Next-generation sequencing transforms today's biology

By Stephan C. Schuster. Nature Methods, 2008

1,783 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/2449e1d56a843cb6e280852d787143479d776ce6

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Citations in the corpus

Next‐generation sequencing technologies for environmental DNA research (2012, background): “Although this late amplification step is carried out with universal probes and can be considered bias-free amplification, it can exaggerate biased amplification in the original amplicon library preparation (Schuster 2008).”
The Utility of Single Nucleotide Polymorphism (SNP) Data in Phylogenetics (2017, neutral): “…of data during collection or postprocessing Coverage: the number of reads that include a given nucleotide in the reconstructed sequence researchers acquire SNPs, and thus scale up to genome-wide data, for studies that were typically conducted using conventional DNA sequencing (Schuster 2007).”
Big Data Application in Biomedical Research and Health Care: A Literature Review (2016, background): “27,28 The role of big data techniques in bioinformatics applications is to provide data repositories, computing infrastructure, and efficient data manipulation tools for investigators to gather and analyze biological information.”
Comprehending crystalline β-carotene accumulation by comparing engineered cell models and the natural carotenoid-rich system of citrus (2011, positive): “The experimental design and field management were the same as described by Zou et al. (2011).”
Noninvasive prenatal diagnosis of fetal chromosomal aneuploidy by massively parallel genomic sequencing of DNA in maternal plasma (2008, background): “We previously (15) proposed that the recently available massively parallel genomic sequencing (MPGS) platforms (16, 17) might be adaptable as an approach to quantify DNA sequences for the noninvasive prenatal diagnosis of fetal chromosomal aneuploidy.”
Non-invasive prenatal assessment of trisomy 21 by multiplexed maternal plasma DNA sequencing: large scale validity study (2011, background): “This technique can identify and quantify millions of DNA fragments in biological samples in a span of days.”
An Extensive Evaluation of Read Trimming Effects on Illumina NGS Data Analysis (2013, background): “In particular, the usage of Illumina (formerly known as Solexa) reads is nowadays the basis for a series of biological applications, both in diagnostic and research fields [1,2].”
High‐throughput DNA sequencing – concepts and limitations (2010, background): “To reflect these huge changes, several companies, researchers, and recent reviews [19–24] use the term ‘‘next-generation sequencing’’”
CNV-seq, a new method to detect copy number variation using high-throughput sequencing (2009, background): “Today, the next-generation sequencing technologies are transforming biology research [7].”
Performance of genetic programming optimised Bowtie2 on genome comparison and analytic testing (GCAT) benchmarks (2015, background): “Although NGS DNA scanners can generate in the region of a billion DNA sequences per run, each sequence is only a few hundred base pairs (bp) long [2].”
Applications of next generation sequencing in molecular ecology of non-model organisms (2011, background): “The future bottlenecks are more likely to be at the bioinformatics end rather than in producing the sequences (Schuster, 2008).”
DNA barcoding for ecologists. (2009, background): “yield a typical read length of 500–1000 bp. Recently, next-generation sequencing systems have become available [85, 86 ].”
Evaluation of next generation sequencing platforms for population targeted sequencing studies (2009, methodology): “Genome Biology 2009, 10:R32 method on the ABI 3730xL platform (hereafter referred to as ABI Sanger) [ 2-4 ].”
baySeq: Empirical Bayesian methods for identifying differential expression in sequence count data (2010, background): “The development of high-throughput sequencing technologies in recent years [1-4] has led to a massive increase in genomic data represented by counts.”
Domestication evolution, genetics and genomics in wheat (2011, background): “The available crop genome sequences and the current sequencing of the wheat genome can transform today’s biology (Schuster 2008), dramatically advancing both the theory and application of wheat domestication studies.”