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It is a time efficient algorithm for low-density noise.
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The development of time-efficient algorithms for this problem is, therefore, crucial for successful real-world applications.
Historically, suffix trees received much attention because time-efficient algorithms for their construction and use were developed early [ 1].
Therefore, to harvest the benefits of utilizing NGS technology, the development of space- and time-efficient algorithms to complete the assembly process has become inevitable.
Here we present version 2.0 of the khmer software package, a high-performance library implementing memory- and time-efficient algorithms for the manipulation and analysis of short-read data sets.
Polynomial time algorithms to find good approximate solutions to either problem most likely do not exist (under certain complexity assumptions), but a time efficient approximation algorithm is shown that solves a special case of these problems.
Furthermore, we show that the string graph can be constructed directly using the FM-index without the need for explicitly finding all overlaps and a subsequent transitive removal step, yielding a space and time efficient construction algorithm.
We thus computed a task-dependent index I task) that represents task by task the average execution time of efficient algorithms with bounded memory.
This paper presents a memory and time efficient string matching algorithm specifically designed for NIMS on commodity processors.
At the same time, they construct an efficient algorithm for the computation of the clearing vector.
It is investigated when the limits for t-ratio are computable in polynomial time and a new efficient algorithm is designed for this case.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com