ArticleInternational journal of molecular sciences2014
iHyd-PseAAC: predicting hydroxyproline and hydroxylysine in proteins by incorporating dipeptide position-specific propensity into pseudo amino acid composition.
Article in International journal of molecular sciences, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.
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48 citing papers in PubMed, 201 citations in OpenAlex.
- Article
- Impact of Bioinformatics Search Parameters for Peptides' Identification and Their Post-Translational Modifications: A Case Study of Proteolysed Gelatines from Beef, Pork, and Fish.Foods (Basel, Switzerland) · 2023Article
- Deep Learning-Based Advances In Protein Posttranslational Modification Site and Protein Cleavage Prediction.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Label-Free Method Development for Hydroxyproline PTM Mapping in Human Plasma Proteome.The protein journal · 2021Article
- Article
- iHyd-LysSite (EPSV): Identifying Hydroxylysine Sites in Protein Using Statistical Formulation by Extracting Enhanced Position and Sequence Variant Feature Technique.Current genomics · 2020Article
- Assessing predictors for new post translational modification sites: A case study on hydroxylation.PLoS computational biology · 2020Article
- Identification of DNA NEpigenetics & chromatin · 2020Article
- iSulfoTyr-PseAAC: Identify Tyrosine Sulfation Sites by Incorporating Statistical MomentsCurrent genomics · 2019Article
- iMethylK_pseAAC: Improving Accuracy of Lysine Methylation Sites Identification by Incorporating Statistical Moments and Position Relative Features into General PseAACCurrent genomics · 2019Article
- iProt-Sub: a comprehensive package for accurately mapping and predicting protease-specific substrates and cleavage sites.Briefings in bioinformatics · 2019Review
- Identification of S-nitrosylation sites based on multiple features combination.Scientific reports · 2019Article
- iHyd-PseAAC (EPSV): Identifying Hydroxylation Sites in Proteins by Extracting Enhanced Position and Sequence Variant FeatureCurrent genomics · 2019Article
- Article
- Structural Variability in the RLR-MAVS Pathway and Sensitive Detection of Viral RNAs.Medicinal chemistry (Shariqah (United Arab Emirates)) · 2019Review
- RAACBook: a web server of reduced amino acid alphabet for sequence-dependent inference by using Chou's five-step rule.Database : the journal of biological databases and curation · 2019Article
- LAIPT: Lysine Acetylation Site Identification with Polynomial Tree.International journal of molecular sciences · 2018Article
- iPhosY-PseAAC: identify phosphotyrosine sites by incorporating sequence statistical moments into PseAAC.Molecular biology reports · 2018Article
- A Hybrid Deep Learning Model for Predicting Protein Hydroxylation Sites.International journal of molecular sciences · 2018Article
- Detecting Succinylation sites from protein sequences using ensemble support vector machine.BMC bioinformatics · 2018Article
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Authors and funding
5 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Post-translational modifications (PTMs) play crucial roles in various cell functions and biological processes. Protein hydroxylation is one type of PTM that usually occurs at the sites of proline and lysine. Given an uncharacterized protein sequence, which site of its Pro (or Lys) can be hydroxylated and which site cannot? This is a challenging problem, not only for in-depth understanding of the hydroxylation mechanism, but also for drug development, because protein hydroxylation is closely relevant to major diseases, such as stomach and lung cancers. With the avalanche of protein sequences generated in the post-genomic age, it is highly desired to develop computational methods to address this problem. In view of this, a new predictor called "iHyd-PseAAC" (identify hydroxylation by pseudo amino acid composition) was proposed by incorporating the dipeptide position-specific propensity into the general form of pseudo amino acid composition. It was demonstrated by rigorous cross-validation tests on stringent benchmark datasets that the new predictor is quite promising and may become a useful high throughput tool in this area. A user-friendly web-server for iHyd-PseAAC is accessible at http://app.aporc.org/iHyd-PseAAC/. Furthermore, for the convenience of the majority of experimental scientists, a step-by-step guide on how to use the web-server is given. Users can easily obtain their desired results by following these steps without the need of understanding the complicated mathematical equations presented in this paper just for its integrity.
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