Fuzzy-based Approach for Filling the Metabolic Pathway Hole
A key challenge in metabolic pathway hole problem is the reconstruction of the pathway data, reactions, enzymes and genes to use all this data to set the missing genes to the pathway which suffer from missing some genes in its reactions, we mean by the reconstruction here the relation between the enzymes and the genes in the pathway, 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.
Results: In this paper we propose a new method to solve the second type of pathway holes using fuzzy logic approach. We applied fuzzy on our published database, RGBMAPS [3] which consists of 100 pathways, 338 reactions and nearly 200,000. The system achieved an accuracy of 84%, where the correct genes which the system sets were 59 genes from the 70 genes.
Keywords: Metabolic pathway. Bioinformatics. Pathway hole. Fuzzy logic. RGB MAPS database.
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ABOUT THE AUTHORS
Ahmed Farouk Al-Sadek
Computer Science researcher in (Central Lab for Agricultural Expert Systems). http://www.claes.sci.eg/ResDetails.aspx?TabId=3&ResID=39&NavId=4&lang=en Computer Science Lecturer in (October University for modern science and Arts). Interested in Bioinformatics and machine learning.
Laila Mohamed Elfangary
interested in data mining and warehousing
Alaa Eldin Abdallah Yassin
Computer Science Research Assistant in (Central Lab for Agricultural Expert Systems). http://www.claes.sci.eg/ResDetails.aspx?TabId=3&ResID=74112&NavId=6&lang=en Master student \" Metabolic Pathway Analysis towards Gene therapy advising \". Interested in Bioinformatics and machine learning.
Ahmed Farouk Al-Sadek
Computer Science researcher in (Central Lab for Agricultural Expert Systems). http://www.claes.sci.eg/ResDetails.aspx?TabId=3&ResID=39&NavId=4&lang=en Computer Science Lecturer in (October University for modern science and Arts). Interested in Bioinformatics and machine learning.
Laila Mohamed Elfangary
interested in data mining and warehousing
Alaa Eldin Abdallah Yassin
Computer Science Research Assistant in (Central Lab for Agricultural Expert Systems). http://www.claes.sci.eg/ResDetails.aspx?TabId=3&ResID=74112&NavId=6&lang=en Master student \" Metabolic Pathway Analysis towards Gene therapy advising \". Interested in Bioinformatics and machine learning.