Evidence map›Paper›PMID 31824565›Full record

ArticleFrontiers in genetics2019

Reads Binning Improves Alignment-Free Metagenome Comparison.

Kai Song, Jie Ren, Fengzhu Sun

Abstract read
In one paragraph

Article in Frontiers in genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. A review of neural networks for metagenomic binning.Briefings in bioinformatics · 2025
    Review
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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.

Kai SongSchool of Mathematics and Statistics, Qingdao University, Qingdao, China.
Jie RenQuantitative and Computational Biology Program, University of Southern California, Los Angeles, CA, United States.
Fengzhu SunQuantitative and Computational Biology Program, University of Southern California, Los Angeles, CA, United States.

Funding

Computational Studies of Virus-host Interactions Using Metagenomics Data and ApplicationsR01GM120624 · NIGMS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI AHLGREN, NATHAN, SUN, FENGZHU · 2017 to 2020
$1.7M
NIGMS NIH HHS R01 GM120624
6 · The paper itself

Abstract

Comparing metagenomic samples is a critical step in understanding the relationships among microbial communities. Recently, next-generation sequencing (NGS) technologies have produced a massive amount of short reads data for microbial communities from different environments. The assembly of these short reads can, however, be time-consuming and challenging. In addition, alignment-based methods for metagenome comparison are limited by incomplete genome and/or pathway databases. In contrast, alignment-free methods for metagenome comparison do not depend on the completeness of genome or pathway databases. Still, the existing alignment-free methods,

Indexed as

alignment-free methodsbeta-diversityMarkov modelmetagenomic samplesreads binning

Identifiers

PMID31824565
PMCPMC6881972

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.