Evidence map›Paper›PMID 26904083›Full record

ReviewFrontiers in plant science2016

Computational Prediction of Effector Proteins in Fungi: Opportunities and Challenges.

Humira Sonah, Rupesh K Deshmukh, Richard R Bélanger

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in plant science, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers.

0numbers the graph read from it
0cells of the map it votes in
68citing papers in PubMed
30.8field-weighted citation impact, top 1% of its field
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

68 citing papers in PubMed, 132 citations in OpenAlex.

  1. Article
  2. Article
  3. Genomic and Functional Characterization of anLife (Basel, Switzerland) · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Profiling the Genomes and Secreted Effector Proteins inJournal of fungi (Basel, Switzerland) · 2025
    Article
  11. Article
  12. How genomics can help unravel the evolution of endophytic fungi.World journal of microbiology & biotechnology · 2025
    Review
  13. Review
  14. Article
  15. Article
  16. Article
  17. Frontiers in microbiology · 2024
    Article
  18. Host Recognition and Specific Infection ofJournal of fungi (Basel, Switzerland) · 2023
    Article
  19. Article
  20. TheInternational journal of molecular sciences · 2023
    Article

8 more citing papers are in PubMed but not listed here.

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

3 authors at 1 institution in 1 country.

Humira SonahDépartement de Phytologie, Faculté des Sciences de l'Agriculture et de l'Alimentation, Centre de Recherche en Horticulture, Université Laval, Québec QC, Canada.
Rupesh K DeshmukhDépartement de Phytologie, Faculté des Sciences de l'Agriculture et de l'Alimentation, Centre de Recherche en Horticulture, Université Laval, Québec QC, Canada.
Richard R BélangerDépartement de Phytologie, Faculté des Sciences de l'Agriculture et de l'Alimentation, Centre de Recherche en Horticulture, Université Laval, Québec QC, Canada.
Université Laval · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Effector proteins are mostly secretory proteins that stimulate plant infection by manipulating the host response. Identifying fungal effector proteins and understanding their function is of great importance in efforts to curb losses to plant diseases. Recent advances in high-throughput sequencing technologies have facilitated the availability of several fungal genomes and 1000s of transcriptomes. As a result, the growing amount of genomic information has provided great opportunities to identify putative effector proteins in different fungal species. There is little consensus over the annotation and functionality of effector proteins, and mostly small secretory proteins are considered as effector proteins, a concept that tends to overestimate the number of proteins involved in a plant-pathogen interaction. With the characterization of Avr genes, criteria for computational prediction of effector proteins are becoming more efficient. There are 100s of tools available for the identification of conserved motifs, signature sequences and structural features in the proteins. Many pipelines and online servers, which combine several tools, are made available to perform genome-wide identification of effector proteins. In this review, available tools and pipelines, their strength and limitations for effective identification of fungal effector proteins are discussed. We also present an exhaustive list of classically secreted proteins along with their key conserved motifs found in 12 common plant pathogens (11 fungi and one oomycete) through an analytical pipeline.

Indexed as

classification and predictioncomputational tool and serverseffector proteinsfungal secretomehost–pathogen interaction

Identifiers

PMID26904083
PMCPMC4751359
OpenAlexW2255352529

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.