The Experts below are selected from a list of 108 Experts worldwide ranked by ideXlab platform
Mohd Saberi Mohamad - One of the best experts on this subject based on the ideXlab platform.
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Prediction of Vanillin Production in Yeast Using a Hybrid of Continuous Bees Algorithm and Flux Balance Analysis (CBAFBA)
Advances in Biomedical Infrastructure 2013, 2013Co-Authors: Yee Wen Choon, Lian En Chai, Chuii Khim Chong, Safaai Deris, Rosli Md. Illias, Mohd Saberi MohamadAbstract:Most food and beverage is containing artificial flavor compound. Creation of artificial flavors is not an easy step and it is hardly ever completely effective. In this paper, we introduce an in silico method in optimization of microbial strains of flavor compound synthesis. Previously, there are several algorithms such as Genetic Algorithm, Evolutionary Algorithm, OptKnock tool and other related techniques are widely used to predict the yield of target compound by suggesting the gene knockouts. The used of these algorithms or tools is able to predict the yield of production instead of using try and error method for gene deletions. Nowadays, without using in silico method, the direct experiment methods are not cost effective and time consumed. As we know, the cost of chemical is expensive and not all Flavorist able to afford the cost. However, the main limitations of previous algorithms are it failed to optimize the prediction of the yield and suggesting unrealistic flux distribution. Therefore, this paper proposed a hybrid of continuous Bees algorithm and Flux Balance Analysis. The target compound in this research is vanillin. The aim of study is to identify optimum gene knockouts. The results in this paper are the prediction of the yield and the growth rate values of the model. The predictive results showed that the improvement in term of yield which may help in food flavorings.
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Prediction of Vanillin and Glutamate Productions in Yeast Using a Hybrid of Continuous Bees Algorithm and Flux Balance Analysis (CBAFBA)
Current Bioinformatics, 2013Co-Authors: Yee Wen Choon, Lian En Chai, Chuii Khim Chong, Safaai Deris, Mohd Saberi Mohamad, Afnizanfaizal Abdullah, Rosli Md. IlliasAbstract:Most food and beverages contain artificial flavor compounds. Creation of artificial flavors is not an easy step and it is hardly ever completely effective. In this paper, we introduce an in silico method in optimization of microbial strains of flavor compound synthesis. Previously, several algorithms exist such as Genetic Algorithm, Evolutionary Algorithm, Opt Knock tool and other related techniques which are widely used to predict the yield of target compound by suggesting the gene knockouts. The use of these algorithms or tools to is able to predict the yield of production instead of using trial and error method for gene deletions. Nowadays, without using in silico method, the direct experiment methods are not cost effective and time consuming. As we know, the cost of chemical is expensive and not all Flavorists are able to afford the cost. However, the main limitations of previous algorithms are that they failed to optimize the prediction of the yield and suggesting unrealistic flux distribution. Therefore, this paper proposed a hybrid of continuous Bees algorithm and Flux Balance Analysis. The target compound in this research is vanillin and glutamate compound. The aim of study is to identify optimum gene knockouts. The results in this paper are the prediction of the yield and the growth rate values of the model. The predictive results showed that the improvement in terms of yield may help in food flavorings.
Rosli Md. Illias - One of the best experts on this subject based on the ideXlab platform.
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Prediction of Vanillin Production in Yeast Using a Hybrid of Continuous Bees Algorithm and Flux Balance Analysis (CBAFBA)
Advances in Biomedical Infrastructure 2013, 2013Co-Authors: Yee Wen Choon, Lian En Chai, Chuii Khim Chong, Safaai Deris, Rosli Md. Illias, Mohd Saberi MohamadAbstract:Most food and beverage is containing artificial flavor compound. Creation of artificial flavors is not an easy step and it is hardly ever completely effective. In this paper, we introduce an in silico method in optimization of microbial strains of flavor compound synthesis. Previously, there are several algorithms such as Genetic Algorithm, Evolutionary Algorithm, OptKnock tool and other related techniques are widely used to predict the yield of target compound by suggesting the gene knockouts. The used of these algorithms or tools is able to predict the yield of production instead of using try and error method for gene deletions. Nowadays, without using in silico method, the direct experiment methods are not cost effective and time consumed. As we know, the cost of chemical is expensive and not all Flavorist able to afford the cost. However, the main limitations of previous algorithms are it failed to optimize the prediction of the yield and suggesting unrealistic flux distribution. Therefore, this paper proposed a hybrid of continuous Bees algorithm and Flux Balance Analysis. The target compound in this research is vanillin. The aim of study is to identify optimum gene knockouts. The results in this paper are the prediction of the yield and the growth rate values of the model. The predictive results showed that the improvement in term of yield which may help in food flavorings.
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Prediction of Vanillin and Glutamate Productions in Yeast Using a Hybrid of Continuous Bees Algorithm and Flux Balance Analysis (CBAFBA)
Current Bioinformatics, 2013Co-Authors: Yee Wen Choon, Lian En Chai, Chuii Khim Chong, Safaai Deris, Mohd Saberi Mohamad, Afnizanfaizal Abdullah, Rosli Md. IlliasAbstract:Most food and beverages contain artificial flavor compounds. Creation of artificial flavors is not an easy step and it is hardly ever completely effective. In this paper, we introduce an in silico method in optimization of microbial strains of flavor compound synthesis. Previously, several algorithms exist such as Genetic Algorithm, Evolutionary Algorithm, Opt Knock tool and other related techniques which are widely used to predict the yield of target compound by suggesting the gene knockouts. The use of these algorithms or tools to is able to predict the yield of production instead of using trial and error method for gene deletions. Nowadays, without using in silico method, the direct experiment methods are not cost effective and time consuming. As we know, the cost of chemical is expensive and not all Flavorists are able to afford the cost. However, the main limitations of previous algorithms are that they failed to optimize the prediction of the yield and suggesting unrealistic flux distribution. Therefore, this paper proposed a hybrid of continuous Bees algorithm and Flux Balance Analysis. The target compound in this research is vanillin and glutamate compound. The aim of study is to identify optimum gene knockouts. The results in this paper are the prediction of the yield and the growth rate values of the model. The predictive results showed that the improvement in terms of yield may help in food flavorings.
Yee Wen Choon - One of the best experts on this subject based on the ideXlab platform.
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Prediction of Vanillin Production in Yeast Using a Hybrid of Continuous Bees Algorithm and Flux Balance Analysis (CBAFBA)
Advances in Biomedical Infrastructure 2013, 2013Co-Authors: Yee Wen Choon, Lian En Chai, Chuii Khim Chong, Safaai Deris, Rosli Md. Illias, Mohd Saberi MohamadAbstract:Most food and beverage is containing artificial flavor compound. Creation of artificial flavors is not an easy step and it is hardly ever completely effective. In this paper, we introduce an in silico method in optimization of microbial strains of flavor compound synthesis. Previously, there are several algorithms such as Genetic Algorithm, Evolutionary Algorithm, OptKnock tool and other related techniques are widely used to predict the yield of target compound by suggesting the gene knockouts. The used of these algorithms or tools is able to predict the yield of production instead of using try and error method for gene deletions. Nowadays, without using in silico method, the direct experiment methods are not cost effective and time consumed. As we know, the cost of chemical is expensive and not all Flavorist able to afford the cost. However, the main limitations of previous algorithms are it failed to optimize the prediction of the yield and suggesting unrealistic flux distribution. Therefore, this paper proposed a hybrid of continuous Bees algorithm and Flux Balance Analysis. The target compound in this research is vanillin. The aim of study is to identify optimum gene knockouts. The results in this paper are the prediction of the yield and the growth rate values of the model. The predictive results showed that the improvement in term of yield which may help in food flavorings.
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Prediction of Vanillin and Glutamate Productions in Yeast Using a Hybrid of Continuous Bees Algorithm and Flux Balance Analysis (CBAFBA)
Current Bioinformatics, 2013Co-Authors: Yee Wen Choon, Lian En Chai, Chuii Khim Chong, Safaai Deris, Mohd Saberi Mohamad, Afnizanfaizal Abdullah, Rosli Md. IlliasAbstract:Most food and beverages contain artificial flavor compounds. Creation of artificial flavors is not an easy step and it is hardly ever completely effective. In this paper, we introduce an in silico method in optimization of microbial strains of flavor compound synthesis. Previously, several algorithms exist such as Genetic Algorithm, Evolutionary Algorithm, Opt Knock tool and other related techniques which are widely used to predict the yield of target compound by suggesting the gene knockouts. The use of these algorithms or tools to is able to predict the yield of production instead of using trial and error method for gene deletions. Nowadays, without using in silico method, the direct experiment methods are not cost effective and time consuming. As we know, the cost of chemical is expensive and not all Flavorists are able to afford the cost. However, the main limitations of previous algorithms are that they failed to optimize the prediction of the yield and suggesting unrealistic flux distribution. Therefore, this paper proposed a hybrid of continuous Bees algorithm and Flux Balance Analysis. The target compound in this research is vanillin and glutamate compound. The aim of study is to identify optimum gene knockouts. The results in this paper are the prediction of the yield and the growth rate values of the model. The predictive results showed that the improvement in terms of yield may help in food flavorings.
Lian En Chai - One of the best experts on this subject based on the ideXlab platform.
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Prediction of Vanillin Production in Yeast Using a Hybrid of Continuous Bees Algorithm and Flux Balance Analysis (CBAFBA)
Advances in Biomedical Infrastructure 2013, 2013Co-Authors: Yee Wen Choon, Lian En Chai, Chuii Khim Chong, Safaai Deris, Rosli Md. Illias, Mohd Saberi MohamadAbstract:Most food and beverage is containing artificial flavor compound. Creation of artificial flavors is not an easy step and it is hardly ever completely effective. In this paper, we introduce an in silico method in optimization of microbial strains of flavor compound synthesis. Previously, there are several algorithms such as Genetic Algorithm, Evolutionary Algorithm, OptKnock tool and other related techniques are widely used to predict the yield of target compound by suggesting the gene knockouts. The used of these algorithms or tools is able to predict the yield of production instead of using try and error method for gene deletions. Nowadays, without using in silico method, the direct experiment methods are not cost effective and time consumed. As we know, the cost of chemical is expensive and not all Flavorist able to afford the cost. However, the main limitations of previous algorithms are it failed to optimize the prediction of the yield and suggesting unrealistic flux distribution. Therefore, this paper proposed a hybrid of continuous Bees algorithm and Flux Balance Analysis. The target compound in this research is vanillin. The aim of study is to identify optimum gene knockouts. The results in this paper are the prediction of the yield and the growth rate values of the model. The predictive results showed that the improvement in term of yield which may help in food flavorings.
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Prediction of Vanillin and Glutamate Productions in Yeast Using a Hybrid of Continuous Bees Algorithm and Flux Balance Analysis (CBAFBA)
Current Bioinformatics, 2013Co-Authors: Yee Wen Choon, Lian En Chai, Chuii Khim Chong, Safaai Deris, Mohd Saberi Mohamad, Afnizanfaizal Abdullah, Rosli Md. IlliasAbstract:Most food and beverages contain artificial flavor compounds. Creation of artificial flavors is not an easy step and it is hardly ever completely effective. In this paper, we introduce an in silico method in optimization of microbial strains of flavor compound synthesis. Previously, several algorithms exist such as Genetic Algorithm, Evolutionary Algorithm, Opt Knock tool and other related techniques which are widely used to predict the yield of target compound by suggesting the gene knockouts. The use of these algorithms or tools to is able to predict the yield of production instead of using trial and error method for gene deletions. Nowadays, without using in silico method, the direct experiment methods are not cost effective and time consuming. As we know, the cost of chemical is expensive and not all Flavorists are able to afford the cost. However, the main limitations of previous algorithms are that they failed to optimize the prediction of the yield and suggesting unrealistic flux distribution. Therefore, this paper proposed a hybrid of continuous Bees algorithm and Flux Balance Analysis. The target compound in this research is vanillin and glutamate compound. The aim of study is to identify optimum gene knockouts. The results in this paper are the prediction of the yield and the growth rate values of the model. The predictive results showed that the improvement in terms of yield may help in food flavorings.
Chuii Khim Chong - One of the best experts on this subject based on the ideXlab platform.
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Prediction of Vanillin Production in Yeast Using a Hybrid of Continuous Bees Algorithm and Flux Balance Analysis (CBAFBA)
Advances in Biomedical Infrastructure 2013, 2013Co-Authors: Yee Wen Choon, Lian En Chai, Chuii Khim Chong, Safaai Deris, Rosli Md. Illias, Mohd Saberi MohamadAbstract:Most food and beverage is containing artificial flavor compound. Creation of artificial flavors is not an easy step and it is hardly ever completely effective. In this paper, we introduce an in silico method in optimization of microbial strains of flavor compound synthesis. Previously, there are several algorithms such as Genetic Algorithm, Evolutionary Algorithm, OptKnock tool and other related techniques are widely used to predict the yield of target compound by suggesting the gene knockouts. The used of these algorithms or tools is able to predict the yield of production instead of using try and error method for gene deletions. Nowadays, without using in silico method, the direct experiment methods are not cost effective and time consumed. As we know, the cost of chemical is expensive and not all Flavorist able to afford the cost. However, the main limitations of previous algorithms are it failed to optimize the prediction of the yield and suggesting unrealistic flux distribution. Therefore, this paper proposed a hybrid of continuous Bees algorithm and Flux Balance Analysis. The target compound in this research is vanillin. The aim of study is to identify optimum gene knockouts. The results in this paper are the prediction of the yield and the growth rate values of the model. The predictive results showed that the improvement in term of yield which may help in food flavorings.
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Prediction of Vanillin and Glutamate Productions in Yeast Using a Hybrid of Continuous Bees Algorithm and Flux Balance Analysis (CBAFBA)
Current Bioinformatics, 2013Co-Authors: Yee Wen Choon, Lian En Chai, Chuii Khim Chong, Safaai Deris, Mohd Saberi Mohamad, Afnizanfaizal Abdullah, Rosli Md. IlliasAbstract:Most food and beverages contain artificial flavor compounds. Creation of artificial flavors is not an easy step and it is hardly ever completely effective. In this paper, we introduce an in silico method in optimization of microbial strains of flavor compound synthesis. Previously, several algorithms exist such as Genetic Algorithm, Evolutionary Algorithm, Opt Knock tool and other related techniques which are widely used to predict the yield of target compound by suggesting the gene knockouts. The use of these algorithms or tools to is able to predict the yield of production instead of using trial and error method for gene deletions. Nowadays, without using in silico method, the direct experiment methods are not cost effective and time consuming. As we know, the cost of chemical is expensive and not all Flavorists are able to afford the cost. However, the main limitations of previous algorithms are that they failed to optimize the prediction of the yield and suggesting unrealistic flux distribution. Therefore, this paper proposed a hybrid of continuous Bees algorithm and Flux Balance Analysis. The target compound in this research is vanillin and glutamate compound. The aim of study is to identify optimum gene knockouts. The results in this paper are the prediction of the yield and the growth rate values of the model. The predictive results showed that the improvement in terms of yield may help in food flavorings.