ArticleMolecular therapy. Nucleic acids2017
2L-piRNA: A Two-Layer Ensemble Classifier for Identifying Piwi-Interacting RNAs and Their Function.
Article in Molecular therapy. Nucleic acids, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers.
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Who cites it
64 citing papers in PubMed.
- Databases and computational methods for the identification of piRNA-related molecules: A survey.Computational and structural biotechnology journal · 2024Review
- Decoding the Non-coding: Tools and Databases Unveiling the Hidden World of "Junk" RNAs for Innovative Therapeutic Exploration.ACS pharmacology & translational science · 2024Review
- Sequence based model using deep neural network and hybrid features for identification of 5-hydroxymethylcytosine modification.Scientific reports · 2024Article
- StackDPP: a stacking ensemble based DNA-binding protein prediction model.BMC bioinformatics · 2024Article
- Tissue Recognition Based on Electrical Impedance Classified by Support Vector Machine in Spinal Operation Area.Orthopaedic surgery · 2022Article
- ASRmiRNA: Abiotic Stress-Responsive miRNA Prediction in Plants by Using Machine Learning Algorithms with PseudoInternational journal of molecular sciences · 2022Article
- piRNAs and PIWI Proteins as Diagnostic and Prognostic Markers of Genitourinary Cancers.Biomolecules · 2022Review
- Biological Sequence Classification: A Review on Data and General Methods.Research (Washington, D.C.) · 2022Article
- A GHKNN model based on the physicochemical property extraction method to identify SNARE proteins.Frontiers in genetics · 2022Article
- Identification of intelligence-related proteins through a robust two-layer predictor.Communicative & integrative biology · 2022Article
- A Review of Discovery Profiling of PIWI-Interacting RNAs and Their Diverse Functions in Metazoans.International journal of molecular sciences · 2021Review
- Bioinformatics and Machine Learning Approaches to Understand the Regulation of Mobile Genetic Elements.Biology · 2021Review
- Advances in Computational Methodologies for Classification and Sub-Cellular Locality Prediction of Non-Coding RNAs.International journal of molecular sciences · 2021Review
- The biogenesis and biological function of PIWI-interacting RNA in cancer.Journal of hematology & oncology · 2021Review
- Computational Methods and Online Resources for Identification of piRNA-Related Molecules.Interdisciplinary sciences, computational life sciences · 2021Review
- The Potential Diagnostic and Prognostic Value of Circulating MicroRNAs in the Assessment of Patients With Prostate Cancer: Rational and Progress.Frontiers in oncology · 2021Review
- 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
- 2lpiRNApred: a two-layered integrated algorithm for identifying piRNAs and their functions based on LFE-GM feature selection.RNA biology · 2020Article
- Mal-Light: Enhancing Lysine Malonylation Sites Prediction Problem Using Evolutionary-based Features.IEEE access : practical innovations, open solutions · 2020Article
- Prediction of Recombination Spots Using Novel Hybrid Feature Extraction Method via Deep Learning Approach.Frontiers in genetics · 2020Article
4 more citing papers are in PubMed but not listed here.
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3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Involved with important cellular or gene functions and implicated with many kinds of cancers, piRNAs, or piwi-interacting RNAs, are of small non-coding RNA with around 19-33 nt in length. Given a small non-coding RNA molecule, can we predict whether it is of piRNA according to its sequence information alone? Furthermore, there are two types of piRNA: one has the function of instructing target mRNA deadenylation, and the other does not. Can we discriminate one from the other? With the avalanche of RNA sequences emerging in the postgenomic age, it is urgent to address the two problems for both basic research and drug development. Unfortunately, to the best of our knowledge, so far no computational methods whatsoever could be used to deal with the second problem, let alone deal with the two problems together. Here, by incorporating the physicochemical properties of nucleotides into the pseudo K-tuple nucleotide composition (PseKNC), we proposed a powerful predictor called 2L-piRNA. It is a two-layer ensemble classifier, in which the first layer is for identifying whether a query RNA molecule is piRNA or non-piRNA, and the second layer for identifying whether a piRNA is with or without the function of instructing target mRNA deadenylation. Rigorous cross-validations have indicated that the success rates achieved by the proposed predictor are quite high. For the convenience of most biologists and drug development scientists, the web server for 2L-piRNA has been established at http://bioinformatics.hitsz.edu.cn/2L-piRNA/, by which users can easily get their desired results without the need to go through the mathematical details.
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