Papers › ItLnc-BXE: a Bagging-XGBoost-ensemble method with multiple features for identification...
ItLnc-BXE: a Bagging-XGBoost-ensemble method with multiple features for identification of plant lncRNAs
Guangyan Zhang, Ziru Liu, Jichen Dai, Zilan Yu, Shuai Liu, Wen Zhang
Motivation: Since long non-coding RNAs (lncRNAs) have involved in a wide range of functions in cellular and developmental processes, an increasing number of methods have been proposed for distinguishing lncRNAs from coding RNAs. However, most of the existing methods are designed for lncRNAs in animal systems, and only a few methods focus on the plant lncRNA identification. Different from lncRNAs in animal systems, plant lncRNAs have distinct characteristics. It is desirable to develop a computational method for accurate and robust identification of plant lncRNAs. Results: Herein, we present a plant lncRNA identification method ItLnc-BXE, which utilizes multiple features and the ensemble learning strategy. First, a diversity of lncRNA features is collected and filtered by feature selection to represent RNA transcripts. Then, several base learners are trained and further combined into a single meta-learner by ensemble learning, and thus an ItLnc-BXE model is constructed. ItLnc-BXE models are evaluated on datasets of six plant species, the results show that ItLnc-BXE outperforms other state-of-the-art plant lncRNA identification methods, achieving better and robust performances (AUC>95.91%). We also perform some experiments about cross-species lncRNA identification, and the results indicate that dicots-based and monocots-based models can be used to accurately identify lncRNAs in lower plant species, such as mosses and algae. Availability: source codes are available at https://github.com/BioMedicalBigDataMiningLab/ItLnc-BXE. Contact: zhangwen@mail.hzau.edu.cn (or) zhangwen@whu.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Tasks
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Methods
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections