| Summary: | The advancement of DNA assembly techniques has greatly boosted up the bioinformatics research and discovery. More precisely, DNA assembly has achieved tremendous popularity due to the ability to decode the hidden information in the DNA. DNA assembly is the process of finding the correct sequence of the nucleotide bases in DNA. The key challenges are a) size of the genomic data and, b) time to process the genomic data. Apparently, genomic data are voluminous consisting of many repeated fragments. The huge sized genomic data makes the DNA assembling a time consuming process. To address the space and time complexity, bloom filter is deployed in DNA assembling. Moreover, bloom filter plays a vital role in DNA processing to deal with the repeated data of DNA. A bloom filter is a probabilistic data structure for membership filter. Bloom filter uses a tiny amount of memory size to store information on the genomic data. However, DNA assembling is a very memory-intensive process. The whole process consists of many stages. In every stage, the repeated data need to be taken care of. Hence, bloom filter is deployed in every stage for its implementation. This paper presents the impact of bloom filter in DNA assembling process. It also gives a precise explanation on every aspect of the DNA assembling process. The focus of this paper is to review the techniques that implemented bloom filter.
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