Graphical Modeling Meets Systems Pharmacology

Lombardo, Rosario; Priami, Corrado

doi:10.1177/1177625017691937

Cited by 4 publications

(7 citation statements)

References 32 publications

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“…The comparison of the results and a graphical representation of the model, designed with the executable Visual QSP modeling platform bStyle 21 , are illustrated in Fig. 3 .…”

Section: Resultsmentioning

confidence: 99%

QSPcc reduces bottlenecks in computational model simulations

et al. 2021

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Mathematical models have grown in size and complexity becoming often computationally intractable. In sensitivity analysis and optimization phases, critical for tuning, validation and qualification, these models may be run thousands of times. Scientific programming languages popular for prototyping, such as MATLAB and R, can be a bottleneck in terms of performance. Here we show a compiler-based approach, designed to be universal at handling engineering and life sciences modeling styles, that automatically translates models into fast C code. At first QSPcc is demonstrated to be crucial in enabling the research on otherwise intractable Quantitative Systems Pharmacology models, such as in rare Lysosomal Storage Disorders. To demonstrate the full value in seamlessly accelerating, or enabling, the R&D efforts in natural sciences, we then benchmark QSPcc against 8 solutions on 24 real-world projects from different scientific fields. With speed-ups of 22000x peak, and 1605x arithmetic mean, our results show consistent superior performances.

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“…The comparison of the results and a graphical representation of the model, designed with the executable Visual QSP modeling platform bStyle 21 , are illustrated in Fig. 3 .…”

Section: Resultsmentioning

confidence: 99%

QSPcc reduces bottlenecks in computational model simulations

et al. 2021

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“…A metabolite pathway enrichment analysis was performed for our probiotic community using bStyle [ 30 ]. Pathways were considered significant if a hypergeometric p value lower than 0.05 was obtained.…”

Section: Resultsmentioning

confidence: 99%

“…The hypergeometric distribution is used to evaluate how likely specific KEGG-available exogenously identified chemical compounds are associated to microbial-specific pathways and help identify those biological processes and pathways that best explain the meaning of the exogenous compounds. All analyses were performed using the graphical environment bStyle [ 30 ], which automated and simplified the entire integration and analytical process (Additional file 3 : Figure S1). bStyle also proved to be much faster than analogous R implementations.…”

Section: Methodsmentioning

confidence: 99%

A reverse metabolic approach to weaning: in silico identification of immune-beneficial infant gut bacteria, mining their metabolism for prebiotic feeds and sourcing these feeds in the natural product space

et al. 2018

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BackgroundWeaning is a period of marked physiological change. The introduction of solid foods and the changes in milk consumption are accompanied by significant gastrointestinal, immune, developmental, and microbial adaptations. Defining a reduced number of infections as the desired health benefit for infants around weaning, we identified in silico (i.e., by advanced public domain mining) infant gut microbes as potential deliverers of this benefit. We then investigated the requirements of these bacteria for exogenous metabolites as potential prebiotic feeds that were subsequently searched for in the natural product space.ResultsUsing public domain literature mining and an in silico reverse metabolic approach, we constructed probiotic-prebiotic-food associations, which can guide targeted feeding of immune health-beneficial microbes by weaning food; analyzed competition and synergy for (prebiotic) nutrients between selected microbes; and translated this information into designing an experimental complementary feed for infants enrolled in a pilot clinical trial (http://www.nourishtoflourish.auckland.ac.nz/).ConclusionsIn this study, we applied a benefit-oriented microbiome research strategy for enhanced early-life immune health. We extended from “classical” to molecular nutrition aiming to identify nutrients, bacteria, and mechanisms that point towards targeted feeding to improve immune health in infants around weaning. Here, we present the systems biology-based approach we used to inform us on the most promising prebiotic combinations known to support growth of beneficial gut bacteria (“probiotics”) in the infant gut, thereby favorably promoting development of the immune system.Electronic supplementary materialThe online version of this article (10.1186/s40168-018-0545-x) contains supplementary material, which is available to authorized users.

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“…The multithreading implementation allows scaling very well when computing averaged model dynamics obtained by running multiple stochastic simulations in parallel. The software has been designed to run in three user-scenarios: (i) via command-line, for example, as batch jobs or as part of wider modeling terminal scripts; (ii) programmatically embedded via its API in custom applications [27] or within MATLAB/Octave/R/Mathematica projects; (iii) as a self-standing simulation environment with a graphical user interface (GUI) for biomedical system modeling. For the three usage scenarios extensive documentation is available at the software web page (http://www.cosbi.eu/research/prototypes/hsimulator.).…”

Section: Resultsmentioning

confidence: 99%

HSimulator: Hybrid Stochastic/Deterministic Simulation of Biochemical Reaction Networks

2017

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HSimulator is a multithread simulator for mass-action biochemical reaction systems placed in a well-mixed environment. HSimulator provides optimized implementation of a set of widespread state-of-the-art stochastic, deterministic, and hybrid simulation strategies including the first publicly available implementation of the Hybrid Rejection-based Stochastic Simulation Algorithm (HRSSA). HRSSA, the fastest hybrid algorithm to date, allows for an efficient simulation of the models while ensuring the exact simulation of a subset of the reaction network modeling slow reactions. Benchmarks show that HSimulator is often considerably faster than the other considered simulators. The software, running on Java v6.0 or higher, offers a simulation GUI for modeling and visually exploring biological processes and a Javadoc-documented Java library to support the development of custom applications. HSimulator is released under the COSBI Shared Source license agreement (COSBI-SSLA).

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Graphical Modeling Meets Systems Pharmacology

Cited by 4 publications

References 32 publications

QSPcc reduces bottlenecks in computational model simulations

QSPcc reduces bottlenecks in computational model simulations

A reverse metabolic approach to weaning: in silico identification of immune-beneficial infant gut bacteria, mining their metabolism for prebiotic feeds and sourcing these feeds in the natural product space

HSimulator: Hybrid Stochastic/Deterministic Simulation of Biochemical Reaction Networks

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