BIAM: a new bio-inspired analysis methodology for digital ecosystems based on a scale-free architecture

Conti, Vincenzo; Ruffo, Simone Sante; Vitabile, Salvatore; Barolli, Leonard

doi:10.1007/s00500-017-2832-z

Cited by 9 publications

(8 citation statements)

References 43 publications

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“…The BIAM framework implements an integrated analysis methodology based on topological analysis, FBA analysis, and Extreme Pathways analysis [26,134]. The framework supplies the needed tools for drawing a network and analyzing its structural and functional properties.…”

Section: Model Reduction and Simplificationmentioning

confidence: 99%

“…The framework supplies the needed tools for drawing a network and analyzing its structural and functional properties. Several scale-free network architectures, dealing with different application domains, have been simulated and validated [26,136]. Topological and functional analysis can be combined to select the main functional nodes and paths of a cellular network.…”

Section: Model Reduction and Simplificationmentioning

confidence: 99%

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Towards Human Cell Simulation

Spolaor

Gribaudo

Iacono

et al. 2019

Lecture Notes in Computer Science

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The faithful reproduction and accurate prediction of the phenotypes and emergent behaviors of complex cellular systems are among the most challenging goals in Systems Biology. Although mathematical models that describe the interactions among all biochemical processes in a cell are theoretically feasible, their simulation is generally hard because of a variety of reasons. For instance, many quantitative data (e.g., kinetic rates) are usually not available, a problem that hinders the execution of simulation algorithms as long as some parameter estimation methods are used. Though, even with a candidate parameterization, the simulation of mechanistic models could be challenging due to the extreme computational effort required. In this context, model reduction techniques and High-Performance Computing infrastructures could be leveraged to mitigate these issues. In addition, as cellular processes are characterized by multiple scales of temporal and spatial organization, novel hybrid simulators able to harmonize different modeling approaches (e.g., logic-based, constraint-based, continuous deterministic, discrete stochastic, spatial) should be designed. This chapter describes a putative unified approach to tackle these challenging tasks, hopefully paving the way to the definition of large-scale comprehensive models that aim at the comprehension of the cell behavior by means of computational tools.

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Section: Model Reduction and Simplificationmentioning

confidence: 99%

Section: Model Reduction and Simplificationmentioning

confidence: 99%

Towards Human Cell Simulation

Spolaor

Gribaudo

Iacono

et al. 2019

Lecture Notes in Computer Science

Self Cite

View full text Add to dashboard Cite

show abstract

“…The approach optimises traffic flows over a road network, minimises road congestion and maximises the number of vehicles reaching their destination target. In [118], the bioinspired methodology has been applied to a class of digital ecosystems based on a scale-free architecture for both maximum information flow and fault/error tolerance detection. Highly connected nodes, inter-module connectors and ultraperipheral nodes can be identified by evaluating their impact on digital ecosystems behavior and addressing their strengthen, fault tolerance and protection countermeasures.…”

Section: Many Acute and Chronic Diseases Originate As Network Diseasementioning

confidence: 99%

Why High-Performance Modelling and Simulation for Big Data Applications Matters

Grelck

Niewiadomska-Szynkiewicz

Aldinucci

et al. 2019

Lecture Notes in Computer Science

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Modelling and Simulation (M&S) offer adequate abstractions to manage the complexity of analysing big data in scientific and engineering domains. Unfortunately, big data problems are often not easily amenable to efficient and effective use of High Performance Computing (HPC) facilities and technologies. Furthermore, M&S communities typically lack the detailed expertise required to exploit the full potential of HPC solutions while HPC specialists may not be fully aware of specific modelling and simulation requirements and applications. The COST Action IC1406 High-Performance Modelling and Simulation for Big Data Applications has created a strategic framework to foster interaction between M&S experts from various application domains on the one hand and HPC experts on the other hand to develop effective solutions for big data applications. One of the tangible outcomes of the COST Action is a collection of case studies from various computing domains. Each case study brought together both HPC and M&S experts, giving witness of the effective cross-pollination facilitated by the COST Action. In this introductory article we argue why joining forces between M&S and HPC communities is both timely in the big data era and crucial for success in many application domains. Moreover, we provide an overview on the state of the art in the various research areas concerned.

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“…In this paper we propose a new approach that leverages the application of bio-inspired algorithms [17] to tackle the problem of attack graphs analysis. The paper envisions some new application scenarios for these algorithms that show a high level of adaptability to different fields of applications, as already seen in [18], [19]. The implemented and proposed framework is an extension of the BIAM software proposed in [18].…”

Section: Introductionmentioning

confidence: 99%

“…The paper envisions some new application scenarios for these algorithms that show a high level of adaptability to different fields of applications, as already seen in [18], [19]. The implemented and proposed framework is an extension of the BIAM software proposed in [18]. The framework allows the drawing and managing of complex networks and their analysis by means of bioinspired algorithms derived from techniques of analysis originally designed for usage with metabolic networks.…”

Section: Introductionmentioning

confidence: 99%

Bio-inspired security analysis for IoT scenarios

Conti

Ziggiotto

Migliardi

et al. 2020

IJES

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Computer security has recently become more and more important as the world economy dependency from data has kept growing. The complexity of the systems that need to be kept secure calls for new models capable of abstracting the interdependencies among heterogeneous components that cooperate at providing the desired service. A promising approach is attack graph analysis, however, the manual analysis of attack graphs is tedious and error prone. In this paper we propose to apply the metabolic network model to attack graphs analysis, using three interacting bio-inspired algorithms: topological analysis, flux balance analysis, and extreme pathway analysis. A developed framework for graph building and simulations as well as an introductory to some IoT scenarios as use cases are also outlined.

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BIAM: a new bio-inspired analysis methodology for digital ecosystems based on a scale-free architecture

Cited by 9 publications

References 43 publications

Towards Human Cell Simulation

Towards Human Cell Simulation

Why High-Performance Modelling and Simulation for Big Data Applications Matters

Bio-inspired security analysis for IoT scenarios

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