الفهرس 
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Abstract
Metabolic network is one of the important classes of biological networks, consisting of enzymatic reactions involving substrates and products. Recent developments in pathway databases enable us to analyze the known metabolic networks. However, most organism specific metabolic networks are left with a number of unknown enzymatic reactions, that is, many enzymes are missing in the known metabolic pathways, and these missing enzymes are defined as metabolic pathway holes, Although all reactions in some pathways are known, but also this pathways have a holes, the hole in this case means that we do not know the genes behind this reactions.
The pillar of the research cycle is the data collection which precedes the analysis phase to solve the pathway hole. The required data for this area is scattered among different data sources, which represent a problem for the researchers of this area. This thesis provides a solution to this obstacle by collecting the required data from various data sources in one database RGBMAPS, which helps the researchers in metabolic engineering at all, where consists of 100 human pathways, 338 reactions, about 3000 genes of seven organisms and around 200,000 human genes; also we have developed a tool to facilitate the use of RGBMAPS database and to make user friendly. Also in this thesis we introduced a fuzzy system which applied on the proposed database to solve one type of the pathway holes, which is missing the genes that catalyze a known EC and the accuracy of this system was 84%. The thesis produced a tool to build the rules in easy way which enabled other researchers to suggest new rules and apply it to obtain new results.