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Next-generation sequencing transforms today's biology
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Cites
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Evaluation of next generation sequencing platforms for population targeted sequencing studies
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CNV-seq, a new method to detect copy number variation using high-throughput sequencing
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The impact of next-generation sequencing on genomics
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“NGS technologies have increased the speed and throughput capacities of DNA sequencing and, as a result, dramatically reduced overall sequencing costs (Mardis, 2006, 2009; Schuster, 2008; Shendure and Ji, 2008; Ng et al., 2009a; Tucker et al., 2009; Metzker, 2010).”
BackgroundAssembly of large genomes using second-generation sequencing
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The insula: an underestimated brain area in clinical neuroscience, psychiatry, and neurology
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“Over the past several years, the next generation sequencing technology has emerged as a cutting edge approach for high-throughput sequence determination and this has dramatically improved the efficiency and speed of gene discovery [16,17].”
BackgroundOptimization of de novo transcriptome assembly from next-generation sequencing data
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Transposases are the most abundant, most ubiquitous genes in nature
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“Next-generation-sequencing (NGS) has revolutionized the field of genomics [1,2] since its recent appearance [3] because of its much higher data throughput, thus much lower cost, and the much faster speed compared with traditional Sanger sequencing [4].”
BackgroundApplication of 'next-generation' sequencing technologies to microbial genetics
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Unlocking short read sequencing for metagenomics
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Comparative studies of de novo assembly tools for next-generation sequencing technologies
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Opportunities and challenges of real-time release testing in biopharmaceutical manufacturing
Jiang, M., Severson, K. A., Love, J. C., Madden, H., Swann, P., Zang, L., & Braatz, R. D. (2017) · Biotechnology and Bioengineering · doi:10.1002/bit.26383 · Cited by 118
Translational Aspects of the Human Respiratory Virome
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Microbiome depiction through user-adapted bioinformatic pipelines and parameters
Nayman, E. I., Schwartz, B. A., Polanco, F. C., Firek, A. K., Gumabong, A. C., Hofstee, N. J., Narasimhan, G., Cickovski, T., & Mathee, K. (2023) · Journal of Medical Microbiology · doi:10.1099/jmm.0.001756 · Cited by 6
Metadata
- Authors
- Schuster, S. C.
- Venue
- Nature Methods
- Published
- 2007-12-19
- Volume
- 5
- Issue
- 1
- Pages
- 16-18
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- OpenAlex
- W2005129098
- Cited by
- 1,807
- References
- 3
- FWCI
- 24.19
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
