic bacteria like Rhodospirillum rubrum can acquire…
Computer & Information Sciences
Predictive Modelling in Biology and Medicine
Over the last 10 years, it has been shown that multi-scale modeling approaches combined with machine learning provide a powerful method for developing robust predictive models for studying many biomedical processes and exploring massive data sets. Recently, the concept of digital twins has gained increasing attention in the biology, biomedicine, and healthcare communities. This collection explores the construction of digital twins and multiscale models as they relate to predictive biology and medicine.
Image Credit: An abstract image of a network of dots by BoliviaInteligente, Unsplash
PLOS Complex Systems
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PLOS Computational Biology Redox poise in R. rubrum phototrophic growth drives large-scale changes in macromolecular pathways
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PLOS Computational Biology Falsifying computational models of endothelial cell network formation through quantitative comparison with in vitro models
During angiogenesis, endothelial cells expand the vasculature by migrating from existing blood vessels, proliferating and collectively…
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PLOS Computational Biology Spatiotemporal orchestration of calcium-cAMP oscillations on AKAP/AC nanodomains is governed by an incoherent feedforward loop
The nanoscale organization of enzymes associated with the dynamics of second messengers is critical for ensuring compartmentation and…
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PLOS Computational Biology Optimal control of agent-based models via surrogate modeling
This paper describes and validates an algorithm to solve optimal control problems for agent-based models (ABMs). For a given ABM and a…
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PLOS Computational Biology A computational algorithm for optimal design of a bioartificial organ scaffold architecture
We develop a computational algorithm based on a diffuse interface approach to study the design of bioartificial organ scaffold…
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PLOS Computational Biology Protein drift-diffusion in membranes with non-equilibrium fluctuations arising from gradients in concentration or temperature
We investigate proteins within heterogeneous cell membranes where non-equilibrium phenomena arises from spatial variations in…
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Image creditNetwork, Internet, Technology by Pete Linforth, Pixabay LicensePLOS Computational Biology Predictive modeling in biology and medicine: Digital twins and multi-scale modeling
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PLOS Computational Biology Towards constructing a generalized structural 3D breathing human lung model based on experimental volumes, pressures, and strains
Respiratory diseases represent a significant healthcare burden, as evidenced by the devastating impact of COVID-19. Biophysical models…
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PLOS Computational Biology A mathematical model of plasmin-mediated fibrinolysis of single fibrin fibers
Fibrinolysis, the plasmin-mediated degradation of the fibrin mesh that stabilizes blood clots, is an important physiological process, and…
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PLOS Computational Biology Aggregating multiple test results to improve medical decision-making
Gathering observational data for medical decision-making often involves uncertainties arising from both type I (false positive) and type…
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PLOS Computational Biology Data-driven model discovery and model selection for noisy biological systems
Biological systems exhibit complex dynamics that differential equations can often adeptly represent. Ordinary differential equation models…
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PLOS Computational Biology A new look at TFPI inhibition of factor X activation
Blood coagulation is a vital physiological process involving a complex network of biochemical reactions, which converge to form a blood…
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PLOS Computational Biology Study of impacts of two types of cellular aging on the yeast bud morphogenesis
Understanding the mechanisms of the cellular aging processes is crucial for attempting to extend organismal lifespan and for studying…
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PLOS Computational Biology Competition between physical search and a weak-to-strong transition rate-limits kinesin binding times
The self-organization of cells relies on the profound complexity of protein-protein interactions. Challenges in directly observing these…
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PLOS Computational Biology Structural and practical identifiability of contrast transport models for DCE-MRI
Contrast transport models are widely used to quantify blood flow and transport in dynamic contrast-enhanced magnetic resonance imaging.…
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PLOS Complex Systems Long-range temporal correlation development in resting-state fMRI signal in preterm infants: Scanned shortly after birth and at term-equivalent age
While the newborn’s brain is functionally organised early on—with similar resting state networks as those of adults present at birth—these…
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PLOS Complex Systems Leveraging mathematical modeling framework to guide regimen strategy for phage therapy
Bacteriophage (phage) cocktail therapy has been relied upon more and more to treat antibiotic-resistant infections. Understanding of the…
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PLOS Complex Systems Determinants and facilitators of community coalition diffusion of prevention efforts
This study examines how individual characteristics and network features of coalition participation in an intervention predict coalition…
PLOS ONE
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PLOS ONE Brain MRI detection and classification: Harnessing convolutional neural networks and multi-level thresholding
Brain tumor detection in clinical applications is a complex and challenging task due to the intricate structures of the human brain.…
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PLOS ONE Brain-like illusion produced by Skye’s Oblique Grating in deep neural networks
The analogy between the brain and deep neural networks (DNNs) has sparked interest in neuroscience. Although DNNs have limitations, they…
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PLOS ONE The potential of the transformer-based survival analysis model, SurvTrace, for predicting recurrent cardiovascular events and stratifying high-risk patients with ischemic heart disease
Introduction: Ischemic heart disease is a leading cause of death worldwide, and its importance is increasing with the aging population. The…
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PLOS ONE Towards Digital Twin-Oriented Complex Networked Systems: Introducing heterogeneous node features and interaction rules
This study proposes an extendable modelling framework for Digital Twin-Oriented Complex Networked Systems (DT-CNSs) with a goal of…
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PLOS ONE An agent-based model of the spread of behavioural risk-factors for cardiovascular disease in city-scale populations
Cardiovascular disease (CVD) is the leading cause of mortality globally, and is the second main cause of mortality in the UK. Four key…
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PLOS ONE Multiclass classification of Autism Spectrum Disorder, attention deficit hyperactivity disorder, and typically developed individuals using fMRI functional connectivity analysis
Neurodevelopmental conditions, such as Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD), present unique…
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PLOS ONE Nonlinear modeling of oral glucose tolerance test response to evaluate associations with aging outcomes
As people age, their ability to maintain homeostasis in response to stressors diminishes. Physical frailty, a syndrome characterized by…
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PLOS ONE BACK-to-MOVE: Machine learning and computer vision model automating clinical classification of non-specific low back pain for personalised management
Background: Low back pain (LBP) is a major global disability contributor with profound health and socio-economic implications. The…
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PLOS ONE An agent-based nested model integrating within-host and between-host mechanisms to predict an epidemic
The COVID-19 pandemic has remarkably heightened concerns regarding the prediction of communicable disease spread. This study introduces an…
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PLOS ONE Design of health information management model for elderly care using an advanced higher-order hybrid clustering algorithm from the perspective of sports and medicine integration
In the context of integrating sports and medicine domains, the urgent resolution of elderly health supervision requires effective data…
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PLOS ONE Prediction of hospital readmission of multimorbid patients using machine learning models
Objective: The objective of this study is twofold. First, we seek to understand the characteristics of the multimorbid population that…
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PLOS ONE Exploring the interplay between colorectal cancer subtypes genomic variants and cellular morphology: A deep-learning approach
Molecular subtypes of colorectal cancer (CRC) significantly influence treatment decisions. While convolutional neural networks (CNNs) have…
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PLOS ONE Clinical and socioeconomic predictors of hospital use and emergency department visits among children with medical complexity: A machine learning approach using administrative data
Objectives: The primary objective of this study was to identify clinical and socioeconomic predictors of hospital and ED use among children…
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PLOS ONE Hypergraph modeling of complex interactions: Applications from human musculoskeletal structures to complex system dynamics
The musculoskeletal network is a complex system of different types of nodes and edges interacting with each other. Although there is a…