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Computers, Volume 6, Issue 4 (December 2017)

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Research

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Open AccessArticle Application of Machine Learning Models in Error and Variant Detection in High-Variation Genomics Datasets
Computers 2017, 6(4), 29; doi:10.3390/computers6040029
Received: 7 October 2017 / Revised: 5 November 2017 / Accepted: 7 November 2017 / Published: 10 November 2017
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Abstract
For metagenomics datasets, datasets of complex polyploid genomes, and other high-variation genomics datasets, there are difficulties with the analysis, error detection and variant calling, stemming from the challenges of discerning sequencing errors from biological variation. Confirming base candidates with high frequency of occurrence
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For metagenomics datasets, datasets of complex polyploid genomes, and other high-variation genomics datasets, there are difficulties with the analysis, error detection and variant calling, stemming from the challenges of discerning sequencing errors from biological variation. Confirming base candidates with high frequency of occurrence is no longer a reliable measure because of the natural variation and the presence of rare bases. The paper discusses an approach to the application of machine learning models to classify bases into erroneous and rare variations after preselecting potential error candidates with a weighted frequency measure, which aims to focus on unexpected variations by using the inter-sequence pairwise similarity. Different similarity measures are used to account for different types of datasets. Four machine learning models are implemented and tested. Full article
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Review

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Open AccessFeature PaperReview 3D NAND Flash Based on Planar Cells
Computers 2017, 6(4), 28; doi:10.3390/computers6040028
Received: 28 July 2017 / Revised: 17 September 2017 / Accepted: 27 September 2017 / Published: 24 October 2017
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Abstract
In this article, the transition from 2D NAND to 3D NAND is first addressed, and the various 3D NAND architectures are compared. The article carries out a comparison of 3D NAND architectures that are based on a “punch-and-plug” process—with gate-all-around (GAA) cell devices—against
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In this article, the transition from 2D NAND to 3D NAND is first addressed, and the various 3D NAND architectures are compared. The article carries out a comparison of 3D NAND architectures that are based on a “punch-and-plug” process—with gate-all-around (GAA) cell devices—against architectures that are based on planar cell devices. The differences and similarities between the two classes of architectures are highlighted. The differences between architectures using floating-gate (FG) and charge-trap (CT) devices are also considered. Although the current production of 3D NAND is based on GAA cell devices, it is suggested that architectures with planar cell devices could also be viable for mass production. Full article
(This article belongs to the Special Issue 3D Flash Memories)
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