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Published on Feb 1, 2016in Nature Nanotechnology 37.49
Stephanie J. Heerema5
Estimated H-index: 5
Cees Dekker81
Estimated H-index: 81
Fast, cheap, and reliable DNA sequencing could be one of the most disruptive innovations of this decade, as it will pave the way for personalized medicine. In pursuit of such technology, a variety of nanotechnology-based approaches have been explored and established, including sequencing with nanopores. Owing to its unique structure and properties, graphene provides interesting opportunities for the development of a new sequencing technology. In recent years, a wide r...
160 Citations Source Cite
Published on Oct 11, 2017in Nature 41.58
Jay Shendure89
Estimated H-index: 89
Shankar Balasubramanian54
Estimated H-index: 54
+ 4 AuthorsRobert H. Waterston75
Estimated H-index: 75
The history and future potential of DNA sequencing, including the development of the underlying technologies and the expansion of its areas of application, are reviewed.
47 Citations Source Cite
Published on Jul 8, 2018 in Intelligent Systems in Molecular Biology
Gryte Satas2
Estimated H-index: 2
(Brown University),
Benjamin J. Raphael41
Estimated H-index: 41
(Princeton University)
Motivation: Single-cell DNA sequencing is a promising technology that allows researchers to examine the genomic content of individual cells. Because the amount of DNA in a single cell is to o little to sequence directly, single-cell sequencing requires a method of whole-genome amplification (WGA). WGA introduces biases in the data, including high rates of allelic drop out and non-uniform coverage of the genome. These biases confound many downstream analyses, including...
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Published on Apr 1, 2017in Nature Methods 26.92
Jared T. Simpson31
Estimated H-index: 31
Rachael E. Workman5
Estimated H-index: 5
+ 3 AuthorsWinston Timp19
Estimated H-index: 19
A hidden Markov model (HMM)-based tool enables detection of 5-methylcytosine (5-mC) from single-molecule nanopore-sequencing data generated directly from human genomic DNA without chemical treatment.
69 Citations Source Cite
Published on Nov 1, 2012in Nature Biotechnology 35.72
Jay Shendure89
Estimated H-index: 89
(University of Washington),
Erez Lieberman Aiden13
Estimated H-index: 13
(Harvard University)
The cost of DNA sequencing has plummeted since 2005 (refs. 1,2), from $1,000 per megabase down to a mere ten cents per megabase3,4. Next-generation technologies have also commoditized high-throughput DNA sequencing and rendered it broadly accessible to individual investigators outside of genome centers3,5 (J.S. and colleagues). For many applications, the cost of sequencing is already negligible in comparison to the costs of sample acquisition, library preparati...
202 Citations Source Cite
Published on Oct 1, 2008in Nature Biotechnology 35.72
Jay Shendure89
Estimated H-index: 89
(University of Washington),
Hanlee P. Ji24
Estimated H-index: 24
(Stanford University)
DNA sequence represents a single format onto which a broad range of biological phenomena can be projected for high-throughput data collection. Over the past three years, massively parallel DNA sequencing platforms have become widely available, reducing the cost of DNA sequencing by over two orders of magnitude, and democratizing the field by putting the sequencing capacity of a major genome center in the hands of individual investigators. These new techn...
2,938 Citations Source Cite
Published on Jan 1, 2016in Briefings in Bioinformatics 6.30
David Laehnemann1
Estimated H-index: 1
Arndt Borkhardt45
Estimated H-index: 45
Alice C. McHardy40
Estimated H-index: 40
Characterizing the errors generated by common high-throughput sequencing platforms and telling true genetic variation from technical artefacts are two interdependent steps, essential to many analyses such as single nucleotide variant calling, haplotype inference, sequence assembly and evolutionary studies. Both random and systematic errors can show a specific occurrence profile for each of the six prominent sequencing platforms surveyed here: 454 pyrosequencing, Complete Genomics <...
93 Citations Source Cite
Published on Jan 1, 1990 in Foundations of Computer Science
Ming Li56
Estimated H-index: 56
(University of Waterloo)
Mathematical frameworks suitable for massive automated DNA sequencing and for analyzing DNA sequencing algorithms are studied under plausible assumptions. The DNA sequencing problem is modeled as learning a superstring from its randomly drawn substrings. Under certain restrictions, this may be viewed as learning a superstring in L.G. Valiant's (1984) learning model, and in this case the author gives an efficient algorithm for learning a superstring and a...
38 Citations Source Cite
Published on Oct 1, 2011in Nature Biotechnology 35.72
Michael J. Clark12
Estimated H-index: 12
(Stanford University),
Rui Chen18
Estimated H-index: 18
(Stanford University)
+ 5 AuthorsMichael Snyder130
Estimated H-index: 130
(Stanford University)
Capturing and sequencing only the coding regions of the human genome leverages resources in the pursuit of rare disease-causing mutations. Clark et al. compare the performance of three leading exome-capture methods and their advantages over whole-genome sequencing.
331 Citations Source Cite
Published on Apr 1, 2017in Nature Methods 26.92
Arthur C Rand5
Estimated H-index: 5
Miten Jain11
Estimated H-index: 11
+ 4 AuthorsBenedict Paten29
Estimated H-index: 29
A tool based on hidden Markov model and hierarchical Dirichlet process (HMM-HDP) can call two methylated cytosine variants and a methylated adenine variant directly from genomic DNA using nanopore sequencing data.
51 Citations Source Cite