Evidence map›Paper›PMID 36806894›Full record

ArticleBriefings in bioinformatics2023

FungiExpresZ: an intuitive package for fungal gene expression data analysis, visualization and discovery.

Chirag Parsania, Ruiwen Chen, Pooja Sethiya, Zhengqiang Miao, Liguo Dong, Koon Ho Wong

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Article in Briefings in bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Applied and environmental microbiology · 2026
    Article
  3. Article
  4. Article
  5. MTD: A cloud-based omics database and interactive platform forSynthetic and systems biotechnology · 2025
    Article
  6. Intrinsically Disordered Regions Define Unique Protein Interaction Networks in CHD Family Remodelers.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2025
    Article
  7. AFED, a comprehensive resource for Aspergillus flavus gene expression profiling.Database : the journal of biological databases and curation · 2025
    Article
  8. Article
  9. Article
  10. 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

6 authors.

Chirag ParsaniaFaculty of Health Sciences, University of Macau, Macau SAR of China.ORCID 0000-0003-4873-2385
Ruiwen ChenFaculty of Health Sciences, University of Macau, Macau SAR of China.ORCID 0000-0001-8780-1078
Pooja SethiyaFaculty of Health Sciences, University of Macau, Macau SAR of China.ORCID 0000-0001-6584-3912
Zhengqiang MiaoFaculty of Health Sciences, University of Macau, Macau SAR of China.
Liguo DongFaculty of Health Sciences, University of Macau, Macau SAR of China.ORCID 0000-0002-8805-7487
Koon Ho WongFaculty of Health Sciences, University of Macau, Macau SAR of China.ORCID 0000-0002-9264-5118

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bioinformatics analysis and visualization of high-throughput gene expression data require extensive computer programming skills, posing a bottleneck for many wet-lab scientists. In this work, we present an intuitive user-friendly platform for gene expression data analysis and visualization called FungiExpresZ. FungiExpresZ aims to help wet-lab scientists with little to no knowledge of computer programming to become self-reliant in bioinformatics analysis and generating publication-ready figures. The platform contains many commonly used data analysis tools and an extensive collection of pre-processed public ribonucleic acid sequencing (RNA-seq) datasets of many fungal species, including important human, plant and insect pathogens. Users may analyse their data alone or in combination with public RNA-seq data for an integrated analysis. The FungiExpresZ platform helps wet-lab scientists to overcome their limitations in genomics data analysis and can be applied to analyse data of any organism. FungiExpresZ is available as an online web-based tool (https://cparsania.shinyapps.io/FungiExpresZ/) and an offline R-Shiny package (https://github.com/cparsania/FungiExpresZ).

Indexed as

GenomicsSoftwareData AnalysisGene ExpressionGene Expression ProfilingHumansRNARNAbioinformatics tooldata analysisdata visualizationfungiFungiExpresZRNA-seq database

Identifiers

PMID36806894
PMCPMC10025439

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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.