Evidence map›Paper›PMID 37848628›Full record

ReviewCurrent microbiology2023

Current Fungal Taxonomy and Developments in the Identification System.

Pei Lin, MooChang Kook, Tae-Hoo Yi, Zheng-Fei Yan

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current microbiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Diversity ofJournal of fungi (Basel, Switzerland) · 2025
    Article
  3. Article
  4. 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

4 authors.

Pei LinSchool of Life Sciences and Health Engineering, Jiangnan University, Wuxi, Jiangsu Province, People's Republic of China.
MooChang KookCollege of Life Science, Kyung Hee University Global Campus, Yongin-si, Gyeonggi-do, Republic of Korea.
Tae-Hoo YiDepartment of Food & Nutrition, Baewha Women's University, Seoul, Republic of Korea.
Zheng-Fei YanState Key Laboratory of Food Science and Resources, Jiangnan University, 1800 Lihu Avenue, Wuxi, 214122, Jiangsu Province, People's Republic of China. zhengfeiyan@jiangnan.edu.cn.ORCID http://orcid.org/0000-0003-2102-6106

Funding

Industrial Infrastructure Program for Fundamental Technologies, Ministry of Trade, Industry & Energy (MOTIE), Korea N0000888
6 · The paper itself

Abstract

A functional identification system is the core and basis of fungal taxonomy, which provides sufficient diagnostic characteristics for species delimitation. Phenotype-based identification systems have exhibited significant drawbacks, such as being laborious and time-consuming. Thus, a molecular-based identification system (rDNA, DNA fingerprint, etc.) is proposed for application to fungi that lack reliable morphological characteristics. High Throughput Sequencing also makes great contributions to fungal taxonomy. However, the formal naming of nonculturable fungi from environmental sequencing is a significant challenge. Biochemical profile-based identification systems have outstanding value in fungal taxonomy and can occasionally be indispensable. This method utilizes biomarker metabolites and proteins that are expected to be unequivocal and stable. Of these, Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry has become the method of choice for chemotaxonomy. In sum, these described identification systems cannot solve all problems of species delimitation, and considerable attention to the updating of fungal nomenclature, standardization of techniques, knowledge sharing, and dissemination will be necessary.

Indexed as

FungiDNA, RibosomalPhenotypePhylogenySpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationDNA, Ribosomal

Identifiers

What OpenQuestion holds

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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.