Evidence map›Paper›PMID 33110420›Full record

ArticleFrontiers in genetics2020

MDACP: A Pathogen Genome and Metagenome Analysis Cloud Platform.

Na Han, Jiaojiao Miao, Tingting Zhang, Yujun Qiang, Xianhui Peng, Xiuwen Li, Wen Zhang

Abstract read
In one paragraph

Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Na HanState Key Laboratory for Infectious Disease Prevention and Control, Chinese Center for Disease Control and Prevention, National Institute for Communicable Disease Control and Prevention, Beijing, China.
Jiaojiao MiaoState Key Laboratory for Infectious Disease Prevention and Control, Chinese Center for Disease Control and Prevention, National Institute for Communicable Disease Control and Prevention, Beijing, China.
Tingting ZhangState Key Laboratory for Infectious Disease Prevention and Control, Chinese Center for Disease Control and Prevention, National Institute for Communicable Disease Control and Prevention, Beijing, China.
Yujun QiangState Key Laboratory for Infectious Disease Prevention and Control, Chinese Center for Disease Control and Prevention, National Institute for Communicable Disease Control and Prevention, Beijing, China.
Xianhui PengState Key Laboratory for Infectious Disease Prevention and Control, Chinese Center for Disease Control and Prevention, National Institute for Communicable Disease Control and Prevention, Beijing, China.
Xiuwen LiState Key Laboratory for Infectious Disease Prevention and Control, Chinese Center for Disease Control and Prevention, National Institute for Communicable Disease Control and Prevention, Beijing, China.
Wen ZhangState Key Laboratory for Infectious Disease Prevention and Control, Chinese Center for Disease Control and Prevention, National Institute for Communicable Disease Control and Prevention, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pathogenic microorganism analysis based on next-generation sequencing technology is an important tool for clinical diagnosis, public health surveillance, and outbreak investigation. However, scientific researchers without the relevant background lack the time, training, or infrastructure to use large data sets or install and use command line tools. Therefore, the bioinformatic team at the Chinese Center for Disease Control and Prevention developed the Microbial Data Analysis Cloud Platform (MDACP) as a safe, professional, and efficient pathogen genetic data analysis platform for rapid microbial data mining, such as for candidate pathogen detection, genome typing, and traceability. MDACP is a web service system based on the Docker platform and can be used for data analysis on various operating systems. The platform focuses on pathogen analysis and continuously develops new analysis processes according to the analysis needs of the users. This platform has a friendly user interface and is easy to operate, allowing users to submit data through data pages or graphical clients, flexibly control parameters according to data conditions, and analyze data in parallel with multiple tasks. Researchers can quickly carry out bioinformatic analyses without coding work, promote follow-up research and information mining of projects, and improve the utilization of big data in the field of disease control. MDACP enables research personnel to conduct data analysis and management and assists clinicians and disease control personnel with mining information, such as pathogen identification, classification, and traceability.

Indexed as

analysis cloud platformgenomemicroorganismpathogenweb resource

Identifiers

PMID33110420
PMCPMC7489492

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.