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Robust Algorithm for Genome Sequence Short Read Error Correction Using Hadoop-Mapreduce

Thesis Info

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Author

Tahir, Muhammad

Program

PhD

Institute

Iqra University

City

Islamabad

Province

Islamabad

Country

Pakistan

Thesis Completing Year

2016

Thesis Completion Status

Completed

Subject

Applied Sciences

Language

English

Link

http://prr.hec.gov.pk/jspui/bitstream/123456789/2824/1/Muhammad_Tahir_Computer_Science_2016_Iqra_Univ_10.05.2016.pdf

Added

2021-02-17 19:49:13

Modified

2024-03-24 20:25:49

ARI ID

1676727106569

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Biological sequences consist of A C G and T in a DNA structure and contain vital information of living organisms. The development of computing technologies, especially NGS technologies have increased genomic data at a rapid rate. The increase in genomic data presents significant research challenges in bioinformatics, such as sequence alignment, short-reads error correction, phylogenetic inference, etc. Next-generation high-throughput sequencing technologies have opened new and thought-provoking research opportunities. In particular, Next-generation sequencers produce a massive amount of short-reads data in a single run. However, these large amounts of short-reads data produced are highly susceptible to errors, as compared to shotgun sequencing. Therefore, there is a peremptory demand to design fast and more accurate statistical and computational tools to analyze these data. This research presents a novel and robust algorithm called HaShRECA for genome sequence short reads error correction. The developed algorithm is based on a probabilistic model that analyzes the potential errors in reads and utilizes the Hadoop-MapReduce framework to speed up the computation processes. Experimental results show that HaShRECA is more accurate, as well as time and space efficient as compared to previous algorithms.
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۵-اين

۵-اين

"يَقُوْلُ الْاِنْسَانُ يَوْمَىِٕذٍ اَيْنَ الْمَفَرُّ"[[1]]

"اُس وقت یہی انسان کہے گاکہاں بھاگ کر جاؤں؟"۔



[[1]]     القرآن ، ۷۵: ۱۰۔

Factors Related to the Implementation of Evidenced-based Practice (EBP) of Nursing Staffing Levels in Hospitals: A Literature Review

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