High‐throughput DNA sequencing – concepts and limitations
By Martin Kircher, Janet Kelso. Bioessays, 2010
644 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/ceef556d19bb34032e4014f24dd9cb33c7d1b7ea
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In Artificial Intelligence
In Molecular Biology
- S. Sawyer
- Lior S. Pachter
- M. Meyer
- Martin Kircher
- Cole Trapnell
- Johannes Rinn
- M. Esteban
- Harry Guy Hornsby
Citations in the corpus
- Improving RNA-Seq expression estimates by correcting for fragment bias (2011, background): “RNA-Seq technology is changing rapidly, and this is evident in the development of numerous preparation protocols (for a recent review see [11]) and increasingly longer read lengths from sequencing machines [12].”
- SNP Discovery through Next-Generation Sequencing and Its Applications (2012, background): “In the last decade, new sequencing technologies have outperformed Sanger-based sequencing in throughput and overall cost, if not quite in sequence length and error rate [23].”
- An Overview of the Immunological Defenses in Fish Skin (2012, background): “NGS is revolutionizing the approaches taken to study both transcriptomics and genomics, due to the massive amount of sequence information that can be generated in a relatively short length of time [363].”
- Current trends in microsatellite genotyping (2011, background): “Such limitations should no longer be an issue because 454 technologies delivering >400 bp reads have now become available (Schuster 2008; Kircher & Kelso 2010).”
- Applications of next-generation sequencing to the study of biological invasions (2015, background): “…Sequencing First-generation, or Sanger sequencing (Sanger et al., 1977), was widely used during the 1980s and 1990s, but has been superseded in terms of output by NGS, with the daily throughput of NGS being 100–100,000 times higher than Sanger sequencing (Kircher and Kelso, 2010; Metzker, 2010).”
- Double indexing overcomes inaccuracies in multiplex sequencing on the Illumina platform (2011, methodology): “Sequences from this library are usually used to train the Ibis base caller (25) and to obtain measures of run quality for comparing different experiments.”