Evidence map›Paper›PMID 29951084›Full record

ArticleFrontiers in genetics2018

Evolutionary Pattern and Large-Scale Architecture of Mutation Networks of 2009 A (H1N1) Influenza A Virus.

Chengmin Wang, Nan Lyu, Lingling Deng, Jing Wang, Wenwen Gu, Hua Ding, Yan Wu, Jing Luo, Liang Wang, Xueze Lyv and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

13 authors.

Chengmin WangKey Lab of Animal Ecology and Conservation Biology, National Research Center for Wildlife-Borne Diseases, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
Nan LyuKey Lab of Animal Ecology and Conservation Biology, National Research Center for Wildlife-Borne Diseases, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
Lingling DengKey Lab of Animal Ecology and Conservation Biology, National Research Center for Wildlife-Borne Diseases, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
Jing WangDepartment of Infectious Diseases, Hangzhou Center for Disease Control and Prevention, Hangzhou, China.
Wenwen GuDepartment of Infectious Diseases, Hangzhou Center for Disease Control and Prevention, Hangzhou, China.
Hua DingDepartment of Infectious Diseases, Hangzhou Center for Disease Control and Prevention, Hangzhou, China.
Yan WuDepartment of Infectious Diseases, Hangzhou Center for Disease Control and Prevention, Hangzhou, China.
Jing LuoKey Lab of Animal Ecology and Conservation Biology, National Research Center for Wildlife-Borne Diseases, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
Liang WangBeijing Animal Husbandry Station, Beijing, China.
Xueze LyvBeijing Animal Husbandry Station, Beijing, China.
Xiaodong LiuBeijing Animal Husbandry Station, Beijing, China.
Yi TaoKey Lab of Animal Ecology and Conservation Biology, National Research Center for Wildlife-Borne Diseases, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
Hongxuan HeKey Lab of Animal Ecology and Conservation Biology, National Research Center for Wildlife-Borne Diseases, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The adaptive evolution of influenza virus is an important question, but predicting its evolutionary future will be more challenging. Here, we investigated the mutation characteristic of influenza virus based on the complete genome data of 2009 (H1N1) influenza A virus. By assuming that evolution proceeds via the accumulation of mutations, we analyzed the mutation networks at four different time stages and found that the network structure follows the characteristics of a scale-free network. These results will be important for epidemiology and the future control of influenza viruses. Furthermore, we predicted the predominant mutation virus strain by using the early mutation network of influenza viruses, and this result was consistent with the WHO recommendation for the candidate vaccine of influenza virus. The key contribution of this study is that we explained the biological significance of this scale-free network for influenza pandemic and provided a potential method for predicting the candidate vaccine by using the early-stage network.

Indexed as

complete genomeevolutionary patternH1N1influenza A virusscale-free mutation network

Identifiers

PMID29951084
PMCPMC6008563

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Registered trials

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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.