ArticleFrontiers in cell and developmental biology2020
DeepCSO: A Deep-Learning Network Approach to Predicting Cysteine S-Sulphenylation Sites.
Article in Frontiers in cell and developmental biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Integrating Redox Proteomics and Computational Modeling to Decipher Thiol-Based Oxidative Post-Translational Modifications (oxiPTMs) in Plant Stress Physiology.International journal of molecular sciences · 2025Review
- PlantNh-Kcr: a deep learning model for predicting non-histone crotonylation sites in plants.Plant methods · 2024Article
- Lactylation prediction models based on protein sequence and structural feature fusion.Briefings in bioinformatics · 2024Article
- EdeepSADPr: an extensive deep-learning architecture for prediction of theFrontiers in cell and developmental biology · 2023Article
- CysModDB: a comprehensive platform with the integration of manually curated resources and analysis tools for cysteine posttranslational modifications.Briefings in bioinformatics · 2022Article
- Article
- CNNArginineMe: A CNN structure for training models for predicting arginine methylation sites based on the One-Hot encoding of peptide sequence.Frontiers in genetics · 2022Article
- Mini-review: Recent advances in post-translational modification site prediction based on deep learning.Computational and structural biotechnology journal · 2022Review
- Development of an experiment-split method for benchmarking the generalization of a PTM site predictor: Lysine methylome as an example.PLoS computational biology · 2021Article
- ECM-LSE: Prediction of Extracellular Matrix Proteins Using Deep Latent Space Encoding of k-Spaced Amino Acid Pairs.Frontiers in bioengineering and biotechnology · 2021Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cysteine S-sulphenylation (CSO), as a novel post-translational modification (PTM), has emerged as a potential mechanism to regulate protein functions and affect signal networks. Because of its functional significance, several prediction approaches have been developed. Nevertheless, they are based on a limited dataset from
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Registered trials
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.