ArticleEvolutionary bioinformatics online2019
iDEF-PseRAAC: Identifying the Defensin Peptide by Using Reduced Amino Acid Composition Descriptor.
Article in Evolutionary bioinformatics online, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 18 citations in OpenAlex.
- RNAincoder: a deep learning-based encoder for RNA and RNA-associated interaction.Nucleic acids research · 2023Article
- Research progress of reduced amino acid alphabets in protein analysis and prediction.Computational and structural biotechnology journal · 2022Review
- Recent development of machine learning-based methods for the prediction of defensin family and subfamily.EXCLI journal · 2022Review
- Identification of Disease-Related 2-Oxoglutarate/Fe (II)-Dependent Oxygenase Based on Reduced Amino Acid Cluster Strategy.Frontiers in cell and developmental biology · 2021Article
- Article
- Identification of cyclin protein using gradient boost decision tree algorithm.Computational and structural biotechnology journal · 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
- 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
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Defensins as 1 of major classes of host defense peptides play a significant role in the innate immunity, which are extremely evolved in almost all living organisms. Developing high-throughput computational methods can accurately help in designing drugs or medical means to defense against pathogens. To take up such a challenge, an up-to-date server based on rigorous benchmark dataset, referred to as iDEF-PseRAAC, was designed for predicting the defensin family in this study. By extracting primary sequence compositions based on different types of reduced amino acid alphabet, it was calculated that the best overall accuracy of the selected feature subset was achieved to 92.38%. Therefore, we can conclude that the information provided by abundant types of amino acid reduction will provide efficient and rational methodology for defensin identification. And, a free online server is freely available for academic users at http://bioinfor.imu.edu.cn/idpf. We hold expectations that iDEF-PseRAAC may be a promising weapon for the function annotation about the defensins protein.
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