ArticlePeerJ2013
iSNO-AAPair: incorporating amino acid pairwise coupling into PseAAC for predicting cysteine S-nitrosylation sites in proteins.
Article in PeerJ, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers.
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Who cites it
77 citing papers in PubMed.
- Deep learning framework with interpretable feature selection for accurate SUMOylation site prediction.Scientific reports · 2026Article
- The evolution of S-nitrosylation detection methodology and the role of protein S-nitrosylation in various cancers.Cancer cell international · 2024Review
- iDLB-Pred: identification of disordered lipid binding residues in protein sequences using convolutional neural network.Scientific reports · 2024Article
- Protein S-Nitrosylation: A Chemical Modification with Ubiquitous Biological Activities.The protein journal · 2024Review
- PPSNO: A Feature-Rich SNO Sites Predictor by Stacking Ensemble Strategy from Protein Sequence-Derived Information.Interdisciplinary sciences, computational life sciences · 2024Article
- The ROP2 GTPase Participates in Nitric Oxide (NO)-Induced Root Shortening in Arabidopsis.Plants (Basel, Switzerland) · 2023Article
- A machine learning technique for identifying DNA enhancer regions utilizing CIS-regulatory element patterns.Scientific reports · 2022Article
- Mini-review: Recent advances in post-translational modification site prediction based on deep learning.Computational and structural biotechnology journal · 2022Review
- Proteomic Analysis ofFrontiers in plant science · 2022Article
- Biological Mechanisms ofAntioxidants (Basel, Switzerland) · 2021Review
- Recent Advances in Predicting Protein S-Nitrosylation Sites.BioMed research international · 2021Review
- S-Nitrosation of E3 Ubiquitin Ligase Complex Components Regulates Hormonal Signalings in Arabidopsis.Frontiers in plant science · 2021Article
- iTAGPred: A Two-Level Prediction Model for Identification of Angiogenesis and Tumor Angiogenesis Biomarkers.Applied bionics and biomechanics · 2021Article
- iSUMOK-PseAAC: prediction of lysine sumoylation sites using statistical moments and Chou's PseAAC.PeerJ · 2021Article
- Yin and Yang in Post-Translational Modifications of Human D-Amino Acid Oxidase.Frontiers in molecular biosciences · 2021Article
- Evolutionary insights into the active-site structures of the metallo-β-lactamase superfamily from a classification study with support vector machine.Journal of biological inorganic chemistry : JBIC : a publication of the Society of Biological Inorganic Chemistry · 2020Article
- A pan-cancer assessment of alterations of the kinase domain of ULK1, an upstream regulator of autophagy.Scientific reports · 2020Article
- Prediction of Recombination Spots Using Novel Hybrid Feature Extraction Method via Deep Learning Approach.Frontiers in genetics · 2020Article
- A Linear Regression Predictor for Identifying NMolecular therapy. Nucleic acids · 2019Article
- iN6-methylat (5-step): identifying DNA NMolecular genetics and genomics : MGG · 2019Article
17 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As one of the most important and universal posttranslational modifications (PTMs) of proteins, S-nitrosylation (SNO) plays crucial roles in a variety of biological processes, including the regulation of cellular dynamics and many signaling events. Knowledge of SNO sites in proteins is very useful for drug development and basic research as well. Unfortunately, it is both time-consuming and costly to determine the SNO sites purely based on biological experiments. Facing the explosive protein sequence data generated in the post-genomic era, we are challenged to develop automated vehicles for timely and effectively determining the SNO sites for uncharacterized proteins. To address the challenge, a new predictor called iSNO-AAPair was developed by taking into account the coupling effects for all the pairs formed by the nearest residues and the pairs by the next nearest residues along protein chains. The cross-validation results on a state-of-the-art benchmark have shown that the new predictor outperformed the existing predictors. The same was true when tested by the independent proteins whose experimental SNO sites were known. A user-friendly web-server for iSNO-AAPair was established at http://app.aporc.org/iSNO-AAPair/, by which users can easily obtain their desired results without the need to follow the mathematical equations involved during its development.
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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.