Dataset Information

Improving Nutritional Quality of Plant Proteins Through Genetic Engineering.

ABSTRACT: Humans and animals are unable to synthesize essential amino acids such as branch chain amino acids methionine (Met), lysine (Lys) and tryptophan (Trp). Therefore, these amino acids need to be supplied through the diets. Several essential amino acids are deficient or completely lacking among crops used for human food and animal feed. For example, soybean is deficient in Met; Lys and Trp are lacking in maize. In this mini review, we will first summarize the roles of essential amino acids in animal nutrition. Next, we will address the question: "What are the amino acids deficient in various plants and their biosynthesis pathways?" And: "What approaches are being used to improve the availability of essential amino acids in plants?" The potential targets for metabolic engineering will also be discussed, including what has already been done and what remains to be tested.

SUBMITTER: Le DT

PROVIDER: S-EPMC4869009 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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Improving Nutritional Quality of Plant Proteins Through Genetic Engineering.

Le Dung Tien DT Chu Ha Duc HD Le Ngoc Quynh NQ

Current genomics 20160601 3

Humans and animals are unable to synthesize essential amino acids such as branch chain amino acids methionine (Met), lysine (Lys) and tryptophan (Trp). Therefore, these amino acids need to be supplied through the diets. Several essential amino acids are deficient or completely lacking among crops used for human food and animal feed. For example, soybean is deficient in Met; Lys and Trp are lacking in maize. In this mini review, we will first summarize the roles of essential amino acids in animal ...[more]

PMID: 27252589

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Project description:BackgroundPortable-devices applications (Android applications) are becoming complex software systems that must be developed quickly and continuously evolved to fit new user requirements and execution contexts. Applications must be produced rapidly and advance persistently in order to fit new client requirements and execution settings. However, catering to these imperatives may bring about poor outline decisions on design choices, known as anti-patterns, which may possibly corrupt programming quality and execution. Thus, the automatic detection of anti-patterns is a vital process that facilitates both maintenance and evolution tasks. Additionally, it guides developers to refactor their applications and consequently enhance their quality.MethodsWe proposed a general method to detect mobile applications' anti-patterns that can detect both semantic and structural design anti-patterns. The proposed method is via reverse-engineering and ontology by using a UML modeling environment, an OWL ontology-based platform and ontology-driven conceptual modeling. We present and test a new method that generates the OWL ontology of mobile applications and analyzes the relationships among object-oriented anti-patterns and offer methods to resolve the anti-patterns by detecting and treating 15 different design's semantic and structural anti-patterns that occurred in analyzing of 29 mobile applications. We choose 29 mobile applications randomly. Selecting a browser is not a criterion in this method because the proposed method is applied on a design level. We demonstrate a semantic integration method to reduce the incidence of anti-patterns using the ontology merging on mobile applications.ResultsThe proposed method detected 15 semantic and structural design anti-patterns which have appeared 1,262 times in a random sample of 29 mobile applications. The proposed method introduced a new classification of the anti-patterns divided into four groups. "The anti-patterns in the class group" is the most group that has the maximum occurrences of anti-patterns and "The anti-patterns in the operation group" is the smallest one that has the minimum occurrences of the anti-patterns which are detected by the proposed method. The results also showed the correlation between the selected tools which we used as Modelio, the Protégé platform, and the OLED editor of the OntoUML. The results showed that there was a high positive relation between Modelio and Protégé which implies that the combination between both increases the accuracy level of the detection of anti-patterns. In the evaluation and analyzing the suitable integration method, we applied the different methods on homogeneous mobile applications and found that using ontology increased the detection percentage approximately by 11.3% in addition to guaranteed consistency.

Dataset Information

Improving Nutritional Quality of Plant Proteins Through Genetic Engineering.

Publications

Improving Nutritional Quality of Plant Proteins Through Genetic Engineering.

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