%0 Journal Article %1 noauthororeditor %A R, Indumathy %D 2012 %J International Journal on Bioinformatics & Biosciences (IJBB) %K Biology Computational Genome Human Optimization Problem Project %N Number 2 %R 10.5121/ijbb.2012.2205 %T NATURE INSPIRED ALGORITHMS TO SOLVE DNA FRAGMENT ASSEMBLY PROBLEM: A SURVEY %U https://wireilla.com/papers/ijbb/V2N2/2212ijbb05.pdf %V Volume 2 %X Evolutionary search algorithms are becoming an essential advantage in the algorithmic toolbox for solving multi-dimensional optimization problems in a wide range of bioinformatics problems such as Genome fragment assembly which is a NP-hard problem. In computational biology, one of the most challenging problems is to reconstruct the original DNA sequence from a huge number of fragments, each one being numerous hundred base-pairs (bps) long. Recently it has become common for the researchers to apply the heuristic search algorithms to solve these kinds of complex problems with the help of combinatorial optimization. A genetic algorithm, the most well-known and representative evolutionary search technique has been the subject of the major part of such applications. Despite the fact that there have been different methods available in the literature, researchers are still facing difficulties in choosing the best method that could solve these problems efficiently and effectively. This paper aims to analyses the existing algorithms, evaluate them, point out the faults of these works and specify the emerging tren

@article{noauthororeditor, abstract = {Evolutionary search algorithms are becoming an essential advantage in the algorithmic toolbox for solving multi-dimensional optimization problems in a wide range of bioinformatics problems such as Genome fragment assembly which is a NP-hard problem. In computational biology, one of the most challenging problems is to reconstruct the original DNA sequence from a huge number of fragments, each one being numerous hundred base-pairs (bps) long. Recently it has become common for the researchers to apply the heuristic search algorithms to solve these kinds of complex problems with the help of combinatorial optimization. A genetic algorithm, the most well-known and representative evolutionary search technique has been the subject of the major part of such applications. Despite the fact that there have been different methods available in the literature, researchers are still facing difficulties in choosing the best method that could solve these problems efficiently and effectively. This paper aims to analyses the existing algorithms, evaluate them, point out the faults of these works and specify the emerging tren}, added-at = {2018-10-10T07:03:54.000+0200}, author = {R, Indumathy}, biburl = {https://www.bibsonomy.org/bibtex/24bde587e271eb62a5d59723a546dffac/jack-12}, doi = {10.5121/ijbb.2012.2205}, interhash = {b50ae16def590024b25850a366aa89b3}, intrahash = {4bde587e271eb62a5d59723a546dffac}, issn = {1839-9614}, journal = {International Journal on Bioinformatics & Biosciences (IJBB)}, keywords = {Biology Computational Genome Human Optimization Problem Project}, language = {english}, month = {June}, number = { Number 2}, timestamp = {2018-10-10T07:03:54.000+0200}, title = {NATURE INSPIRED ALGORITHMS TO SOLVE DNA FRAGMENT ASSEMBLY PROBLEM: A SURVEY}, url = {https://wireilla.com/papers/ijbb/V2N2/2212ijbb05.pdf}, volume = {Volume 2}, year = 2012 }