Next-generation DNA sequencing technology, challenges and bioinformatics approaches for sequence alignment
Journal
ICT Innovations 2010, Web Proceedings
Date Issued
2010-09
Author(s)
Kocarev, Ljupcho
Abstract
The advent of high-throughput sequencing platforms brought
bioinformatics to a new level. This, so called ‘next-generation’ sequencing
technology opened the researching doors of every laboratory allowing
accomplishment of previously unimaginable scale and expensive experiments.
As a result, novel research areas have emerged providing huge amounts of new
data ready to be analyzed. Parallel to this progress, a variety of sequencing tools
designed for data analysis has been published. Sequence alignment takes the
central challenge in data analysis, providing primary representative results for
the experiments. Few alignment methods and diversity of tools have been
published and developed in the last years. The main goal of all these alignment
tools is to fit between performance and accuracy. In this review will be
presented the new NGS technologies and platforms, the current alignment
approaches applied in data analysis and described some commonly used
implementations of the methods.
bioinformatics to a new level. This, so called ‘next-generation’ sequencing
technology opened the researching doors of every laboratory allowing
accomplishment of previously unimaginable scale and expensive experiments.
As a result, novel research areas have emerged providing huge amounts of new
data ready to be analyzed. Parallel to this progress, a variety of sequencing tools
designed for data analysis has been published. Sequence alignment takes the
central challenge in data analysis, providing primary representative results for
the experiments. Few alignment methods and diversity of tools have been
published and developed in the last years. The main goal of all these alignment
tools is to fit between performance and accuracy. In this review will be
presented the new NGS technologies and platforms, the current alignment
approaches applied in data analysis and described some commonly used
implementations of the methods.
Subjects
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