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- W2295984145 abstract "The development of sophisticated sequencing machines and DNA techniques has enabled advances to be madein the medical field of genetics research. However, due to the large amount of data that sequencers produce,new methods and programs are required to allow an efficient and rapid analysis of the data. MapReduce is adata-intensive computing model that handles large volumes that are easy to program by means of two basicfunctions (Map and Reduce). This work introduces GMS, a genetic mapping system that can assist doctors inthe clinical diagnosis of patients by conducting an analysis of the genetic mutations contained in their DNA.As a result, the model can offer a good method for analyzing the data generated by sequencers, by providing ascalable system that can handle a large amount of data. The use of several medical databases at the same timemakes it possible to determine susceptibilities to diseases through big data analysis mechanisms. The resultsshow scalability and offer a possible diagnosis that can improve the genetic diagnosis with a powerful tool forhealth professionals." @default.
- W2295984145 created "2016-06-24" @default.
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- W2295984145 date "2015-01-01" @default.
- W2295984145 modified "2023-09-23" @default.
- W2295984145 title "Genetic Mapping of Diseases through Big Data Techniques" @default.
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- W2295984145 doi "https://doi.org/10.5220/0005365402790286" @default.
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