Evidence map›Paper›PMID 41645295›Full record

ArticleGenome biology2026

FungiGuard: identification of plant antifungal peptides with artificial intelligence.

Xiang Li, Yitian Fang, You Wu, Xiang Yu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genome biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Xiang Li *Joint International Research Laboratory of Metabolic & Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China.
Yitian Fang *Shanghai Frontiers Science Center of Drug Target Identification and Delivery, National Key Laboratory of Innovative Immunotherapy, School of Pharmaceutical Sciences, Shanghai Jiao Tong University, Shanghai, 200240, China.
You WuJoint International Research Laboratory of Metabolic & Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China. wuyou1990@sjtu.edu.cn.
Xiang YuJoint International Research Laboratory of Metabolic & Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China. yuxiang2021@sjtu.edu.cn.

Funding

National Natural Science Foundation of China 32170581National Natural Science Foundation of China 32500568Shanghai Municipal Education Commission 2024AIYB005Shanghai Municipal Science and Technology Commission 25JS2850100Shanghai Municipal Science and Technology Commission 25ZR1402261
6 · The paper itself

Abstract

Antifungal peptides (AFPs) are crucial for plant defense against biotic stress. Yet, no artificial intelligence tool specifically classifies plant AFPs. To fill this gap, we develop FungiGuard, which integrates Random Forest, Long Short-Term Memory, and attention mechanisms to identify AFPs using functionally annotated plant small peptides. FungiGuard outperforms existing generalized AFP model in classifying plant AFPs, and detects candidate AFPs in Arabidopsis, wheat, rice, and maize. It also discovers novel AFPs through randomly generated sequences. Experimental validation confirms the antifungal activity of candidate AFP against Botrytis cinerea. This tool deepens plant AFP understanding and facilitates novel AFP discovery.

Indexed as

Antifungal AgentsAntimicrobial PeptidesArtificial IntelligencePeptidesPlant ProteinsPlantsSoftwareArabidopsisBotrytisPlant DiseasesRandom ForestAntifungal AgentsAntimicrobial PeptidesPeptidesPlant ProteinsArtificial intelligenceBotrytis cinereaNon-conventional peptidePlant antifungal peptideSmall peptide

Identifiers

PMID41645295
PMCPMC12977696

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.