AraPathogen2.0: An Improved Prediction of Plant–Pathogen Protein–Protein Interactions Empowered by the Natural Language Processing Technique-Reference-Cited by-同舟云学术

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AraPathogen2.0: An Improved Prediction of Plant–Pathogen Protein–Protein Interactions Empowered by the Natural Language Processing Technique

Published:2023-12-09 Issue:1 Volume:23 Page:494-499
ISSN:1535-3893
Container-title:Journal of Proteome Research
language:en
Short-container-title:J. Proteome Res.

Author:

Lei Chenping¹^ORCID,Zhou Kewei¹,Zheng Jingyan¹,Zhao Miao¹,Huang Yan¹,He Huaqin²,Yang Shiping³,Zhang Ziding¹^ORCID

Affiliation:

1. State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing 100193, China

2. College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China

3. State Key Laboratory of Plant Environmental Resilience, College of Biological Sciences, China Agricultural University, Beijing 100193, China

Funder

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Subject

General Chemistry,Biochemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jproteome.3c00364

Reference19 articles.

1. The plant immune system

2. Action Mechanisms of Effectors in Plant-Pathogen Interaction

3. Bioinformatic tools support decision-making in plant disease management

4. Independently Evolved Virulence Effectors Converge onto Hubs in a Plant Immune System Network

5. Convergent Targeting of a Common Host Protein-Network by Pathogen Effectors from Three Kingdoms of Life

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1. What NLR you recognizing? Predicted binding affinities- and energies may be used to identify novel NLR-effector interactions;2024-07-27

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