LinDing Group


Welcome to iLoc-LncRNA

    Long non-coding RNAs (lncRNAs) are a class of RNA molecules with more than 200 bases that have important functions in cell development and metabolism, including genetic markers, genome rearrangements, chromatin modifications, cell cycle regulation, transcription and Translation, etc. And its function is also closely related to the location of the cell. The aberrant expression of lncRNAs is associated with several types of cancer, Alzheimer's disease, etc. Therefore, it is highly desirable to use machine learning methods to predict the subcellular location of LncRNAs. In this work, a feature-based strategy for nucleotide sequence-based characterization was developed by constructing a dataset based on the RNALocate database, and then the binomial distribution was used to screen the optimal feature set. We found that the proposed method has the maximum overall accuracy of 86.72% and the average accuracy of 59.95% in the jackknife cross-validation, suggesting that the proposed predictor is promising and will provide important guidance in this area.