The Experts below are selected from a list of 204825 Experts worldwide ranked by ideXlab platform
Feixiong Cheng - One of the best experts on this subject based on the ideXlab platform.
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quantitative and systems pharmacology 3 Network based identification of new Targets for natural products enables potential uses in aging associated disorders
Frontiers in Pharmacology, 2017Co-Authors: Jiansong Fang, Feixiong Cheng, Qihui Wu, Tian Wu, Jun Wu, Qi WangAbstract:Aging that refers the accumulation of genetic and physiology changes in cells and tissues over a lifetime has been shown a high risk of developing various complex diseases, such as neurodegenerative disease, cardiovascular disease and cancer. Over the past several decades, natural products have been demonstrated as anti-aging interveners via extending lifespan and preventing aging-associated disorders. In this study, we developed an integrated systems pharmacology infrastructure to uncover new indications for aging-associated disorders by natural products. Specifically, we incorporated 411 high-quality aging-associated human genes or human-orthologous genes from mus musculus, saccharomyces cerevisiae, caenorhabditis elegans, and drosophila melanogaster. We constructed a global drug-Target Network of natural products by integrating both experimental and computationally predicted drug-Target interactions. We further built the statistical Network models for identification of new anti-aging indications of natural products through integration of the curated aging-associated genes and drug-Target Network of natural products. High accuracy was achieved on the Network models. We showcased several Network-predicted anti-aging indications of four typical natural products (caffeic acid, metformin, myricetin and resveratrol) with new mechanism-of-actions. In summary, this study offers a powerful systems pharmacology infrastructure to identify natural products for treatment of aging-associated disorders.
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quantitative and systems pharmacology 3 Network based identification of new Targets for natural products enables potential uses in aging associated disorders
Frontiers in Pharmacology, 2017Co-Authors: Jiansong Fang, Feixiong Cheng, Qi Wang, Li GaoAbstract:Aging that refers the accumulation of genetic and physiology changes in cells and tissues over a lifetime has been shown a high risk of developing various complex diseases, such as neurodegenerative disease, cardiovascular disease and cancer. Over the past several decades, natural products have been demonstrated as anti-aging interveners via extending lifespan and preventing aging-associated disorders. In this study, we developed an integrated systems pharmacology infrastructure to uncover new indications for aging-associated disorders by natural products. Specifically, we incorporated 411 high-quality aging-associated human genes or human-orthologous genes from mus musculus (MM), saccharomyces cerevisiae (SC), caenorhabditis elegans (CE), and drosophila melanogaster (DM). We constructed a global drug-Target Network of natural products by integrating both experimental and computationally predicted drug-Target interactions (DTI). We further built the statistical Network models for identification of new anti-aging indications of natural products through integration of the curated aging-associated genes and drug-Target Network of natural products. High accuracy was achieved on the Network models. We showcased several Network-predicted anti-aging indications of four typical natural products (caffeic acid, metformin, myricetin, and resveratrol) with new mechanism-of-actions. In summary, this study offers a powerful systems pharmacology infrastructure to identify natural products for treatment of aging-associated disorders.
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quantitative and systems pharmacology 1 in silico prediction of drug Target interactions of natural products enables new Targeted cancer therapy
Journal of Chemical Information and Modeling, 2017Co-Authors: Jiansong Fang, Yun Tang, Qi Wang, Zengrui Wu, Feixiong ChengAbstract:Natural products with diverse chemical scaffolds have been recognized as an invaluable source of compounds in drug discovery and development. However, systematic identification of drug Targets for natural products at the human proteome level via various experimental assays is highly expensive and time-consuming. In this study, we proposed a systems pharmacology infrastructure to predict new drug Targets and anticancer indications of natural products. Specifically, we reconstructed a global drug–Target Network with 7,314 interactions connecting 751 Targets and 2,388 natural products and built predictive Network models via a balanced substructure–drug–Target Network-based inference approach. A high area under receiver operating characteristic curve of 0.96 was yielded for predicting new Targets of natural products during cross-validation. The newly predicted Targets of natural products (e.g., resveratrol, genistein, and kaempferol) with high scores were validated by various literature studies. We further bu...
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in silico prediction of chemical mechanism of action via an improved Network based inference method
British Journal of Pharmacology, 2016Co-Authors: Anqi Luo, Hanping Bian, Guixia Liu, Jin Huang, Feixiong Cheng, Yun TangAbstract:Background and purpose Deciphering chemical mechanism-of-action (MoA) enables the development of novel therapeutics (e.g. drug repositioning) and evaluation of drug side effects. Development of novel computational methods for chemical MoA assessment under systems pharmacology framework would accelerate drug discovery and development with high efficiency and low cost. Experimental approach In this study, we proposed an improved Network-based inference method, namely balanced substructure-drug-Target Network-based inference (bSDTNBI), to predict MoA for old drugs, clinical failed drugs, and new chemical entities. Specifically, three parameters were introduced into Network-based resource diffusion processes to adjust the initial resource allocation of different node types, the weighted values of different edge types, and the influence of hub nodes, respectively. The performance of the method was systematically validated by benchmark datasets and bioassays. Key results High performance was yielded for bSDTNBI in both 10-fold and leave-one-out cross validations. A global drug-Target Network was built to explore MoA of anticancer drugs and repurpose old drugs for 15 cancer types/subtypes. In a case study, 27 predicted candidates among 56 commercially available compounds were experimentally validated to have binding affinities on estrogen receptor α with IC50 or EC50 values ≤ 10 μM. Furthermore, two dual ligands with both agonistic and antagonistic activities ≤ 1 μM would provide potential lead compounds for the development of novel Targeted therapy in breast cancer or osteoporosis. Conclusion and implications In summary, bSDTNBI would provide a powerful tool for the MoA assessment on both old drugs and novel compounds in drug discovery and development.
Yoshikazu Fukuyama - One of the best experts on this subject based on the ideXlab platform.
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Long-term distribution Network expansion planning by Network reconfiguration and generation of construction plans
IEEE Transactions on Power Systems, 2003Co-Authors: T. Asakura, T. Genji, T. Yura, N. Hayashi, Yoshikazu FukuyamaAbstract:This paper proposes a distribution Network expansion planning method by Network reconfiguration and generation of construction plans. Considering natural growth of electric loads and installation of new large customers, the method first tries to reconfigure the Target Network by changing switch status for loss minimization and analyzing security of the Target Network by contingency analysis. If operational constraints are violated even in the reconfigured Network, the method tries to generate construction plan candidates, which can eliminate the operational constraint violations. The proposed method handles long-term yearly load increase and generates the best Network expansion plans, namely, the best Network reconfiguration and construction plans for each year of the Target term. The proposed method is verified by comparing construction plans generated by the proposed method with the actual plan composed by experienced planning persons in distribution control centers. It is found that the proposed method can generate the same plans generated by the experienced persons. Moreover, the method can generate various alternative construction plan candidates. The results indicate the practical applicability of the proposed distribution Network expansion planning method.
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Long-term distribution Network expansion planning by Network reconfiguration and generation of construction plans
2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491), 2024Co-Authors: T. Asakura, T. Genji, T. Yura, N. Hayashi, Yoshikazu FukuyamaAbstract:Summary form only given. This paper proposes a distribution Network expansion planning method by Network reconfiguration and generation of construction plans. Considering natural growth of electric loads and installation of new large customers, the method first tries to reconfigure the Target Network by changing switch status for loss minimization and analyzing security of the Target Network by contingency analysis. If operational constraints are violated even in the reconfigured Network, the method tries to generate construction plan candidates, which can eliminate the operational constraint violations. The proposed method handles long-term yearly load increase and generates the best Network expansion plans, namely, the best Network reconfiguration and construction plans for each year of the Target term. The proposed method is verified by comparing construction plans generated by the proposed method with the actual plan composed by experienced planning persons in distribution control centers. It is found that the proposed method can generate the same plans generated by the experienced persons. Moreover, the method can generate various alternative construction plan candidates. The results indicate the practical applicability of the proposed distribution Network expansion planning method.
Jason Ioannidis - One of the best experts on this subject based on the ideXlab platform.
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a mirna Target Network putatively involved in follicular atresia
Domestic Animal Endocrinology, 2017Co-Authors: F X Donadeu, Bushra T Mohammed, Jason IoannidisAbstract:Abstract In a previous microarray study, we identified a subset of micro RNAS (miRNAs), which expression was distinctly higher in atretic than healthy follicles of cattle. In the present study, we investigated the involvement of those miRNAs in granulosa and theca cells during atresia. Reverse Transcription-quantitative Polymerase Chain Reaction (RT-qPCR) confirmed that miR-21-5p/-3p, miR-150, miR-409a, miR-142-5p, miR-378, miR-222, miR-155, and miR-199a-5p were expressed at higher levels in atretic than healthy follicles (9–17 mm, classified based on steroidogenic capacity). All miRNAs except miR-21-3p and miR-378 were expressed at higher levels in theca than granulosa cells. The expression of 13 predicted miRNA Targets was determined in follicular cells by RT-qPCR, revealing downregulation of HIF1A , ETS1 , JAG1 , VEGFA , and MSH2 in either or both cell types during atresia. Based on increases in miRNA levels simultaneous with decreases in Target levels in follicular cells, several predicted miRNA Target interactions were confirmed that are putatively involved in follicular atresia, namely miR-199a-5p/miR-155- HIF1A in granulosa cells, miR-155/miR-222- ETS1 in theca cells, miR-199a-5p- JAG1 in theca cells, miR-199a-5p/miR-150/miR-378- VEGFA in granulosa and theca cells, and miR-155- MSH2 in theca cells. These results offer novel insight on the involvement of miRNAs in follicle development by identifying a miRNA Target Network that is putatively involved in follicle atresia.
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a mirna Target Network putatively involved in follicular atresia
Domestic Animal Endocrinology, 2017Co-Authors: F X Donadeu, Bushra T Mohammed, Jason IoannidisAbstract:Abstract In a previous microarray study, we identified a subset of micro RNAS (miRNAs), which expression was distinctly higher in atretic than healthy follicles of cattle. In the present study, we investigated the involvement of those miRNAs in granulosa and theca cells during atresia. Reverse Transcription-quantitative Polymerase Chain Reaction (RT-qPCR) confirmed that miR-21-5p/-3p, miR-150, miR-409a, miR-142-5p, miR-378, miR-222, miR-155, and miR-199a-5p were expressed at higher levels in atretic than healthy follicles (9–17 mm, classified based on steroidogenic capacity). All miRNAs except miR-21-3p and miR-378 were expressed at higher levels in theca than granulosa cells. The expression of 13 predicted miRNA Targets was determined in follicular cells by RT-qPCR, revealing downregulation of HIF1A , ETS1 , JAG1 , VEGFA , and MSH2 in either or both cell types during atresia. Based on increases in miRNA levels simultaneous with decreases in Target levels in follicular cells, several predicted miRNA Target interactions were confirmed that are putatively involved in follicular atresia, namely miR-199a-5p/miR-155- HIF1A in granulosa cells, miR-155/miR-222- ETS1 in theca cells, miR-199a-5p- JAG1 in theca cells, miR-199a-5p/miR-150/miR-378- VEGFA in granulosa and theca cells, and miR-155- MSH2 in theca cells. These results offer novel insight on the involvement of miRNAs in follicle development by identifying a miRNA Target Network that is putatively involved in follicle atresia.
Jiansong Fang - One of the best experts on this subject based on the ideXlab platform.
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quantitative and systems pharmacology 3 Network based identification of new Targets for natural products enables potential uses in aging associated disorders
Frontiers in Pharmacology, 2017Co-Authors: Jiansong Fang, Feixiong Cheng, Qihui Wu, Tian Wu, Jun Wu, Qi WangAbstract:Aging that refers the accumulation of genetic and physiology changes in cells and tissues over a lifetime has been shown a high risk of developing various complex diseases, such as neurodegenerative disease, cardiovascular disease and cancer. Over the past several decades, natural products have been demonstrated as anti-aging interveners via extending lifespan and preventing aging-associated disorders. In this study, we developed an integrated systems pharmacology infrastructure to uncover new indications for aging-associated disorders by natural products. Specifically, we incorporated 411 high-quality aging-associated human genes or human-orthologous genes from mus musculus, saccharomyces cerevisiae, caenorhabditis elegans, and drosophila melanogaster. We constructed a global drug-Target Network of natural products by integrating both experimental and computationally predicted drug-Target interactions. We further built the statistical Network models for identification of new anti-aging indications of natural products through integration of the curated aging-associated genes and drug-Target Network of natural products. High accuracy was achieved on the Network models. We showcased several Network-predicted anti-aging indications of four typical natural products (caffeic acid, metformin, myricetin and resveratrol) with new mechanism-of-actions. In summary, this study offers a powerful systems pharmacology infrastructure to identify natural products for treatment of aging-associated disorders.
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quantitative and systems pharmacology 3 Network based identification of new Targets for natural products enables potential uses in aging associated disorders
Frontiers in Pharmacology, 2017Co-Authors: Jiansong Fang, Feixiong Cheng, Qi Wang, Li GaoAbstract:Aging that refers the accumulation of genetic and physiology changes in cells and tissues over a lifetime has been shown a high risk of developing various complex diseases, such as neurodegenerative disease, cardiovascular disease and cancer. Over the past several decades, natural products have been demonstrated as anti-aging interveners via extending lifespan and preventing aging-associated disorders. In this study, we developed an integrated systems pharmacology infrastructure to uncover new indications for aging-associated disorders by natural products. Specifically, we incorporated 411 high-quality aging-associated human genes or human-orthologous genes from mus musculus (MM), saccharomyces cerevisiae (SC), caenorhabditis elegans (CE), and drosophila melanogaster (DM). We constructed a global drug-Target Network of natural products by integrating both experimental and computationally predicted drug-Target interactions (DTI). We further built the statistical Network models for identification of new anti-aging indications of natural products through integration of the curated aging-associated genes and drug-Target Network of natural products. High accuracy was achieved on the Network models. We showcased several Network-predicted anti-aging indications of four typical natural products (caffeic acid, metformin, myricetin, and resveratrol) with new mechanism-of-actions. In summary, this study offers a powerful systems pharmacology infrastructure to identify natural products for treatment of aging-associated disorders.
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quantitative and systems pharmacology 1 in silico prediction of drug Target interactions of natural products enables new Targeted cancer therapy
Journal of Chemical Information and Modeling, 2017Co-Authors: Jiansong Fang, Yun Tang, Qi Wang, Zengrui Wu, Feixiong ChengAbstract:Natural products with diverse chemical scaffolds have been recognized as an invaluable source of compounds in drug discovery and development. However, systematic identification of drug Targets for natural products at the human proteome level via various experimental assays is highly expensive and time-consuming. In this study, we proposed a systems pharmacology infrastructure to predict new drug Targets and anticancer indications of natural products. Specifically, we reconstructed a global drug–Target Network with 7,314 interactions connecting 751 Targets and 2,388 natural products and built predictive Network models via a balanced substructure–drug–Target Network-based inference approach. A high area under receiver operating characteristic curve of 0.96 was yielded for predicting new Targets of natural products during cross-validation. The newly predicted Targets of natural products (e.g., resveratrol, genistein, and kaempferol) with high scores were validated by various literature studies. We further bu...
T. Asakura - One of the best experts on this subject based on the ideXlab platform.
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Long-term distribution Network expansion planning by Network reconfiguration and generation of construction plans
IEEE Transactions on Power Systems, 2003Co-Authors: T. Asakura, T. Genji, T. Yura, N. Hayashi, Yoshikazu FukuyamaAbstract:This paper proposes a distribution Network expansion planning method by Network reconfiguration and generation of construction plans. Considering natural growth of electric loads and installation of new large customers, the method first tries to reconfigure the Target Network by changing switch status for loss minimization and analyzing security of the Target Network by contingency analysis. If operational constraints are violated even in the reconfigured Network, the method tries to generate construction plan candidates, which can eliminate the operational constraint violations. The proposed method handles long-term yearly load increase and generates the best Network expansion plans, namely, the best Network reconfiguration and construction plans for each year of the Target term. The proposed method is verified by comparing construction plans generated by the proposed method with the actual plan composed by experienced planning persons in distribution control centers. It is found that the proposed method can generate the same plans generated by the experienced persons. Moreover, the method can generate various alternative construction plan candidates. The results indicate the practical applicability of the proposed distribution Network expansion planning method.
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Long-term distribution Network expansion planning by Network reconfiguration and generation of construction plans
2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491), 2024Co-Authors: T. Asakura, T. Genji, T. Yura, N. Hayashi, Yoshikazu FukuyamaAbstract:Summary form only given. This paper proposes a distribution Network expansion planning method by Network reconfiguration and generation of construction plans. Considering natural growth of electric loads and installation of new large customers, the method first tries to reconfigure the Target Network by changing switch status for loss minimization and analyzing security of the Target Network by contingency analysis. If operational constraints are violated even in the reconfigured Network, the method tries to generate construction plan candidates, which can eliminate the operational constraint violations. The proposed method handles long-term yearly load increase and generates the best Network expansion plans, namely, the best Network reconfiguration and construction plans for each year of the Target term. The proposed method is verified by comparing construction plans generated by the proposed method with the actual plan composed by experienced planning persons in distribution control centers. It is found that the proposed method can generate the same plans generated by the experienced persons. Moreover, the method can generate various alternative construction plan candidates. The results indicate the practical applicability of the proposed distribution Network expansion planning method.
