Parallel algorithm for indexing large DNA sequences using MapReduce on Hadoop
F Kaniwa, O Dinakenyane… - 2017 IEEE International …, 2017 - ieeexplore.ieee.org
2017 IEEE International Conference on Bioinformatics and …, 2017•ieeexplore.ieee.org
MapReduce has recently become very successful parallel processing technique. Latest
DNA sequencing technologies are now able to generate huge DNA sequences easily and
cheaper. Consequently making it a challenge for single-core processor systems to mine
patterns, hence leading to unsatisfactory performance. In this paper, we explore this
challenge by making use of MapReduce on Hadoop platform using a successful data
structure called the generalized suffix tree. Our experimental results show that the proposed …
DNA sequencing technologies are now able to generate huge DNA sequences easily and
cheaper. Consequently making it a challenge for single-core processor systems to mine
patterns, hence leading to unsatisfactory performance. In this paper, we explore this
challenge by making use of MapReduce on Hadoop platform using a successful data
structure called the generalized suffix tree. Our experimental results show that the proposed …
MapReduce has recently become very successful parallel processing technique. Latest DNA sequencing technologies are now able to generate huge DNA sequences easily and cheaper. Consequently making it a challenge for single-core processor systems to mine patterns, hence leading to unsatisfactory performance. In this paper, we explore this challenge by making use of MapReduce on Hadoop platform using a successful data structure called the generalized suffix tree. Our experimental results show that the proposed approach can index long sequences with improved performance than previous related approaches.
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