Evidence map›Paper›PMID 35546367›Full record

ReviewApplied microbiology and biotechnology2022

Fungal secondary metabolites in food and pharmaceuticals in the era of multi-omics.

Akshay Shankar, Krishna Kant Sharma

Abstract readReview
In one paragraph

Review in Applied microbiology and biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing 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

42 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
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  6. Article
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  9. Review
  10. Article
  11. Unraveling bioactive potential and production inChinese herbal medicines · 2025
    Review
  12. Review
  13. Review
  14. Review
  15. Improving the Proteome-Mining ofJournal of fungi (Basel, Switzerland) · 2025
    Article
  16. Multi-omics analysis ofFrontiers in microbiology · 2025
    Article
  17. Article
  18. Review
  19. Article
  20. Review
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

2 authors.

Akshay ShankarLaboratory of Enzymology and Recombinant DNA Technology, Department of Microbiology, Maharshi Dayanand University, Rohtak, 124001, Haryana, India.
Krishna Kant SharmaLaboratory of Enzymology and Recombinant DNA Technology, Department of Microbiology, Maharshi Dayanand University, Rohtak, 124001, Haryana, India. kekulsharma@gmail.com.ORCID http://orcid.org/0000-0001-9576-342X

Funding

DST-FIST 1196SR/FST/LS-I/2017/4
6 · The paper itself

Abstract

Fungi produce several bioactive metabolites, pigments, dyes, antioxidants, polysaccharides, and industrial enzymes. Fungal products are also the primary sources of functional food and nutrition, and their pharmacological products are used for healthy aging. Their molecular properties are validated through the use of recent high-throughput genomic, transcriptomic, and metabolomic tools and techniques. Together, these updated multi-omic tools have been used to study fungal metabolites structure and their mode of action on biological and cellular processes. Diverse groups of fungi produce different proteins and secondary metabolites, which possess tremendous biotechnological and pharmaceutical applications. Furthermore, its use and acceptability can be accelerated by adopting multi-omics, bioinformatics, and machine learning tools that generate a huge amount of molecular data. The integration of artificial intelligence and machine learning tools in the era of omics and big data has opened up a new outlook in both basic and applied researches in the area of nutraceuticals and functional food and nutrition. KEY POINTS: • Multi-omic tool helps in the identification of novel fungal metabolites • Intra-omic data from genomics to bioinformatics • Novel metabolites and application in human health.

Indexed as

Artificial IntelligenceGenomicsHumansMachine LearningMetabolomicsPharmaceutical PreparationsPharmaceutical PreparationsFungal metabolitesMachine learningMetabolomicMulti-omicsTranscriptomic

Identifiers

PMID35546367
PMCPMC9095418

What OpenQuestion holds

Textmetadata
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.