The association between miRNA and disease has attracted more and more attention.Until now,existing methods for identifying miRNA related disease mainly rely on top-ranked association model,which may not provide a full...The association between miRNA and disease has attracted more and more attention.Until now,existing methods for identifying miRNA related disease mainly rely on top-ranked association model,which may not provide a full landscape of association between miRNA and disease.Hence there is strong need of new computational method to identify the associations from miRNA group view.In this paper,we proposed a framework,MDA-TOEPGA,to identify miRNAdisease association based on two-objective evolutionary programming genetic algorithm,which identifies latent miRNAdisease associations from the view of functional module.To understand the miRNA functional module in diseases,the case study is presented.We have been compared MDA-TOEPGA with several state-of-the-art functional module algorithm.Experimental results showed that our method cannot only outperform classical algorithms,such as K-means,IK-means,MCODE,HC-PIN,and ClusterONE,but can also achieve an ideal overall performance in terms of a composite score consisting of f1,Sensitivity,and Accuracy.Altogether,our study showed that MDA-TOEPGA is a promising method to investigate miRNA-disease association from the landscapes of functional module.展开更多
In recent years, energy-retrofitting is becoming an imperative aim for existing buildings worldwide and increased interest has focused on the development of nanoparticle blended concretes with adequate mechanical...In recent years, energy-retrofitting is becoming an imperative aim for existing buildings worldwide and increased interest has focused on the development of nanoparticle blended concretes with adequate mechanical properties and durability performance, through the optimization of concrete permeability and the incorporation of the proper nanoparticle type in the concrete matrix. In order to investigate the potential use of nanocomposites as dense barriers against the permeation of liquids into the concrete, three types of nanoparticles including Zinc Oxide (ZnO), Magnesium Oxide (MgO), and composite nanoparticles were used in the present study as partial replacement of cement. Besides, the effect of adding these nanoparticles on both pore structure and mechanical strengths of the concrete at different ages was determined, and scanning electron microscopy (SEM) images were then used to illustrate the uniformity dispersion of nanoparticles in cement paste. It was demonstrated that the addition of a small number of nanoparticles effectively enhances the mechanical properties of concrete and consequently reduces the extent of the water permeation front. Finally, the behavioral models using Genetic Algorithm (GA) programming were developed to describe the time-dependent behavioral characteristics of nanoparticle blended concrete samples in various compressive and tensile stress states at different ages.展开更多
基金This work was supported in part by the National Natural Science Foundation of China under Grants 61873089,62032007the Key Project of the Education Department of Hunan Province under Grant 20A087the Innovation Platform Open Fund Project of Hunan Provincial Education Department under Grant 20K025.
文摘The association between miRNA and disease has attracted more and more attention.Until now,existing methods for identifying miRNA related disease mainly rely on top-ranked association model,which may not provide a full landscape of association between miRNA and disease.Hence there is strong need of new computational method to identify the associations from miRNA group view.In this paper,we proposed a framework,MDA-TOEPGA,to identify miRNAdisease association based on two-objective evolutionary programming genetic algorithm,which identifies latent miRNAdisease associations from the view of functional module.To understand the miRNA functional module in diseases,the case study is presented.We have been compared MDA-TOEPGA with several state-of-the-art functional module algorithm.Experimental results showed that our method cannot only outperform classical algorithms,such as K-means,IK-means,MCODE,HC-PIN,and ClusterONE,but can also achieve an ideal overall performance in terms of a composite score consisting of f1,Sensitivity,and Accuracy.Altogether,our study showed that MDA-TOEPGA is a promising method to investigate miRNA-disease association from the landscapes of functional module.
文摘In recent years, energy-retrofitting is becoming an imperative aim for existing buildings worldwide and increased interest has focused on the development of nanoparticle blended concretes with adequate mechanical properties and durability performance, through the optimization of concrete permeability and the incorporation of the proper nanoparticle type in the concrete matrix. In order to investigate the potential use of nanocomposites as dense barriers against the permeation of liquids into the concrete, three types of nanoparticles including Zinc Oxide (ZnO), Magnesium Oxide (MgO), and composite nanoparticles were used in the present study as partial replacement of cement. Besides, the effect of adding these nanoparticles on both pore structure and mechanical strengths of the concrete at different ages was determined, and scanning electron microscopy (SEM) images were then used to illustrate the uniformity dispersion of nanoparticles in cement paste. It was demonstrated that the addition of a small number of nanoparticles effectively enhances the mechanical properties of concrete and consequently reduces the extent of the water permeation front. Finally, the behavioral models using Genetic Algorithm (GA) programming were developed to describe the time-dependent behavioral characteristics of nanoparticle blended concrete samples in various compressive and tensile stress states at different ages.
