Evidence map›Paper›PMID 37881319›Full record

ArticlePhenomics (Cham, Switzerland)2023

Mycobacteriaceae Phenome Atlas (MPA): A Standardized Atlas for the Mycobacteriaceae Phenome Based on Heterogeneous Sources.

Wan Liu, Hui Cen, Zhile Wu, Haokui Zhou, Shuo Chen, Xilan Yang, Guoping Zhao, Guoqing Zhang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Phenomics (Cham, Switzerland), 2023. 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

8 authors.

Wan Liu *National Genomics Data Center & Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031 China.ORCID 0000-0002-3638-1461
Hui Cen *National Genomics Data Center & Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031 China.ORCID 0000-0002-2699-1362
Zhile Wu *National Genomics Data Center & Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031 China.ORCID 0000-0002-8975-5471
Haokui ZhouInstitute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055 China.ORCID 0000-0002-6931-3377
Shuo ChenInstitute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055 China.ORCID 0000-0001-7693-4473
Xilan YangInstitute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055 China.ORCID 0000-0002-5444-2969
Guoping Zhao *National Genomics Data Center & Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031 China.ORCID 0000-0002-7621-6620
Guoqing Zhang *National Genomics Data Center & Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031 China.ORCID 0000-0001-8827-7546

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The bacterial family Mycobacteriaceae includes pathogenic and nonpathogenic bacteria, and systematic research on their genome and phenome can give comprehensive perspectives for exploring their disease mechanism. In this study, the phenotypes of Mycobacteriaceae were inferred from available phenomic data, and 82 microbial phenotypic traits were recruited as data elements of the microbial phenome. This Mycobacteriaceae phenome contains five categories and 20 subcategories of polyphasic phenotypes, and three categories and eight subcategories of functional phenotypes, all of which are complementary to the existing data standards of microbial phenotypes. The phenomic data of Mycobacteriaceae strains were compiled by literature mining, third-party database integration, and bioinformatics annotation. The phenotypes were searchable and comparable from the website of the Mycobacteriaceae Phenome Atlas (MPA, https://www.biosino.org/mpa/). A topological data analysis of MPA revealed the co-evolution between Supplementary Information: The online version contains supplementary material available at 10.1007/s43657-023-00101-5.

Indexed as

Co-evolutionData elementsMycobacteriaceae phenomePathogenicity

Identifiers

PMID37881319
PMCPMC10593683

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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.