Evidence map›Paper›PMID 31166948›Full record

ReviewPLoS computational biology2019

Modern technologies and algorithms for scaffolding assembled genomes.

Jay Ghurye, Mihai Pop

Abstract readReview
In one paragraph

Review in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

  1. Benchmarking of bioinformatics tools for the hybridComputational and structural biotechnology journal · 2025
    Article
  2. The Bioinformatic Applications of Hi-C and Linked Reads.Genomics, proteomics & bioinformatics · 2024
    Review
  3. Article
  4. Chromosome-Scale Genome Assembly of the Sheep-Biting LouseInternational journal of molecular sciences · 2024
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Integrating Genetic and Chromosome Maps ofInternational journal of molecular sciences · 2022
    Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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

2 authors.

Jay GhuryeDepartment of Computer Science and Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, United States of America.ORCID 0000-0003-1381-4081
Mihai PopDepartment of Computer Science and Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, United States of America.ORCID 0000-0001-9617-5304

Funding

Algorithms and Software for the Assembly of Metagenomic DataR01AI100947 · NIAID · UNIV OF MARYLAND, COLLEGE PARK · PI POP, MIHAI · 2013 to 2025
$7.4M
NIAID NIH HHS R01 AI100947
6 · The paper itself

Abstract

The computational reconstruction of genome sequences from shotgun sequencing data has been greatly simplified by the advent of sequencing technologies that generate long reads. In the case of relatively small genomes (e.g., bacterial or viral), complete genome sequences can frequently be reconstructed computationally without the need for further experiments. However, large and complex genomes, such as those of most animals and plants, continue to pose significant challenges. In such genomes, assembly software produces incomplete and fragmented reconstructions that require additional experimentally derived information and manual intervention in order to reconstruct individual chromosome arms. Recent technologies originally designed to capture chromatin structure have been shown to effectively complement sequencing data, leading to much more contiguous reconstructions of genomes than previously possible. Here, we survey these technologies and the algorithms used to assemble and analyze large eukaryotic genomes, placed within the historical context of genome scaffolding technologies that have been in existence since the dawn of the genomic era.

Indexed as

AlgorithmsChromosome MappingGenome, HumanGenomicsHumansSequence AlignmentSequence Analysis, DNA

Identifiers

PMID31166948
PMCPMC6550390

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.