ArticleDatabase : the journal of biological databases and curation2019
RAACBook: a web server of reduced amino acid alphabet for sequence-dependent inference by using Chou's five-step rule.
Article in Database : the journal of biological databases and curation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
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- Deciphering Sequence Determinants of Zygotic Genome Activation Genes: Insights From Machine Learning and the ZGAExplorer Platform.Cell proliferation · 2025Article
- PCBert-Kla: an efficient prediction method for lysine lactylation sites based on ProtBert and fusion of physicochemical features.Briefings in bioinformatics · 2025Article
- Benchmarking Machine Learning Models for HIV-1 Protease Inhibitor Resistance Prediction: Impact of Data Set Construction and Feature Representation.Journal of chemical information and modeling · 2025Article
- Empirical Comparison and Analysis of Artificial Intelligence-Based Methods for Identifying Phosphorylation Sites of SARS-CoV-2 Infection.International journal of molecular sciences · 2024Review
- A robust deep learning approach for identification of RNA 5-methyluridine sites.Scientific reports · 2024Article
- A First Computational Frame for Recognizing Heparin-Binding Protein.Diagnostics (Basel, Switzerland) · 2023Article
- ATTIC is an integrated approach for predicting A-to-I RNA editing sites in three species.Briefings in bioinformatics · 2023Article
- Empirical comparison and recent advances of computational prediction of hormone binding proteins using machine learning methods.Computational and structural biotechnology journal · 2023Review
- Identifying Transcription Factors That Prefer Binding to Methylated DNA Using ReducedACS omega · 2022Article
- Research progress of reduced amino acid alphabets in protein analysis and prediction.Computational and structural biotechnology journal · 2022Review
- IBPred: A sequence-based predictor for identifying ion binding protein in phage.Computational and structural biotechnology journal · 2022Article
- Identification ofComputational and mathematical methods in medicine · 2022Article
- Immunoglobulin Classification Based on FC* and GC* Features.Frontiers in genetics · 2021Article
- ANPrAod: Identify Antioxidant Proteins by Fusing Amino Acid Clustering Strategy andComputational and mathematical methods in medicine · 2021Article
- Amino Acid Reduction Can Help to Improve the Identification of Antimicrobial Peptides and Their Functional Activities.Frontiers in genetics · 2021Article
- Application of Machine Learning for Drug-Target Interaction Prediction.Frontiers in genetics · 2021Review
- Identification of Disease-Related 2-Oxoglutarate/Fe (II)-Dependent Oxygenase Based on Reduced Amino Acid Cluster Strategy.Frontiers in cell and developmental biology · 2021Article
- Identification of cyclin protein using gradient boost decision tree algorithm.Computational and structural biotechnology journal · 2021Article
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8 authors.
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Abstract
By reducing amino acid alphabet, the protein complexity can be significantly simplified, which could improve computational efficiency, decrease information redundancy and reduce chance of overfitting. Although some reduced alphabets have been proposed, different classification rules could produce distinctive results for protein sequence analysis. Thus, it is urgent to construct a systematical frame for reduced alphabets. In this work, we constructed a comprehensive web server called RAACBook for protein sequence analysis and machine learning application by integrating reduction alphabets. The web server contains three parts: (i) 74 types of reduced amino acid alphabet were manually extracted to generate 673 reduced amino acid clusters (RAACs) for dealing with unique protein problems. It is easy for users to select desired RAACs from a multilayer browser tool. (ii) An online tool was developed to analyze primary sequence of protein. The tool could produce K-tuple reduced amino acid composition by defining three correlation parameters (K-tuple, g-gap, λ-correlation). The results are visualized as sequence alignment, mergence of RAA composition, feature distribution and logo of reduced sequence. (iii) The machine learning server is provided to train the model of protein classification based on K-tuple RAAC. The optimal model could be selected according to the evaluation indexes (ROC, AUC, MCC, etc.). In conclusion, RAACBook presents a powerful and user-friendly service in protein sequence analysis and computational proteomics. RAACBook can be freely available at http://bioinfor.imu.edu.cn/raacbook. Database URL: http://bioinfor.imu.edu.cn/raacbook.
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