Evidence map›Paper›PMID 27698619›Full record

ReviewThe Yale journal of biology and medicine2016

Metagenomic Assembly: Overview, Challenges and Applications.

Jay S Ghurye, Victoria Cepeda-Espinoza, Mihai Pop

Abstract readReview
In one paragraph

Review in The Yale journal of biology and medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 86 papers.

0numbers the graph read from it
0cells of the map it votes in
86citing 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

86 citing papers in PubMed.

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  17. Targeted whole-genome recovery of single viral species in a complex environmental sample.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
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26 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.

Jay S GhuryeDepartment of Computer Science and Center of Bioinformatics and Computational Biology, University of Maryland.
Victoria Cepeda-EspinozaDepartment of Computer Science and Center of Bioinformatics and Computational Biology, University of Maryland.
Mihai PopDepartment of Computer Science and Center of Bioinformatics and Computational Biology, University of Maryland.

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

Advances in sequencing technologies have led to the increased use of high throughput sequencing in characterizing the microbial communities associated with our bodies and our environment. Critical to the analysis of the resulting data are sequence assembly algorithms able to reconstruct genes and organisms from complex mixtures. Metagenomic assembly involves new computational challenges due to the specific characteristics of the metagenomic data. In this survey, we focus on major algorithmic approaches for genome and metagenome assembly, and discuss the new challenges and opportunities afforded by this new field. We also review several applications of metagenome assembly in addressing interesting biological problems.

Indexed as

AlgorithmsAnimalsHumansMetagenomeMetagenomicsSequence Analysis, DNAAssemblyMetagenomicsMicrobiome

Identifiers

PMID27698619
PMCPMC5045144

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.