Evidence map›Paper›PMID 23340846›Full record

ReviewMolecular systems biology2013

High-throughput sequencing for biology and medicine.

Wendy Weijia Soon, Manoj Hariharan, Michael P Snyder

Abstract readReview
In one paragraph

Review in Molecular systems biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 127 papers.

0numbers the graph read from it
0cells of the map it votes in
127citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

127 citing papers in PubMed.

  1. Article
  2. Article
  3. A novel biological function-based method for mining core genes in rare disease with limited cases.Mammalian genome : official journal of the International Mammalian Genome Society · 2026
    Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Enhancer regulation in cancer: from epigenetics to mArchives of pharmacal research · 2025
    Review
  10. Review
  11. Article
  12. Article
  13. Review
  14. Article
  15. The Evolution of Next-Generation Sequencing Technologies.Methods in molecular biology (Clifton, N.J.) · 2025
    Review
  16. Article
  17. Article
  18. Review
  19. Article
  20. Review

67 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Wendy Weijia SoonDepartment of Genetics, Stanford University School of Medicine, Alway Building, 300 Pasteur Drive, Stanford, CA 94305, USA.
Manoj Hariharan
Michael P Snyder

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Advances in genome sequencing have progressed at a rapid pace, with increased throughput accompanied by plunging costs. But these advances go far beyond faster and cheaper. High-throughput sequencing technologies are now routinely being applied to a wide range of important topics in biology and medicine, often allowing researchers to address important biological questions that were not possible before. In this review, we discuss these innovative new approaches-including ever finer analyses of transcriptome dynamics, genome structure and genomic variation-and provide an overview of the new insights into complex biological systems catalyzed by these technologies. We also assess the impact of genotyping, genome sequencing and personal omics profiling on medical applications, including diagnosis and disease monitoring. Finally, we review recent developments in single-cell sequencing, and conclude with a discussion of possible future advances and obstacles for sequencing in biology and health.

Indexed as

GenomeBiomedical ResearchEpigenomicsGene Expression ProfilingGenetic VariationHigh-Throughput Nucleotide SequencingHistonesHumansSingle-Cell AnalysisHistones

Identifiers

PMID23340846
PMCPMC3564260

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.